Control method for information processing equipment

Abstract

To provide information about the authenticity of information obtained through public lines by taking the state of a reader into consideration.SOLUTION: An information processing device (1) includes a communication unit (61,62,63) that connects to a network (612), and a control unit (11). The control unit performs control to receive information, and a degree of information fake concerning the authenticity of the information via the communication unit, calculate an index of individual fake concerning the authenticity judgment tendency of a user, calculate a degree of information correction fake obtained by correcting the degree of information fake based on the index of individual fake, and output a warning based on the degree of information correction fake calculated for the information when the information is transmitted from the communication unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an information processing device. Control method This relates, in particular, to technologies that provide users with credibility regarding information. [Background technology]

[0002] In recent years, portable information terminals (information display devices), such as smartphones, have become commonplace. Smartphones can connect to the internet via telephone lines or LANs (Local Area Networks) and obtain various types of information from external servers. Furthermore, as personal information terminals, smartphones can acquire information about the individual user operating the smartphone through application software and various sensors.

[0003] Patent Document 1 discloses a system for determining the credibility of news obtained via the internet, stating that "received news content is evaluated, and relevant media sources, relevant journalists, and at least one relevant predetermined topic can be identified. The current scores of each of the relevant media sources, relevant journalists, and at least one relevant predetermined topic can be identified based on stored information. A credibility score can be assigned based on the identified current scores of the relevant media sources, relevant journalists, and at least one relevant predetermined topic. The display associated with the received news content can be modified based on the generated credibility score. (Abstract Excerpt)" [Prior art documents] [Patent Documents]

[0004] [Patent Document 1] Special table 2020-508518 publication [Overview of the Initiative] [Problems that the invention aims to solve]

[0005] Information obtained via the internet is not limited to news content; it also includes content shared by individuals through social media. The reliability of information obtained via the internet, including this type of content, can be uncertain, posing a risk of deception for readers. Furthermore, well-meaning recipients may inadvertently spread unreliable information through social media.

[0006] On the other hand, just as some readers are deceived by the same information while others are not, whether or not a reader is deceived by a piece of content depends not only on the credibility of the content itself, but also on the extent to which the reader pays attention to the credibility of the content.

[0007] While Patent Document 1 can identify the credibility of news content itself, it does not consider the degree of risk that individual readers who encounter that news content may come to believe it. Furthermore, while Patent Document 1 can identify the credibility of news content from which the source media or journalist can be identified, it remains problematic that it cannot identify the credibility of information disseminated by ordinary individuals or anonymously, such as content transmitted via social media.

[0008] Therefore, the present invention aims to provide information regarding the credibility of information acquired via public networks such as the Internet and broadcasting networks (this acquired information is displayed on the display screen of an information display device, and is therefore hereinafter referred to as "displayed information"), taking into account the reader's circumstances, not limited to news content. [Means for solving the problem]

[0009] To solve the aforementioned problems, the present invention patent The present invention comprises the configuration described in the claims. For example, the present invention is an information processing apparatus. Control method And, The aforementioned information processing device Connect to the network do communication The steps to take,Receive information and the degree of information forgery regarding the authenticity of the information The steps to take, Judgment tendency of user authenticity Based on indicators that show Calculate individual forgery degrees The steps to take, Calculate the corrected information forgery degree by correcting the information forgery degree based on the individual forgery degrees The steps to take, The information Send When trying to believe the information, control to output a warning based on the calculated corrected information forgery degree for the information The invention is characterized by including a step.

Advantages of the Invention

[0010] According to the present invention, not limited to news content, information regarding the authenticity of information obtained via public networks such as the Internet and broadcast networks can be provided in consideration of the reader's state. The objects, configurations, and effects of the present invention other than those described above will be clarified in the following embodiments.

Brief Description of the Drawings

[0011] [Figure 1] Schematic diagram for explaining the outline of the information display device according to this embodiment [Figure 2] Hardware configuration diagram showing an example of the internal configuration of a smartphone [Figure 3] Functional block diagram showing an example of the functional block configuration in the first embodiment [Figure 4] Flowchart showing the processing procedure of forgery degree display processing in the first embodiment [Figure 5] Diagram showing an example of the display of display information in the first embodiment [Figure 6] Diagram showing an example of the display by the display processing during the calculation of the user individual forgery degree in the first embodiment [Figure 7] Flowchart showing the processing procedure of the information forgery degree calculation processing in the first embodiment [Figure 8] Flowchart showing the processing procedure of the personality information acquisition processing in the first embodiment [Figure 9] User individual forgery degree coefficient table in the first embodiment [Figure 10] This figure shows an example of the display using the user-specific fakeness level display processing in the first embodiment. [Figure 11] A schematic diagram illustrating the outline of the second embodiment. [Figure 12] A functional block diagram showing an example of a functional block configuration in the second embodiment. [Figure 13] A flowchart showing the processing procedure for displaying the degree of fakeness in the second embodiment. [Figure 14] A flowchart showing the processing procedure for acquiring physical information in the second embodiment. [Figure 15] User-specific fake degree coefficient table in the second embodiment. [Figure 16] A functional block diagram showing an example of a functional block configuration in the third embodiment. [Figure 17] A flowchart showing the processing procedure for displaying the degree of fakeness in the third embodiment. [Figure 18] User-specific fake degree coefficient table in the third embodiment. [Figure 19] A schematic diagram illustrating the outline of the fourth embodiment. [Figure 20] A functional block diagram showing an example of a functional block configuration in the fourth embodiment. [Figure 21] A flowchart showing the processing procedure for displaying the degree of fakeness in the fourth embodiment. [Modes for carrying out the invention]

[0012] Hereinafter, examples of embodiments of the present invention will be described with reference to the drawings. The same reference numerals are used for the same elements in all drawings, and redundant explanations are omitted.

[0013] <First Embodiment> Figure 1 is a schematic diagram illustrating the overview of the information display device according to this embodiment.

[0014] Figure 1 shows a user 10 operating a smartphone 1 as an information display device, acquiring display information from a WEB (World Wide Web) page 613 and a SNS (Social Networking Service) 614 via the internet 612, and displaying it on the display screen 711 of the smartphone 1. In this embodiment, a smartphone 1 is used as an example of an information display device, but any device that has the function of receiving and displaying display information from the internet 612 or SNS 613 may also be used, such as a portable information terminal like a tablet or an information processing device like a PC.

[0015] There are several methods by which the smartphone 1 can connect to the internet 612, including a method via a mobile phone base station 621 which is part of the mobile phone network, and a method via a wireless LAN router (Wi-Fi® router) 611. However, in any case, the background of this embodiment is the same in that it involves connecting to the internet 612.

[0016] Furthermore, an external server 615 that transmits fake information is connected to the internet 612. The smartphone 1 is configured to obtain the fake information necessary for carrying out this embodiment from the external server 615. This external server 615 may be connected to a fake information dissemination management site, or it may be an independent server that transmits fake information.

[0017] The information displayed by user 10 operating smartphone 1 via the internet 612 (such as information displayed from web pages 613 and information displayed from social networking services 614) may contain some information of questionable credibility. (In Figure 1, this is labeled "Fake information?".)

[0018] In this embodiment, the degree of credibility is referred to as the "fake degree." The fake degree is the opposite of the degree of credibility (0% to 100%), with a degree of 0% corresponding to a degree of 100% and a degree of 0% corresponding to a degree of 100%. In other words, the fake degree (%) is the value obtained by subtracting the degree of credibility (%) from 100%.

[0019] In this embodiment, smartphone 1 obtains fake-related information from an external server 615 that transmits fake-related information, and calculates the degree of fakery through internal processing of smartphone 1. Of course, if the displayed information itself is accompanied by fake-related information related to that displayed information, it is used as is.

[0020] When user 10 encounters information displayed on the internet 612 or social networking services 613, even if the displayed information is the same, the likelihood of being deceived differs depending on user 10's personality and knowledge. In other words, since users perceive the degree of fakery in displayed information differently, even when encountering the same displayed information, some users will be deceived while others will not.

[0021] Therefore, in this embodiment, a user-specific fake degree coefficient, which indicates the degree to which a user 10 operating the smartphone 1 can judge the truthfulness of the displayed information, is calculated based on an index representing the user's tendency to judge credibility. This coefficient is then used to correct the fake degree (information fake degree) inherent in the displayed information, and the fake degree is optimized by taking into account the user's personality information (susceptibility to being deceived). The optimized fake degree corresponds to the user-specific fake degree in this specification and is the fake degree that is displayed.

[0022] The degree of information fakery is calculated using credibility characteristics derived from the displayed information. Specific examples of "credibility characteristics derived from the displayed information" may include the type of site where the displayed information is published, information indicating the author of the displayed information, information indicating the publisher of the displayed information, evaluation information assigned by the publisher of the displayed information after evaluating its credibility, the time when the displayed information was disseminated via the public network, the speed at which the displayed information was disseminated via the public network, and at least one or any combination of the textual expressions included in the displayed information. The degree of information fakery can be calculated by smartphone 1 based on the credibility characteristics derived from the displayed information, or it can be acquired by smartphone 1 by acquiring an already calculated degree of information fakery (reception is one form of acquisition). In the case of acquisition, as explained later, the information fakery calculation process can be omitted, and the degree of information fakery of the displayed information can be acquired simultaneously with or at a different time when the displayed information is received.

[0023] The "indicator representing the user's tendency to judge credibility" used in calculating the user-specific fake-rate coefficient is a value that changes according to the user's susceptibility to deception. Users with a cautious personality are considered more susceptible to deception than those who are not. Furthermore, even the same user is considered more susceptible to deception when, for example, they are excited, anxious, or disoriented due to an emergency. Therefore, it is possible to diagnose the user's susceptibility to deception in advance and use the results of that diagnosis as an indicator. In addition, when a person is excited or anxious, changes in physical state such as increased blood pressure, increased heart rate, increased respiratory rate, and increased body temperature are likely to occur, so physical information may also be used as an indicator. The embodiment of using this physical information as an indicator will be explained in more detail in <Second Embodiment> below.

[0024] In Figure 1, the determined degree of fakery is displayed as a bar graph in the fakery degree area 713 of the display screen 711. The display format of the fakery degree will be described later.

[0025] Figure 2 is a hardware configuration diagram showing an example of the internal configuration of smartphone 1.

[0026] The smartphone 1 includes a main processor 2, storage 4, GPS receiver 51, geomagnetic sensor group 52, accelerometer group 53, gyroscope sensor group 54, LAN communication device 61, telephone network communication device 62, short-range wireless communication device 63, broadcast receiver 64, display 71, front camera 72, rear camera 73, microphone 81, speaker 82, touch sensor 91, and operation keys 92, and each component is connected to the others via a system bus 3.

[0027] The main processor 2 is a microprocessor unit that controls the entire smartphone 1 according to a predetermined operating program.

[0028] System bus 3 is a data communication channel for sending and receiving various commands and data between the main processor 2 and each component block within the smartphone 1.

[0029] Storage 4 includes a ROM 41 that stores programs for controlling the operation of the smartphone 1, a non-volatile memory 42 that stores various data such as operation settings, detected values ​​from each sensor, and library information downloaded from objects and libraries containing content, and a rewritable RAM 43 that includes a work area used for various program operations.

[0030] Furthermore, storage 4 can store operating programs downloaded from the network, as well as various data created by those operating programs. It can also store content such as videos, still images, and audio downloaded from the network. In addition, it can store data such as videos and still images taken using the shooting functions of the front camera 72 and rear camera 73. Moreover, storage 4 needs to retain the information it stores even when the smartphone 1 is not supplied with external power. Therefore, devices such as semiconductor memory elements like flash ROM or SSD (Solid State Drive), or magnetic disk drives like HDD (Hard Disc Drive) are used. Note that each operating program stored in storage 4 can be updated and its functions expanded by downloading from an external server 615.

[0031] Smartphone 1 is equipped with a GPS (Global Positioning System) receiver 51, a group of geomagnetic sensors 52, a group of accelerometers 53, and a group of gyroscopes 54. These sensors enable the detection of the position, tilt, direction, movement, etc., of Smartphone 1. Smartphone 1 may also be equipped with other sensors such as an illuminance sensor, an altitude sensor, and a proximity sensor.

[0032] The LAN communication device 61 is connected to the internet 612 via an access point or the like, and transmits and receives data with an external server 615 on the internet 612. The connection to the access point or the like may be made via wireless communication such as Wi-Fi (registered trademark). (In this embodiment, a wireless LAN router 611 is assumed.)

[0033] The telephone network communication device 62 performs telephone communication (calls) and data transmission / reception via wireless communication with a mobile phone base station 621, etc., of the mobile telephone communication network. Communication with the mobile phone base station 621, etc., may be performed using W-CDMA (Wideband Code Division Multiple Access) (registered trademark), GSM (Global System for Mobile communications), LTE (Long Term Evolution), or other communication methods.

[0034] The short-range wireless communication device 63 exchanges information with external Bluetooth® devices and external NFC-compatible devices using Bluetooth® communication or NFC standard communication.

[0035] The broadcast receiver 64 receives broadcast signals such as TV broadcasts and radio broadcasts.

[0036] The LAN communication device 61, the telephone network communication device 62, the short-range wireless communication device 63, and the broadcast receiver 64 each include encoding circuits, decoding circuits, antennas, etc. In addition to the above communication devices, other communication devices such as infrared communication devices may also be included.

[0037] The display 71 is a display device such as a backlit liquid crystal display or a self-emissive organic EL display, and it displays and provides to the user 10 image data, video data, news content, text information, or image and video information captured by the front camera 72 or rear camera 73, which are obtained via the internet 612.

[0038] The front camera 72 is located on the same surface as the display 71 of the smartphone 1. It is used to capture an image of the user 10's face in order to identify the user 10.

[0039] The rear camera 73 is located on the back of the smartphone 1 and is used to capture images of landscapes, etc.

[0040] The front camera 72 and the rear camera 73 are cameras that input image information of the surroundings and objects by converting light input from the lens into electrical signals using electronic devices such as CCD (Charge Coupled Device) and CMOS (Complementary Metal Oxide Semiconductor) sensors.

[0041] Microphone 81 converts sounds from the real world, user voices, etc., into audio information for input.

[0042] Speaker 82 outputs necessary audio information to the user. Of course, earphones and headphones can also be connected, allowing users to choose the appropriate speaker for their needs.

[0043] The touch sensor 91 is stacked and arranged on the display screen 711 of the display 71.

[0044] The operation key 92 is composed of a series of button switches and the like.

[0045] The touch sensor 91 and operation key 92 are examples of operation input devices for inputting operation instructions to the smartphone 1, and other operation input devices may also be used. Alternatively, the smartphone 1 may be operated using a separate mobile terminal device connected via wired or wireless communication using a LAN communication device 61 or a short-range wireless communication device 63.

[0046] Alternatively, the system may analyze the video footage captured by the front camera 72 and use gestures or other actions to control the smartphone 1.

[0047] Note that the example hardware configuration of smartphone 1 shown in Figure 2 includes many components that are not essential to this embodiment, but the effects of this embodiment will not be impaired even if these components are not included. Furthermore, additional components not shown, such as an electronic money payment function, may also be included.

[0048] (Functional block of this embodiment) Figure 3 is a functional block diagram showing an example of a functional block configuration in the first embodiment.

[0049] The control unit 11 is responsible for controlling the entire smartphone 1, and is mainly composed of the main processor 2 reading a program stored in the ROM 41 of the storage 4 and loading it into the RAM 43.

[0050] The communication processing unit 12 has the function of performing communication processing for connecting to the Internet 612 using the LAN communication device 61 and the telephone network communication device 62.

[0051] The display information acquisition unit 13 has the function of acquiring display information from web pages 613 and display information from SNS 614, etc., via the internet 612 using the communication processing unit 12.

[0052] The display information storage unit 14 has the function of storing the display information obtained by the display information acquisition unit 13 in the non-volatile memory 42 of the storage unit 4.

[0053] The fake information acquisition unit 15 is a function that acquires fake-related information from an external server 615 that transmits fake-related information, via the communication processing unit 12. The external server 615 verifies (fact-checks) the information displayed on web pages 613 and social networking services (SNS) and transmits fake-related information including the verification results. For example, a media partner of the Fact Check Initiative Japan (FIJ) can be used as the external server 615.

[0054] The Information Fake Degree Calculation Unit 16 is a function that uses AI (Artificial Intelligence) processing to infer the fake-related information acquired by the Fake-Related Information Acquisition Unit 15, and calculates the fake degree of the inferred displayed information. The AI ​​processing involves learning the regularity and rules of the data to derive inferences. The fake degree is calculated by the AI ​​processing based on information related to fakes, past displayed information and the accuracy of its credibility, etc.

[0055] Furthermore, if the fake-related information acquisition unit 15 is unable to acquire fake information, the information fake-degree calculation unit 16 utilizes past fake information and infers the degree of fakeness through AI processing. The information fake-degree calculation unit 16 may also calculate the degree of fakeness using conventional rule-based calculation processing without using AI processing.

[0056] The information fake degree data storage unit 17 has the function of storing the fake degree (hereinafter referred to as "information fake degree" as it is a fake degree related to the displayed information) obtained by the information fake degree calculation unit 16, together with the corresponding displayed information, in the non-volatile memory 42 or RAM 43 of the storage 4.

[0057] The personality information acquisition unit 18 is a function that acquires information about the personality (susceptibility to deception) of user 10 who is operating smartphone 1. The personality information acquisition unit 18 presents various questions to user 10 who is operating smartphone 1, and makes a personality judgment, including the susceptibility to deception of user 10, based on the answers to those questions. The personality information acquisition unit 18 generates personality information by converting the results of the personality judgment into, for example, a score indicating susceptibility to deception.

[0058] The personality information storage unit 19 has the function of storing information about the user 10's personality (susceptibility to deception) acquired by the personality information acquisition unit 18 in the non-volatile memory 42 of the storage 4, associating it with information that uniquely identifies the user 10 (user identification information). The user identification information may be physical characteristic information such as the user 10's face image captured by the front camera 72, iris information, fingerprint information read from a fingerprint sensor (not shown), or voiceprint information of the user 10 collected from the microphone 81, or it may simply be the user 10's name.

[0059] The user-specific fake degree coefficient calculation unit 20 determines the personality information stored by the personality information storage unit 19 and calculates a coefficient (weighting) for the information fake degree obtained by the information fake degree calculation unit 16. The user-specific fake degree coefficient calculation unit 20 determines the fake degree to be displayed. The coefficient (weighting) for the information fake degree will be described later.

[0060] The display data output unit 21 is a function that displays the display information stored in the non-volatile memory 42 of the storage 4 by the display information storage unit 14, as well as the degree of fakery (hereinafter referred to as "user-specific fakery degree") which takes into account the user's personality information, on the display screen 711 of the smartphone 1. The final user-specific fakery degree displayed on the display screen 711 of the smartphone 1 will be described later.

[0061] (Processing procedure for displaying the degree of fakery) Figure 4 is a flowchart showing the processing procedure for displaying the degree of fakeness (corresponding to the information display method) in this embodiment. The processing procedure in Figure 4 will be explained with reference to the functional block diagram in Figure 3.

[0062] When the main processor 2 starts processing the fakeness level display (S411), the display information acquisition unit 13 acquires the display information to be displayed on the smartphone 1 (S412).

[0063] Next, the main processor 2 stores the display information acquired in the display information acquisition process (S412) in the non-volatile memory 42 of the storage 4 using the display information storage unit 14 (S413).

[0064] Next, the main processor 2 outputs the display information saved in the display information saving process (S413) to the display screen 711 of the smartphone 1 via the display data output unit 21 (S414) and displays it. The display of the display information by this display information screen output process (S414) is the same as the display information on a typical smartphone 1.

[0065] Figure 5 shows an example of the display information generated by the display information screen output processing (S414).

[0066] In Figure 5, the display information of a web page obtained via the internet 612 is displayed in the display information area 712 on the display screen 711 of the smartphone 1. The display information displayed in the display information area 712 in Figure 5 is typically the same display information obtained by the user 10 operating the smartphone 1.

[0067] Now, let's return to the processing procedure for displaying the degree of fakery in Figure 4 and continue the explanation.

[0068] Following the display information screen output processing (S414), the main processor 2 performs processing to indicate that the degree of fake information regarding the display information is being calculated (user-specific fake degree calculation display processing) (S415).

[0069] Figure 6 shows an example of the display resulting from the user-specific fakeness calculation process (S415).

[0070] In Figure 6, the fakeness level area 713 of the display screen 711 shows a text message (string "Fakeness Level Calculation in Progress") indicating that the fakeness level is being calculated.

[0071] User 10 operating smartphone 1 can learn that the information fakeness level of the displayed information is being calculated by the text displayed in this fakeness level area 713. In this embodiment, there is an information fakeness level which is specific to the content, and a user-specific fakeness level which is specific to each user when they encounter that information. However, as shown in Figure 6, in the screen display example, they may not be distinguished and may simply be described as "fakeness level".

[0072] Now, let's return to the processing procedure for displaying the degree of fakery in Figure 4 and continue the explanation.

[0073] Following the user-specific fakeness calculation and display process (S415), the main processor 2 performs the information fakeness calculation process (S430), which is a predefined process (subroutine).

[0074] The subroutine, Information Fake Degree Calculation Process (S430), calculates the degree of information fakeness regarding the displayed information, and the Information Fake Degree regarding the displayed information is obtained.

[0075] Here, we will explain the subroutine, the information fakeness calculation process (S430). Figure 7 is a flowchart showing the processing procedure of the subroutine, the information fakeness calculation process (S430). The processing procedure in Figure 7 will be explained with reference to the functional block diagram in Figure 3.

[0076] When the main processor 2 starts the information fakeness calculation process (S430) (S431), it reads the display information stored by the display information storage unit 14 and loads it into the RAM 43 (S432). Of course, the display information to be displayed can also be acquired again by the display information acquisition unit 13.

[0077] Next, the main processor 2, via the communication processing unit 12, requests fake-related information from the external server 615 that transmits fake-related information (S433).

[0078] Next, the main processor 2 determines whether or not it has received fake-related information from the external server 615 that transmits fake-related information (S434).

[0079] If the main processor 2 determines in the fake information reception determination process (S434) that it could not receive the fake information (S434 / No), it determines whether a predetermined time has elapsed (S435). Here, "predetermined time" refers to the time set aside for waiting for the reception of the fake information.

[0080] If the main processor 2 determines in the predetermined time elapsed determination process (S435) that the predetermined time has not elapsed (S435 / No), it returns to the fake-related information reception determination process (S434). This predetermined time elapsed determination process (S435) prevents the information fake degree calculation process (S430) from falling into a deadlock.

[0081] On the other hand, if the main processor 2 determines in the predetermined time elapsed determination process (S435) that a predetermined time has elapsed or more (S435 / Yes), it proceeds to the information fake degree calculation process (S436).

[0082] If the main processor 2 determines in the fake-related information reception determination process (S434) that fake-related information has been received (S434 / Yes), or if a predetermined time has elapsed in S435 (S435 / Yes), it proceeds to the information fake degree calculation process (S436).

[0083] In the information fakeness calculation process in S436, the main processor 2 calculates the information fakeness level using AI processing or conventional rule-based calculation processing (S436).

[0084] In the information fakeness calculation process (S436), the main processor 2 comprehensively judges the fakeness-related information from the external server 615 acquired by the fakeness-related information acquisition unit 15, as well as past display information and supplementary information related to that display information (such as past fakeness levels), and infers and calculates the information fakeness level.

[0085] Furthermore, the displayed information itself may include information about its degree of fakery. For example, Twitter (USA) labels the content of tweets, indicating whether a tweet contains misleading or questionable information. The information fakery calculation process (S436) infers that tweets with this label have a high degree of information fakery.

[0086] Furthermore, if the predetermined time has elapsed (S435) and the process proceeds to S436 (information fake degree calculation process), the main processor 2 uses past fake information to infer and calculate the information fake degree. If there is no past fake information, the main processor 2 may set a predetermined fake degree. There is no specific definition of the predetermined fake degree set here, but since no fake-related information has been obtained, a medium fake degree (fake degree 50%) can be used.

[0087] Next, the main processor 2 stores the information fakeness degree obtained by the information fakeness degree calculation process (S436), or the information fakeness degree set by the information fakeness degree setting process (S436), in the non-volatile memory 42 of the storage 4 using the information fakeness degree data storage unit 17 (S437).

[0088] This concludes the processing steps for calculating the degree of information fakery (S430) (S438).

[0089] Now, let's return to the processing procedure for displaying the degree of fakery in Figure 4 and continue the explanation.

[0090] Following the information fakeness calculation process (S430), the process moves to the predefined process (subroutine) of acquiring personality information (S450). The personality information acquisition process (S450) is the process of acquiring personal information such as personality related to the user 10 who is operating the smartphone 1. Here, the personality information acquisition process (S450), which is a subroutine, will be explained.

[0091] Figure 8 is a flowchart showing the processing procedure for acquiring personality information (S450). The processing procedure in Figure 8 will be explained with reference to the functional block diagram in Figure 3. The personality information in Figure 8 concerns the user's personality regarding susceptibility to deception.

[0092] When the main processor 2 starts the personality information acquisition process (S450) (S451), the personality information storage unit 19 determines whether or not the user's personality information has been stored (S452).

[0093] If, in the personality information storage determination process (S452), the main processor 2 determines that the user's personality information has already been stored (S452 / Yes), then the personality information acquisition process (S450) is terminated (S455) because the user's personality information has been obtained. Of course, it goes without saying that this personality information can be acquired again.

[0094] If the main processor 2 determines that the user's personality information is not stored (S452 / No), it proceeds to the next personality information lookup process (S453).

[0095] The personality information investigation process (S453) is a process in which the main processor 2 investigates the user's personality (susceptibility to deception) using the personality information acquisition unit 18. Here, the user's personality and susceptibility to deception are investigated through various questions and the answers to those questions.

[0096] Furthermore, there are various methods for investigating susceptibility to deception, and there are many websites dedicated to these personality assessments, so you can use those as well. For example, the Consumer Affairs Agency asks 15 questions such as "Are you easily flattered?" and asks respondents to answer on a 5-point scale from "Almost never applies" (1 point) to "Very much applies" (5 points). Based on the total score, they calculate the probability of signing a contract when presented with one, on a 5-point scale (approximately 25%, 30%, 40%, 50%, and 70%). In this embodiment, for the sake of simplification, the results of the susceptibility to deception survey are classified into three patterns (not easily deceived, average, easily deceived).

[0097] Next, the main processor 2 saves the user's personality information obtained in the personality information investigation process (S453) to the non-volatile memory 42 of the storage 4 using the personality information storage unit 19 (S454), and terminates this personality information acquisition process (S450) (S455).

[0098] Now, let's return to the processing procedure for displaying the degree of fakery in Figure 4 and continue the explanation.

[0099] Following the personality information acquisition process (S450), the user-specific fakeness coefficient calculation process (S416) is performed.

[0100] The user-specific fake-degree coefficient calculation process (S416) is a process that calculates the user-specific fake-degree coefficient (fake-degree personality coefficient) based on the user's personality information (three classifications for susceptibility to deception) stored by the personality information storage process (S454).

[0101] Here, we will explain the user-specific fakeness coefficient (fakeness personality coefficient) based on the user's personality information.

[0102] Figure 9 is a table (800) showing the individual user fakeness coefficient (fakeness personality coefficient) for susceptibility to deception (3 categories).

[0103] The item (column 801) consists of a personality classification (row 802) and a personality coefficient indicating the degree of fakery (row 803).

[0104] The personality classification (row 802) shows three categories of susceptibility to deception (difficult to deceive (column 831), average (column 832), easily deceived (column 833)). The fake-degree personality coefficient (row 802) shows the user's individual fake-degree coefficient (fake-degree personality coefficient) for the three categories of personality classification (row 802). For example, if a user's personality classification is average in terms of susceptibility to deception, it means that the user's individual fake-degree coefficient (fake-degree personality coefficient) is 1.0.

[0105] Now, let's return to the processing procedure for displaying the degree of fakery in Figure 4 and continue the explanation.

[0106] The main processor 2 performs the user-specific fakeness coefficient calculation process (S417) after the user-specific fakeness coefficient calculation process (S416).

[0107] The user-specific fake score is the final fake score displayed in the fake score area 713 of smartphone 1, and it reflects the user's personality information (susceptibility to being deceived).

[0108] The individual user's degree of fakery is calculated by the product of the information fakery score and the fakery score personality coefficient, as shown in equation (1) below. y n =x A *w 1n ...(1) however, y n User-specific degree of fakery for information A of user n: x A : Degree of falsehood of information A w 1n User n's degree of fake personality coefficient (individual user degree of fake coefficient)

[0109] For example, if the information fakeness level is 50% and the personality classification (susceptibility to deception) is normal, the individual user's fakeness level is the product of the information fakeness level (50%) and the fakeness level personality coefficient (1.0), so it will be 50% (50% × 1.0). Also, if the information fakeness level is 50% and the personality classification (susceptibility to deception) is easily deceived, the individual user's fakeness level is the product of the information fakeness level (50%) and the fakeness level personality coefficient (1.5), so it will be 75% (50% × 1.5).

[0110] In this embodiment, if the individual user fake score, which is the product of the information fake score and the fake score personality coefficient, exceeds 100%, it is set to the maximum value of 100%. It should be noted that a fake score of 100% does not mean that it is objectively completely fake (= has zero credibility), but rather that the fake score has been determined to be at its maximum value in order to warn individual users.

[0111] Next, the user-specific fakeness score calculated in the user-specific fakeness score calculation process (S417) is displayed in the fakeness score area 713 of smartphone 1 (S418), and the processing procedure for displaying the fakeness score in Figure 4 is completed (S419).

[0112] Figure 10 shows an example of the display resulting from the processing in S418 (user-specific fakeness display processing).

[0113] In Figure 10, the user-specific fake score 714 is displayed as a bar graph in the fake score area 713 of the display screen 711. The display example in Figure 10 is an example of the display when the user-specific fake score is approximately 50%.

[0114] User 10, who is operating smartphone 1, can find out their individual level of fakeness through the bar graph (approximately 50%) displayed in this fakeness level area 713.

[0115] Figure 10 shows the degree of fakeness (user-specific fakeness) for the entire display information in the display information area 712. However, it is also possible to highlight or blink only the text for which a degree of fakeness (user-specific fakeness) has been determined, allowing for identification.

[0116] In this embodiment, the user-specific fake score is displayed using a bar graph, but it is also possible to quantify the user-specific fake score and display it as text information (for example, the string "50%").

[0117] Furthermore, if the fake status is highly suspicious, a warning message can be displayed on the display screen 711, or a warning sound can be emitted, to draw attention to the issue.

[0118] Regarding the display of warning messages, since fake information tends to spread quickly, if the degree of fake information obtained is high, specifically if the degree of fake information exceeds a predetermined first warning threshold, a warning message may be displayed when the user attempts to forward or spread that information. In this case, the warning message might be, for example, "This information is likely fake. Are you sure you want to forward it?" Alternatively, even if the degree of fake information is below the first warning threshold, if the user's individual fake information coefficient exceeds the first warning threshold, a different warning message with a lower level of warning than the above warning message may be displayed, for example, "This information may be fake. Are you sure you want to forward it?"

[0119] In this embodiment, the degree of fakery (user-specific degree of fakery) is displayed as a bar graph, but in some cases, a rough three-stage degree of fakery (for example, "likely," "caution needed," and "doubtful") may suffice. In that case, since the identification of the degree of fakery (user-specific degree of fakery) is in three stages, various identification methods can be employed.

[0120] For example, this can be achieved by adding a border around the display information area or the target text, and using the border's characteristics (border thickness, border type (dotted, solid, dashed, etc.), border color, etc.). Alternatively, it can be achieved by adding a background around the display information area or the target text, and using the background's characteristics (background color, texture pattern type, etc.).

[0121] In this embodiment, information regarding the credibility of display information acquired via a network (such as display information from web pages or display information from social media) is obtained from an external server 615 via the network, and the degree of fakery (degree of information fakery) is calculated. However, it is also possible to infer and calculate the degree of fakery (degree of information fakery) by comprehensively judging past display information and related information (such as past degrees of fakery) using AI processing within the smartphone 1, without relying on the external server 615.

[0122] In this embodiment, when displaying the degree of fakery regarding the displayed information, the degree of fakery (degree of information fakery) is taken into account along with the personality information (susceptibility to being deceived) of the user handling the displayed information. Therefore, it is possible to display the optimal degree of fakery (user-specific degree of fakery) for the user viewing the displayed information.

[0123] In this embodiment, as shown in Figure 9, user personalities are categorized into three types ("hard to deceive," "average," and "easily deceived"), but the number of categories is not limited to three and may be increased or decreased.

[0124] Furthermore, while the individual user's fake score is calculated by multiplying it with the fake score personality coefficient shown in Figure 9, it is not necessarily required to use multiplication; weighting using statistical calculations or other methods may also be employed.

[0125] <Second Embodiment> The following describes a second embodiment of the present invention. The basic hardware configuration of the second embodiment is the same as that of the first embodiment described above. The following description will mainly focus on the differences between this embodiment (second embodiment) and the aforementioned embodiment (first embodiment), and common parts will be omitted as much as possible to avoid duplication.

[0126] In the previously described embodiment, the user information focused on the user's personality information regarding their susceptibility to deception, but in this embodiment, the user information focuses on the user's physical information.

[0127] Figure 11 is a schematic diagram illustrating the outline of this embodiment (second embodiment).

[0128] Figure 11 is almost identical to the schematic diagram in Figure 1, but with the addition of a body measurement device 721 connected to the smartphone 1 via short-range wireless communication. The body measurement device 721 is a device that measures the physical condition of the user 10 and is configured separately from the smartphone 1, thus it is considered an external body measurement device.

[0129] It is generally said that when a person is excited, their ability to make normal judgments is impaired. In this embodiment, the user's state of excitement is estimated using physical information obtained from the body measurement device 721, and the degree of that excitement is reflected in the "fake" rating and displayed.

[0130] (Functional block of this embodiment) Figure 12 is a functional block diagram showing an example of the functional block configuration of this embodiment.

[0131] The functional block diagram in Figure 12 contains some functions that overlap with the functional block diagram in the first embodiment (Figure 3), and therefore, explanations of those functions will be omitted. Here, only functions newly added in this embodiment or functions that require further explanation will be described.

[0132] In this embodiment, the communication processing unit 12 has the function of sending and receiving information with an external device that performs short-range wireless communication using a short-range wireless communication device 63 (see Figure 2). In this embodiment, it mainly receives body information from a body measurement device 721.

[0133] In recent years, body measurement devices 721 that perform short-range wireless communication such as Bluetooth® communication and NFC standard communication have become widespread, and various types of body information (blood pressure, body temperature, respiratory rate, heart rate, sweating amount, etc.) can be acquired. In this embodiment, such body measurement devices 721 that can perform short-range wireless communication are used. These body measurement devices 721 are called wearable devices and are often built into watch-type, wristband-type, or body-attached devices.

[0134] The body measurement device detection unit 22 has the function of searching for body measurement devices 721 that can communicate using the short-range wireless communication device 63. This body measurement device detection unit 22 can determine the types and number of body measurement devices 721 that can communicate.

[0135] The body measurement value acquisition unit 23 has the function of acquiring body measurement values ​​from the body measurement device 721 detected by the body measurement device detection unit 22.

[0136] The average value calculation unit 24 is a function that calculates the average value of physical measurements. Since the values ​​of the various physical information mentioned above differ from person to person, it is not possible to determine the level of excitement by comparing them to absolute values. Therefore, the average value calculation unit 24 compares the physical measurements obtained by the physical measurement acquisition unit 23 with the normal physical measurements and makes it possible to determine how much they have increased or decreased based on the comparison result. Calculating the average value is the calculation of physical information under normal conditions.

[0137] In this embodiment, the average value is calculated by averaging (moving average) the physical measurements taken over two weeks (14 days).

[0138] The timing of physical measurements can be arbitrarily selected, such as at a fixed time each day, at fixed intervals, or continuously.

[0139] If two weeks' worth of physical measurement data is unavailable, the missing data is supplemented, and the average value is calculated. In this embodiment, statistical standard values ​​(same sex, same age, and approximately the same build) are used as the supplementary physical measurement data.

[0140] The body information storage unit 25 has the function of storing the body measurement values ​​acquired by the body measurement value acquisition unit 23 and the average value up to the previous day calculated by the average value calculation unit 24 in the non-volatile memory 42 of the storage unit 4.

[0141] The excitement state estimation unit 26 determines how much the physical measurements acquired by the physical measurement acquisition unit 23 have increased or decreased compared to the average value of physical measurements up to the previous day calculated by the average value calculation unit 24, and estimates the excitement state based on the result. In this embodiment, it is classified into three stages ("normal", "slightly excited", and "excited"). The excitement state information storage unit 27 stores the excitement state information (three stages) estimated by the excitement state estimation unit 26 in the non-volatile memory 42 of the storage 4.

[0142] The user-specific fake degree coefficient calculation unit 20 is a function that calculates a coefficient (weighting) for the information fake degree obtained by the information fake degree calculation unit 16, using the user's excitement state information stored by the excitement state information storage unit 27. The user-specific fake degree coefficient calculation unit 20 determines the fake degree that should be displayed.

[0143] The coefficients (weighting) for the degree of fakery (degree of information fakery) will be discussed later.

[0144] The display data output unit 21 is a function that displays the display information stored in the non-volatile memory 42 of the storage 4 by the display information storage unit 14, as well as the user-specific fake degree, which is calculated by adding the user's physical information to the degree of fakeness related to the display information, on the display screen 711 of the smartphone 1.

[0145] (Processing procedure for displaying the degree of fakery in this embodiment) Figure 13 is a flowchart showing the processing procedure for displaying the degree of fakery in this embodiment.

[0146] The flowchart in Figure 13 contains some processes that overlap with the flowchart in the first embodiment (Figure 4), and explanations of those processes will be omitted. Here, only processes newly added in this embodiment or processes that require further explanation will be described.

[0147] The processing procedure in Figure 13 will be explained with reference to the functional block diagram in Figure 12.

[0148] In the flowchart for displaying the degree of fakery in this embodiment (Figure 13), several processes (physical information acquisition process (S460), excitement state estimation process (S420), excitement state preservation process (S421)) are added in place of the personality information acquisition process (S450) in the first embodiment described above.

[0149] Here, we will explain the subroutine, body information acquisition process (S460).

[0150] Figure 14 is a flowchart showing the processing procedure for acquiring physical information (S460).

[0151] The processing procedure in Figure 14 will be explained with reference to the functional block diagram in Figure 12.

[0152] When the body information acquisition process (S460) is started (S461), the body measurement device detection unit 22 detects a body measurement device 721 that can communicate (S462).

[0153] Next, it is determined whether or not the body measurement device 721 has been detected (S463).

[0154] In the process of determining the presence or absence of a body measurement device (S463), if it is determined that there is no body measurement device 721 that can be connected (S463 / No), then body measurement values ​​cannot be obtained, and this body information acquisition process (S460) is terminated (S469).

[0155] In the process of determining the presence or absence of a body measurement device (S463), if it is determined that there is a body measurement device 721 that can be connected (S463 / Yes), the body measurement value acquisition unit 23 acquires body measurement values ​​from the connected body measurement device 721 (S464).

[0156] Next, the average value calculation unit 24 calculates the average value of the physical measurements up to the previous day, which is stored by the physical information storage unit 25 (S465).

[0157] There are various methods for calculating the average value, such as the average of physical measurements over the most recent specified number of days, or the average of physical measurements over the most recent specified number of items. However, in this embodiment, the average value is calculated for the 14 days up to the previous day and used as the average of the physical measurements.

[0158] In this embodiment, if physical measurement data for the most recent 14 days is unavailable, the missing data is supplemented, and the average value of the physical measurement data is calculated.

[0159] Next, the degree to which the physical measurement values ​​obtained in the physical measurement value acquisition process (S464) have changed from the average value of the physical measurement values ​​calculated in the average value calculation process (S465) is calculated as the rate of change from the average value (S466).

[0160] Next, the body measurement values ​​obtained in the body measurement value acquisition process (S464) and the rate of change of the body measurement values ​​calculated in the rate of change calculation process (S466) are stored in the non-volatile memory 42 of the storage 4 by the body information storage unit 25 (S467).

[0161] Next, for all body measurement devices 721 detected in the body measurement device detection process (S462), it is determined whether or not all of their body measurement values ​​have been acquired (S468).

[0162] In the process of determining the completion of all body measurement devices (S468), if it is determined that all body measurement devices 721 have not completed their operation (S468 / No), the system connects to the unconnected body measurement devices 721 and proceeds to the process of acquiring body measurement values ​​(S464).

[0163] In the process of determining the completion of all body measurement devices (S468), if it is determined that all body measurement devices 721 have completed their operation (S468 / Yes), then there are no unconnected body measurement devices 721, and this body information acquisition process (S460) is terminated (S469).

[0164] Now, let's return to the processing procedure for displaying the degree of fakery in Figure 13 and continue the explanation.

[0165] Following the physical information acquisition process (S460), the excitement state estimation unit 26 performs the excitement state estimation process (S420).

[0166] The degree to which different physical measurement items affect the state of excitement varies, but in this embodiment, AI processing is used to weight the physical measurement items.

[0167] There are various estimation methods for estimating the state of excitement, such as classification based on the range of anthropometric measurements or classification based on the rate of change of anthropometric measurements relative to the average value. In this embodiment, the classification method based on the rate of change of anthropometric measurements relative to the average value is adopted.

[0168] Here, we will explain using the case where the anthropometric measurement is respiratory rate as an example. In this embodiment, if the anthropometric measurement is less than +10% of the average value, it is considered a normal state; if the anthropometric measurement is between +10% and +30% of the average value, it is considered a slightly excited state; and if the anthropometric measurement is +30% or more of the average value, it is considered an excited state. For example, if the average respiratory rate is 15 breaths / minute, the anthropometric measurement is classified as a normal state if it is less than 16.5 breaths / minute, a slightly excited state if it is between 16.5 breaths / minute and 19.5 breaths / minute, and an excited state if it is 19.5 breaths / minute or more. Of course, it goes without saying that the objective of this embodiment can also be achieved using classification methods other than this rate of change. For example, there are classification methods based on the difference between the average value and the anthropometric measurement, or classification methods that take into account the variability and rate of change of the elements used to calculate the average value.

[0169] Next, the excitement state information storage unit 27 stores the excitement state information, based on the results estimated in the excitement state estimation process (S420), in the non-volatile memory 42 of the storage 4 (S421).

[0170] Next, the process moves to calculating the user-specific fakeness coefficient (S416).

[0171] The user-specific fakeness coefficient calculation process (S416) is a process that calculates the user-specific fakeness coefficient (fakeness physical coefficient) based on the user's excitement state (3 classifications) saved in the excitement state saving process (S421).

[0172] Here, we will explain the user-specific fakeness coefficient (fakeness coefficient based on physical information).

[0173] Figure 15 is a table (810) showing the individual user fakeness coefficient (fakeness physical coefficient) for excited states (3 classifications).

[0174] The item (column 811) consists of an agitation state classification (row 812) and a fake degree physical coefficient (row 813).

[0175] The excitement state classification (row 812) indicates three classifications for the excitement state (normal state (column 841), slightly excited state (column 842), excited state (column 843)). Also, the fake degree physical coefficient (row 813) indicates the user-specific fake degree coefficient (fake degree physical coefficient) for the three classifications of the excitement state classification (row 812).

[0176] For example, when the user's excitement state is normal, it means that the user-specific fake degree coefficient (fake degree physical coefficient) is 1.0.

[0177] Here, returning to the processing procedure of the fake degree display in FIG. 13, the explanation will continue.

[0178] Next to the user-specific fake degree coefficient calculation process (S416), a user-specific fake degree calculation process (S417) is performed.

[0179] The user-specific fake degree is the final fake degree displayed in the fake degree area 713 of the smartphone 1 and is a fake degree that reflects the physical information (excitement state).

[0180] The user-specific fake degree is calculated by the product of the information fake degree and the fake degree physical coefficient, as shown in the following formula (2). y n =x A *w 2n ···(2) However,[[]] y n : The user-specific fake degree for the information A of user n x A : The information fake degree of information A w 2n : The fake degree physical coefficient (user-specific fake degree coefficient) of user n

[0181] For example, if the information fakeness level is 50% and the excitement level is normal, the individual user's fakeness level is the product of the information fakeness level (50%) and the fakeness level physical coefficient (1.0), so it will be 50% (50% × 1.0). Also, if the information fakeness level is 50% and the excitement level is slightly excited, the individual user's fakeness level is the product of the information fakeness level (50%) and the fakeness level physical coefficient (1.5), so it will be 75% (50% × 1.5).

[0182] In this embodiment as well, if the user-specific fake degree, which is the product of the information fake degree and the fake degree body coefficient, exceeds 100%, it is all set to the maximum value of 100%.

[0183] Next, the user-specific fakeness score calculated in the user-specific fakeness score calculation process (S417) is displayed in the fakeness score area 713 of smartphone 1 (S418), and the processing procedure for displaying the fakeness score in Figure 13 is completed (S419).

[0184] In this embodiment, as shown in Figure 15, the user's excitement level is categorized into three types ("normal," "slightly excited," and "excited"), but the number of categories is not limited to three and may be increased or decreased.

[0185] Furthermore, while the individual user's fake score is calculated by multiplying it with the fake score body coefficient shown in Figure 15, it is not necessarily required to be a multiplication operation; weighting using statistical calculations or other methods may also be used.

[0186] In this embodiment, we focus on respiratory rate as bodily information, but it is also possible to detect the state of excitement using other bodily information such as blood pressure, body temperature, heart rate, and sweating amount. By combining multiple pieces of bodily information, it is possible to detect the state of excitement more accurately.

[0187] In the explanation above, the user's body measurements are performed using an external body measurement device 721, but if body measurements can be performed using only the smartphone 1, those measurements can also be used.

[0188] For example, by shining the light-emitting diode (LED) light from a smartphone onto the capillaries in the user's fingertip and analyzing the image of the capillaries in the user's fingertip using the smartphone's camera function, it is possible to measure pulse rate, blood pressure, and other parameters.

[0189] In this embodiment, when displaying the degree of fakery related to the displayed information, the physical information (state of excitement) of the user handling the displayed information is taken into account in addition to the degree of fakery, so that the optimal degree of fakery (user-specific degree of fakery) can be displayed for the user viewing the displayed information.

[0190] <Third Embodiment> The following describes a third embodiment of the present invention. The basic hardware configuration of the third embodiment is the same as that of the previously described embodiments. The following description will mainly focus on the differences between this embodiment (third embodiment) and the previously described embodiments, and common parts will be omitted as much as possible to avoid duplication.

[0191] In the first embodiment described above, the user information focused on the user's personality information (susceptibility to deception). In the second embodiment described above, the user information focused on the user's physical information (state of excitement).

[0192] In this embodiment, information about the user, including both the user's personality information (susceptibility to being deceived) and the user's physical information (state of excitement), is reflected in the degree of deception and displayed.

[0193] (Functional block of this embodiment) Figure 16 is a functional block diagram showing an example of the functional block configuration of this embodiment.

[0194] The functional block diagram in Figure 16 is a superimposed functional block diagram of the functional block diagram in the first embodiment (Figure 3) and the functional block diagram in the second embodiment (Figure 12). Therefore, a description of its functions will be omitted. Here, only the functions that require further explanation in this embodiment will be described.

[0195] The user-specific fake degree coefficient calculation unit 20 is a function that calculates a coefficient (weighting) for the information fake degree obtained by the information fake degree calculation unit 16, using the user's personality information stored by the personality information storage unit 19 and the user's excitement state information stored by the excitement state information storage unit 27. The user-specific fake degree coefficient calculation unit 20 determines the fake degree that should be displayed.

[0196] The coefficients (weightings) used to determine the degree of information falsification will be discussed later.

[0197] (Processing procedure for displaying the degree of fakery in this embodiment) Figure 17 is a flowchart showing the processing procedure for displaying the degree of fakery in this embodiment.

[0198] The flowchart in Figure 17 is a superimposed flowchart of the flowchart in the first embodiment (Figure 4) and the flowchart in the second embodiment (Figure 13). Therefore, the explanation of the processing is omitted. Here, only the functions that require further explanation in this embodiment will be described.

[0199] The user-specific fake-degree coefficient calculation process (S416) is a process that calculates the user-specific fake-degree coefficient based on the user's personality information (three classifications for susceptibility to deception) stored by the personality information storage process (S454) and the user's excitement state (three classifications) stored by the excitement state storage process (S421).

[0200] Here, we will explain the user-specific fake-rate coefficient based on personality information (three categories of susceptibility to deception) and physical information (three categories of excitement levels).

[0201] Figure 18 is a table (820) showing the individual user fake-rate coefficients for three categories of susceptibility to deception and three categories of excitement levels.

[0202] The items consist of personality classifications (row 850) and excitement level classifications (column 860).

[0203] The personality classification (row 850) is a three-category classification of susceptibility to deception (difficult to deceive (column 851), average (column 852), easily deceived (column 853)), and the excitement state classification (column 860) is a three-category classification of excitement state (normal state (row 861), slightly excited state (row 862), excited state (row 863)).

[0204] The user-specific fake-degree coefficient, which takes into account both the user's personality information (susceptibility to being deceived) and the user's physical information (state of arousal), is calculated as the product of the fake-degree personality coefficient and the fake-degree arousal coefficient, as shown in equation (3) below. w 3n =w 1n *w 2n ...(3) w 3n User-specific fake degree coefficient w 1n User n's degree of fake personality coefficient w 2n User n's degree of fakeness physical coefficient

[0205] For example, if a person is moderately susceptible to deception (fakeness personality coefficient = 1.0) and has a normal level of excitement (fakeness physical coefficient = 1.0), it means that the individual user's fakeness coefficient is 1.0 (the product of the fakeness personality coefficient = 1.0 and the fakeness physical coefficient = 1.0).

[0206] The main processor 2 performs the user-specific fakeness coefficient calculation process (S417) after the user-specific fakeness coefficient calculation process (S416).

[0207] The user-specific fake score is the final fake score displayed in the fake score area 713 of smartphone 1, and it reflects both the user's personality information (susceptibility to being deceived) and the user's physical information (state of excitement).

[0208] The user-specific fake score is calculated by multiplying the information fake score by the user-specific fake score coefficient, as shown in equation (4) below. y n =x A *w 3n =x A *w 1n *w 2n ...(4) however, y n User-specific degree of fakery for information A of user n: x A : Degree of falsehood of information A w 1n User n's degree of fake personality coefficient w 2n User n's degree of fakeness physical coefficient w 3n User-specific fake degree coefficient

[0209] For example, if the information fakeness rate is 50% and the user-specific fakeness rate coefficient is 1.0, the user-specific fakeness rate is the product of the information fakeness rate (50%) and the user-specific fakeness rate coefficient (1.0), so it becomes 50% (50% × 1.0).

[0210] In this embodiment as well, if the user-specific fake degree, which is the product of the information fake degree and the user-specific fake degree coefficient, exceeds 100%, it is set to the maximum value of 100%.

[0211] Next, the user-specific fakeness score calculated in the user-specific fakeness score calculation process (S417) is displayed in the fakeness score area 713 of the smartphone 1 (S418), and the processing procedure for displaying the fakeness score in Figure 17 is completed (S419).

[0212] In this embodiment, as shown in Figure 18, the user's personality is categorized into three types ("hard to deceive," "average," and "easily deceived"), but the number of categories is not limited to three and may be increased or decreased. Similarly, the user's state of excitement is categorized into three types ("normal," "slightly excited," and "excited"), but the number of categories is not limited to three and may be increased or decreased.

[0213] Furthermore, while the user-specific fake score is calculated by multiplying it with the user-specific fake score coefficient shown in Figure 18, it is not necessarily required to use multiplication; weighting using statistical calculations or other methods may also be employed.

[0214] In this embodiment, when displaying the degree of fakery related to the displayed information, both the personality information (susceptibility to being deceived) and physical information (state of excitement) of the user handling the displayed information are taken into account, so that the optimal degree of fakery (user-specific degree of fakery) can be displayed for the user viewing the displayed information.

[0215] <Fourth Embodiment> The following describes a fourth embodiment of the present invention. The basic hardware configuration of the fourth embodiment is the same as that of the previously described embodiments. The following description will mainly focus on the differences between this embodiment (the fourth embodiment) and the previously described embodiments, and common parts will be omitted as much as possible to avoid duplication.

[0216] While the previously described embodiment dealt with display information obtained via the Internet, this embodiment deals with received broadcast content. In this embodiment, the degree of information fakery is calculated based on credibility characteristics derived from the audio information. As a specific example, at least one or any combination of the following may be used: the broadcasting station that broadcast the audio information, evaluation information assigned based on an evaluation of the credibility of the audio information, the time when the audio information was disseminated via public lines, the speed at which the audio information was disseminated via public lines, and the textual expressions included in the audio information.

[0217] Figure 19 is a schematic diagram illustrating the outline of this embodiment (the fourth embodiment).

[0218] Figure 19 is a schematic diagram showing a user 10 operating a portable information terminal (smartphone) 1, receiving broadcast signals 616 from television, radio, etc., and acquiring audio information from the speaker 82 of the smartphone 1. Video information is, of course, displayed on the display screen 711 of the smartphone 1.

[0219] User 10, operating smartphone 1, may be receiving and acquiring audio information from broadcasts that contains potentially unreliable audio. (This is labeled "Fake information?" in Figure 19.)

[0220] In this embodiment, the degree of fakery is calculated by converting audio information into text information (text conversion) and treating it as equivalent to the display information in the previously described embodiment.

[0221] (Functional block of this embodiment) Figure 20 is a functional block diagram showing an example of the functional block configuration of this embodiment.

[0222] The functional block diagram in Figure 20 contains some functions that overlap with the functional block diagram in the first embodiment (Figure 3), and explanations of those functions will be omitted. Here, only functions newly added in this embodiment or functions that require further explanation will be described.

[0223] In this embodiment, the communication processing unit 12 has the function of receiving broadcasts such as television and radio broadcasts using the broadcast receiver 64.

[0224] The audio information acquisition unit 28 has the function of acquiring audio information of the broadcast received by the communication processing unit 12.

[0225] The speech-to-text unit 29 has the function of converting the speech information acquired by the speech information acquisition unit 28 into text information.

[0226] The speech-to-text data storage unit 30 has the function of storing the character information converted by the speech-to-text unit 29 in the non-volatile memory 42 and various RAMs 43 of the storage 4.

[0227] The display data output unit 21 is a function that displays on the display screen 711 of the smartphone 1 the character information stored by the speech-to-text data storage unit 30, as well as the degree of fakery related to that character information, which takes into account the user's personality information.

[0228] (Processing procedure for displaying the degree of fakery in this embodiment) Figure 21 is a flowchart showing the processing procedure for displaying the degree of fakery in this embodiment.

[0229] The flowchart in Figure 21 contains some processes that overlap with the flowchart in the first embodiment (Figure 4), and explanations of those processes will be omitted. Here, only processes newly added in this embodiment or processes that require further explanation will be described.

[0230] The processing procedure in Figure 21 will be explained with reference to the functional block diagram in Figure 20.

[0231] In the flowchart for displaying the degree of fakery in this embodiment (Figure 4), four processes (audio information acquisition process (S422), speech-to-text conversion process (S423), speech-to-text data storage process (S424), and speech-to-text data display process (S425)) are added in place of some of the processes in the first embodiment described above.

[0232] When the fakeness display process begins (S411), the audio information acquisition unit 28 acquires audio information from the broadcast signal 616 (S422).

[0233] Next, the speech-to-text unit 29 converts the speech information acquired in the speech information acquisition process (S422) into text information (referred to as "speech-to-text data") (S423).

[0234] In this embodiment, the process of converting voice information into speech-to-text data is performed using AI-based voice analysis. The AI-based voice analysis process is the same as that used by Siri on iPhones (registered trademark) and Google's voice input technology, such as the technology that recognizes the hot word "OK, Google".

[0235] Next, the speech-to-text data converted by the speech-to-text processing (S423) is stored in the non-volatile memory 42 of the storage 4 by the speech-to-text data storage unit 30 (S424).

[0236] Next, the speech-to-text data saved in the speech-to-text data saving process (S424) is displayed on the display screen 711 (S425).

[0237] In the case of television broadcasts, the audio-text data is displayed on display screen 711 by overlaying it with the television broadcast screen or by creating a dual-screen display.

[0238] The speech-to-text data converted into text information can be handled in the same way as the display information in the first embodiment.

[0239] The following process is equivalent to the process for displaying the degree of fakery in the first embodiment, so its explanation will be omitted.

[0240] This embodiment allows the effects of the present invention to be obtained even when receiving broadcasts such as television and radio.

[0241] In this embodiment, the user's personality information (susceptibility to deception) is used as user information, but the user's physical information (state of arousal) as described in the second embodiment above can also be used. Furthermore, both the user's personality information (susceptibility to deception) and the user's physical information (state of arousal) as described in the third embodiment above can also be used.

[0242] As an application of this embodiment, similar processing can be performed on audio information (audio information files) attached to web pages 613 or SNS 614 acquired via the Internet 612 as a communication network. As a result, the effects of the present invention can also be obtained for audio information acquired via the Internet 612.

[0243] Furthermore, if character patterns can be extracted from still image information or video information and converted into text information, the effects of the present invention can naturally be obtained. For example, a television not connected to the Internet 612 may be configured to receive broadcast signals (broadcast radio waves), convert audio information into text information, and display user-specific fake degree and warning messages as captions on the television screen. In that case, user personality information may be accepted through setting operations on the television, or the viewer's age (for example, a distinction between child and adult) and gender may be estimated from past programs watched. For example, if a user spends a lot of time watching children's programs, there is a high possibility that the user (viewer) is a child, so the user-specific fake degree coefficient may be set to a value higher than the usual 1.0.

[0244] Although the above-described embodiment focused on smartphones, it goes without saying that the present invention can also be applied to other information display devices, such as tablets, personal computers including laptops, AR (augmented reality) glasses, and HMDs (head-mounted displays).

[0245] Furthermore, since the fakeness level display function of the present invention is an additional function added to the function of displaying the original information, this fakeness level display function should be selectable by the user to turn on (enable) or off (disable). Therefore, the system may be configured so that the fakeness level display function can be turned on (enable) or off (disabled) by any operation input device such as the main processor 2, storage 4, touch sensor 91, and operation key 92 shown in Figure 2. Furthermore, the user-specific fakeness level may not only be displayed on the same display screen 711 together with the display information, but may also be displayed on multiple display screens 711, each displaying the display information and the user-specific fakeness level, and the user may switch between the display screens 711 to display the information. Furthermore, even if the user-specific fakeness level is calculated, only the display information may be displayed on the display screen 711, and when an SNS or the like is launched on the smartphone 1 to transfer the display information, a warning display (which may be a pop-up display) corresponding to the user-specific fakeness level value may be shown to warn against the transfer.

[0246] Although examples of embodiments of the present invention have been described above using the first to fourth embodiments, the configurations that realize the technology of the present invention are not limited to the above embodiments, and various modifications are conceivable. For example, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. All of these fall within the scope of the present invention. Furthermore, the numbers and messages that appear in the text and figures are merely examples, and using different ones will not impair the effects of the present invention.

[0247] Furthermore, while the above-described embodiments have been explained under the premise that a single user uses the portable information terminal as an information display device, it is also possible for multiple users to use a single portable information terminal. In this case, user personality information, physical information, etc., are unique to each user and must be handled separately and independently.

[0248] Therefore, when multiple users use a single portable information terminal, in conjunction with user authentication, personality information, physical information, etc. for each user are stored in the non-volatile memory 42 of the storage 4, and by using the stored information, the individual fake degree for each user can be displayed. User authentication is a commonly used technology such as face authentication, fingerprint authentication, password authentication, etc.

[0249] Even when multiple users use a single portable information terminal, the effects of the present invention can be obtained by these.

[0250] The functions, etc. of the present invention described above may be realized in hardware by designing some or all of them, for example, with an integrated circuit. Also, they may be realized in software by a microprocessor unit, etc. interpreting and executing a program that realizes each function, etc. Hardware and software may be used in combination. The software may be stored in advance in the ROM 41, etc. of the smartphone 1 at the time of product shipment. After product shipment, it may be acquired from an external server 615, etc. on the Internet 612. Also, the software provided on a memory card, optical disk, etc. may be acquired.

[0251] Also, the control lines and information lines shown in the figure indicate those considered necessary for explanation, and do not necessarily show all the control lines and information lines on the product. In reality, it may be considered that almost all components are interconnected.

Explanation of Reference Numerals

[0252] 1: Smartphone 2: Main Processor 3: System Bus 4: Storage 10: User 11: Control Unit 12: Communication Processing Unit 13: Display Information Acquisition Unit 14: Display Information Storage Unit 15: Fake-Related Information Acquisition Unit 16: Information fake degree calculation unit 17: Information fake degree data storage unit 18: Personality information acquisition unit 19: Personality information storage unit 20: User-specific fake degree coefficient calculation unit 21: Display data output unit 22: Body measurement device detection unit 23: Body measurement value acquisition unit 24: Average value calculation unit 25: Body information storage unit 26: Excitement state estimation unit 27: Excitement state information storage unit 28: Voice information acquisition unit 29: Voice text conversion unit 30: Voice text conversion data storage unit 41: ROM 42: Non-volatile memory 43: RAM 51: GPS receiver 52: Geomagnetic sensor group 53: Acceleration sensor group 54: Gyro sensor group 61: LAN communicator 62: Telephone network communicator 63: Short-range wireless communicator 64: Broadcast receiver 71: Display 72: In-camera 73: Out-camera 81: Microphone 82: Speaker 91: Touch sensor 92: Operation key 611: Wireless LAN router 612: Internet 613: Web page 615: External server 616: Broadcast signal 621: Mobile phone base station 711: Display screen 712: Display information area 713: Degree of fakery range 714: User-specific degree of fakery 721: Body Measurement Equipment

Claims

1. A method for controlling an information processing device, The aforementioned information processing device The steps of connecting to a network and communicating, The steps include receiving information and information regarding the credibility of said information, A step of calculating an individual fake score based on an indicator that shows the user's tendency to judge credibility, A step of calculating the information correction fake degree by correcting the information fake degree based on the individual fake degree, The steps include controlling the system to output a warning based on the information correction fake degree calculated for the information when attempting to transmit the aforementioned information, A control method for an information processing device, characterized by including the following:

2. In the control method for the information processing device described in claim 1, In the step of calculating the individual fake score, the information processing device calculates the individual fake score based on the user's personality information, including how easily they are deceived. A control method for an information processing device characterized by the following features.

3. In the control method for the information processing device described in claim 1, In the step of calculating the individual fake degree, the information processing device calculates the individual fake degree based on the user's physical information. A control method for an information processing device characterized by the following features.

4. In the control method for the information processing device described in claim 3, The step of performing proximity communication with an external body measurement device is further included before the step of calculating the individual fake degree, The information processing device calculates the individual fake degree based on the user's physical information measured by the external physical measurement device. A control method for an information processing device characterized by the following features.

5. In the control method for the information processing device described in claim 4, The information processing device stores the user's physical information that was previously measured by the external physical measurement device. The information processing device calculates the individual fake degree based on the comparison result between the user's physical information previously measured by the external physical measurement device and the user's physical information currently measured by the external physical measurement device. A control method for an information processing device characterized by the following features.

6. In the control method for the information processing device described in claim 4, The information processing device calculates the individual fake score based on both the user's physical information measured by the external physical measurement device and the user's personality information, including their susceptibility to being deceived. A control method for an information processing device characterized by the following features.

7. In the control method for the information processing device described in claim 3, The information processing device estimates the user's state of arousal using at least one or any combination of the user's blood pressure, body temperature, respiratory rate, heart rate, and sweat volume as the user's physical information, and calculates the individual fake degree based on the estimated result. A control method for an information processing device characterized by the following features.

8. In the control method for the information processing device described in claim 1, After the step of calculating the individual fake degree, the information processing device displays the information and the individual fake degree. A control method for an information processing device characterized by the following features.

9. In the control method for the information processing device described in claim 1, In the step of calculating the degree of fakery in the information correction, at least one or any combination of the following are used as characteristics related to the credibility of the information: the type of site on which the information was published, the author of the information, the publisher of the information, evaluation information assigned based on an evaluation of the credibility of the information, the time when the information was disseminated via public lines, the speed at which the information was disseminated via public lines, and the textual expressions contained in the information. A control method for an information processing device characterized by the following features.

10. In the control method for the information processing device described in claim 8, In the step of controlling the output of the aforementioned warning, the information processing device transmits the information including the displayed information and the individual fake degree. A control method for an information processing device characterized by the following features.

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