Psychological education system and method for remote digital information

Abstract

The embodiment of the present application provides a kind of psychological education system and method of remote digital information, it is related to remote psychological education field.The system includes: information collection module, for obtaining the user information input by user, wherein, user information is the information that user inputs by replying to preset psychological education questionnaire;Semantic recognition module is used to obtain first semantic information by the semantic recognition of user information;Strategy determination module is used to determine psychological education strategy based on first semantic information, and obtains voice broadcast text information and voice broadcast sound information according to psychological education strategy;Combination module is used to combine voice broadcast text information and voice broadcast sound information, and determine psychological education voice file;Voice broadcast module is used to carry out voice broadcast according to psychological education voice file, to realize psychological education.By the present application, it solves the problem that the degree of customization of psychological education is low, and achieves the effect of improving the degree of individual customization.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the field of remote psychological education, and in particular, to a remote digital information psychological education system and method. BACKGROUND

[0002] With the advent of the digital age, mental health problems have gradually attracted widespread attention from all sectors of society. As a new education model, remote psychological education shows its importance because it can break through geographical restrictions and provide psychological support and education for people in different regions and with different needs.

[0003] In the prior art, there are still some problems to be solved in the remote psychological education system, such as the lack of a function of customizing personalized education strategies according to the specific psychological state of users, which leads to suboptimal education effect.

[0004] There is currently no good solution to the above problems. SUMMARY

[0005] Embodiments of the present application provide a remote digital information psychological education system and method to at least solve the problem of low personalized education capability in related technologies.

[0006] According to an embodiment of the present application, a remote digital information psychological education system is provided, comprising:

[0007] An information collection module is configured to obtain user information input by a user, wherein the user information is information input by the user in response to a pre-set psychological education questionnaire;

[0008] A semantic recognition module is configured to perform semantic recognition on the user information to obtain first semantic information;

[0009] A strategy determination module is configured to determine a psychological education strategy based on the first semantic information, and obtain voice broadcast text information and voice broadcast sound information according to the psychological education strategy;

[0010] A combination module is configured to combine the voice broadcast text information and the voice broadcast sound information to determine a psychological education voice file;

[0011] A voice broadcast module is configured to perform voice broadcast according to the psychological education voice file to achieve psychological education.

[0012] In an exemplary embodiment, the semantic recognition of the user information to obtain first semantic information comprises:

[0013] perform vocabulary recognition on the user information to obtain a number of vocabularies, vocabulary position information of a first vocabulary, and a vocabulary-based sentiment tendency score of the first vocabulary, wherein the first vocabulary is any vocabulary in the user information, and the vocabulary-based sentiment tendency score corresponds to the first vocabulary one-to-one;

[0014] determine a target sentiment tendency score of the first vocabulary in the user information according to the number of vocabularies, the vocabulary position, and the vocabulary-based sentiment tendency score by using a first formula, wherein the first semantic information comprises the target sentiment tendency score, and the first formula comprises:

[0015]

[0016] wherein C is the target sentiment tendency score, c' is a preset sentiment tendency adjustment factor, s is the vocabulary-based sentiment tendency score, p(i) is the position of the first vocabulary in the user information, p(m) is the position of a vocabulary in the middle position in the user information, and N is the total number of vocabularies in the user information, is an average of the total number of vocabularies in historical user information.

[0017] In an example embodiment, the determining the psychological education strategy based on the first semantic information comprises:

[0018] determining a sentiment tendency score of the user information based on the target sentiment tendency score of the first vocabulary;

[0019] determining the psychological education strategy as a first strategy if the sentiment tendency score is less than a first threshold value, and otherwise as a second strategy.

[0020] In an example embodiment, the system further comprises:

[0021] a vocabulary detection module configured to, after the semantic recognition on the user information to obtain the first semantic information, construct a vocabulary detection matrix based on the number of vocabularies and the vocabulary position;

[0022] a calculation module configured to perform correlation detection calculation on the vocabulary detection matrix to obtain a correlation value;

[0023] an abnormality judgment module configured to determine that the first semantic information is abnormal if the correlation value does not meet a preset threshold condition.

[0024] In an example embodiment, the system further comprises:

[0025] The video information collection module is configured to collect face image information and sound information of the user through remote video operation before determining the psychological education strategy based on the first semantic information.

[0026] The information analysis module is configured to analyze the face image information to obtain image information, and analyze the sound information to obtain voiceprint information, wherein the image information includes eye movement information and expression change information.

[0027] The second strategy determination module is configured to determine the psychological education strategy based on the image information, the voiceprint information and the first semantic information.

[0028] According to another embodiment of the present application, a psychological education method for remote digital information is provided, comprising:

[0029] The user information input by the user is collected, wherein the user information is input by the user in response to a preset psychological education questionnaire.

[0030] The user information is subjected to semantic recognition to obtain first semantic information.

[0031] A psychological education strategy is determined based on the first semantic information, and voice broadcast text information and voice broadcast sound information are obtained according to the psychological education strategy.

[0032] The voice broadcast text information and the voice broadcast sound information are combined to determine a psychological education voice file.

[0033] Voice broadcast is performed according to the psychological education voice file to achieve psychological education.

[0034] In an exemplary embodiment, the semantic recognition of the user information to obtain first semantic information comprises:

[0035] The user information is subjected to vocabulary recognition to obtain a number of vocabularies, vocabulary position information of a first vocabulary and a vocabulary-based emotional tendency score of the first vocabulary, wherein the first vocabulary is any vocabulary in the user information, and the vocabulary-based emotional tendency score corresponds to the first vocabulary.

[0036] The target emotional tendency score of the first vocabulary in the user information is determined by a first formula based on the number of vocabularies, the vocabulary position and the vocabulary-based emotional tendency score, wherein the first semantic information includes the target emotional tendency score, and the first formula includes:

[0037]

[0038] In the formula, C is the target emotional tendency score; c' is a preset emotional tendency adjustment factor, s is the lexical-based emotional tendency score, p(i) is the position of the first lexical in the user information, p(m) is the position of the lexical in the middle position in the user information, N is the total number of lexicals in the user information, and N is the average of the total number of lexicals in the historical user information.

[0039] In one example embodiment, the determining the psychological education strategy based on the first semantic information comprises:

[0040] determining an emotional tendency score of the user information based on the target emotional tendency score of the first lexical;

[0041] determining the psychological education strategy as a first strategy if the emotional tendency score is less than a first threshold value, and otherwise as a second strategy.

[0042] According to still another embodiment of the present application, there is also provided a computer readable storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.

[0043] According to still another embodiment of the present application, there is also provided an electronic device comprising a memory and a processor, the memory having a computer program stored therein, the processor being arranged to execute the computer program to perform the steps of any of the above method embodiments.

[0044] By the present application, since the semantic emotional tendency condition is determined by deeply analyzing the semantic information input by the user, and the education strategy is correspondingly determined, the problem of insufficient customization of psychological education can be solved, and the effect of improving the degree of customization is achieved. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 is a structural block diagram of a remote digital information psychological education system according to an embodiment of the present application;

[0046] Figure 2 is a flowchart of a remote digital information psychological education method according to an embodiment of the present application. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments.

[0048] The terms "first", "second", and the like, are used merely to describe the purpose of the referenced elements and do not imply or suggest relative importance or a limitation on the number of the referenced elements. Thus, features defined with "first", "second", and the like, can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "a plurality" is two or more, unless otherwise specified.

[0049] In addition, in the present application, the orientation terms such as "upper", "lower", "left", "right", and the like, can include, but are not limited to, the orientation defined by the relative placement of the components in the figures. It should be understood that these directional terms are relative concepts, which are used for relative description and clarification, and can change accordingly according to the change of the placement of the components in the figures.

[0050] In the present application, unless otherwise explicitly specified and limited, the term "connection" should be understood broadly, for example, "connection" can be fixed connection, or detachable connection, or integral; can be directly connected, or indirectly connected through intermediate medium. In addition, the term "coupling" can be an electrically connected manner for signal transmission.

[0051] As used herein, "about", "approximately", or "nearly" includes the stated value and the average value within an acceptable range of deviation from the specific value, wherein the acceptable range of deviation is determined by the person of ordinary skill in the art considering the measurement being discussed and the error related to the measurement of the specific quantity (i.e., the limitations of the measurement system).

[0052] In the present embodiment, a remote digital information psychological education system is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and will not be described again. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware, or a combination of software and hardware implementations are also possible and contemplated.

[0053] Figure 1 is a structural block diagram of a remote digital information psychological education system according to an embodiment of the present application, as shown in Figure 1 The system comprises:

[0054] An information collection module 11 is configured to obtain user information input by a user, wherein the user information is information input by the user in response to a pre-set psychological education questionnaire;

[0055] In the present embodiment, the user inputs their responses through a graphical user interface (GUI). These responses can include text input, selection of options, or filling out a rating scale.

[0056] The psychological education questionnaire includes, but is not limited to, standardized psychological assessment scales, open questions and multiple-choice questions; the questionnaire aims to collect basic information, mental health status, living habits and personal feelings of the user; the information input by the user is collected by the information collection module and then converted into a structured data format for subsequent semantic recognition and analysis.

[0057] The semantic recognition module 12 is configured to perform semantic recognition on the user information to obtain first semantic information.

[0058] In this embodiment, data preprocessing is required before semantic recognition, which includes text cleaning (removing irrelevant characters and stop words), word segmentation (segmenting continuous text into independent words) and part-of-speech tagging (identifying the grammatical properties of each word).

[0059] The first semantic information includes, but is not limited to, the number of words, word position information, the position distance between specific words, sentence structure, and the basic sentiment tendency score of each word. The word position information refers to the specific position of the word in the user's reply (generally, a specific position is marked as 1, and then the position is identified from 1). The basic sentiment tendency score is the sentiment tendency score assigned to each word according to a pre-set word dictionary.

[0060] The strategy determination module 13 is configured to determine a psychological education strategy based on the first semantic information, and to obtain voice broadcast text information and voice broadcast sound information according to the psychological education strategy.

[0061] In this embodiment, the determined psychological education strategy includes positive regulation strategy, negative regulation strategy, or emotion regulation strategy, behavior regulation strategy, etc. Since different users have different levels of acceptance of voice in different psychological states, after determining the psychological education strategy, the corresponding broadcast text and the corresponding sound (such as young male voice, young female voice, middle-aged male voice, middle-aged female voice, etc.) need to be determined and combined to improve the effect of psychological education.

[0062] The combination module 14 is configured to combine the voice broadcast text information and the voice broadcast sound information to determine a psychological education voice file.

[0063] The voice broadcast module 15 is configured to perform voice broadcast according to the psychological education voice file to achieve psychological education.

[0064] In this embodiment, the psychological education voice file is a file that can be recognized by a voice broadcast device. Since different voice broadcast devices have different file formats, the format needs to be adjusted after combination.

[0065] In an optional embodiment, the semantic recognition of the user information comprises:

[0066] vocabulary recognition of the user information to obtain a vocabulary quantity, a vocabulary position information of a first vocabulary, and a vocabulary basic sentiment tendency score of the first vocabulary, wherein the first vocabulary is any vocabulary in the user information, and the vocabulary basic sentiment tendency score corresponds to the first vocabulary one-to-one;

[0067] In the embodiment, the vocabulary basic sentiment tendency score of the first vocabulary is recorded in a vocabulary dictionary after statistical scoring annotation based on historical data. The statistical score can be obtained by scoring calculation of a neural network (usually a score from positive (positive score), negative (negative score) to neutral (zero score)), and the related score value needs to be obtained by repeatedly adjusting the sentiment distribution of various vocabularies through big data statistics.

[0068] According to the vocabulary quantity, the vocabulary position, and the vocabulary basic sentiment tendency score, a target sentiment tendency score of the first vocabulary in the user information is determined by a first formula, wherein the first semantic information comprises the target sentiment tendency score, and the first formula comprises:

[0069]

[0070] In the formula, C is the target sentiment tendency score, c' is a preset sentiment tendency adjustment factor, s is the vocabulary basic sentiment tendency score, p(i) is the position of the first vocabulary in the user information, p(m) is the position of a vocabulary located in the middle position in the user information, and N is the total number of vocabularies in the user information. is the average value of the total number of vocabularies in historical user information.

[0071] In an optional embodiment, the determination of the psychological education strategy based on the first semantic information comprises:

[0072] determination of a sentiment tendency score of the user information based on the target sentiment tendency score of the first vocabulary;

[0073] determination of the psychological education strategy as a first strategy if the sentiment tendency score is less than a first threshold value, and otherwise as a second strategy.

[0074] In the embodiment, the first strategy can be a positive adjustment strategy, a negative positive strategy, a sentiment adjustment strategy, or a behavior adjustment strategy, and the second strategy can be a relative strategy.

[0075] In an optional embodiment, the system further comprises:

[0076] a vocabulary detection module, configured to construct a vocabulary detection matrix based on the vocabulary quantity and the vocabulary position after the semantic recognition of the user information is performed to obtain the first semantic information;

[0077] a calculation module, configured to perform correlation detection calculation on the vocabulary detection matrix to obtain a correlation value;

[0078] an abnormality judgment module, configured to determine that the first semantic information is abnormal if the correlation value does not meet a preset threshold condition.

[0079] In this embodiment, since the questionnaire is pre-set, the vocabulary position, the vocabulary quantity and even the vocabulary emotional tendency of the corresponding reply content can be predicted. If the vocabulary quantity and the vocabulary position are irrelevant, the relevant reply may be an abnormal reply (for example, the user's mental state is unstable, or the reply is malicious, etc.).

[0080] For example, the correlation value ranges from 0.4 to 0.7. If the value exceeds the range, it is determined that the semantic information is abnormal.

[0081] In addition to the vocabulary quantity and the vocabulary position, the vocabulary detection matrix can also be constructed according to the frequency of the vocabulary in the document (word frequency), the rarity of the vocabulary in the entire corpus (inverse document frequency), the semantic similarity or correlation of the vocabulary, the emotional tendency of the vocabulary, etc.

[0082] In an optional embodiment, the system further comprises:

[0083] a video information acquisition module, configured to acquire facial image information and sound information of the user by remote video operation before the psychological education strategy is determined based on the first semantic information;

[0084] an information analysis module, configured to perform image recognition analysis on the facial image information of the user to obtain image information, and perform voiceprint analysis processing on the sound information to obtain voiceprint information, wherein the image information includes eye movement information and expression change information;

[0085] a second strategy judgment module, configured to determine the psychological education strategy based on the image information, the voiceprint information and the first semantic information.

[0086] In this embodiment, facial expressions and sounds are important external manifestations of emotional states. Therefore, by analyzing these non-verbal signals, the user's emotions and psychological state can be more comprehensively understood, and thus the psychological comprehensive judgment can be performed in combination with the facial image information and the sound information when the strategy is determined.

[0087] The user facial information includes eye movement trajectory, facial muscle change, and the like; and the sound information includes voiceprint, tone, frequency, intensity, and the like.

[0088] It should be noted that the above modules can be implemented by software or hardware, and for the latter, the following implementation manners can be used, but are not limited thereto: the above modules are located in the same processor; or the above modules are located in different processors in any combination.

[0089] The embodiment also provides a psychological education method of remote digital information, Figure 1 as shown in the flowchart of the psychological education method of remote digital information according to the embodiment of the present application, the flowchart includes the following steps: Figure 1 as shown in the flowchart of the psychological education method of remote digital information according to the embodiment of the present application, the flowchart includes the following steps:

[0090] Step S101: obtaining user information input by a user, wherein the user information is information input by the user in response to a preset psychological education questionnaire;

[0091] Step S102: performing semantic recognition on the user information to obtain first semantic information;

[0092] Step S103: determining a psychological education strategy based on the first semantic information, and obtaining voice broadcast text information and voice broadcast sound information according to the psychological education strategy;

[0093] Step S104: combining the voice broadcast text information and the voice broadcast sound information to determine a psychological education voice file;

[0094] Step S105: performing voice broadcast according to the psychological education voice file to implement psychological education.

[0095] In an optional embodiment, the performing semantic recognition on the user information to obtain first semantic information includes:

[0096] performing vocabulary recognition on the user information to obtain a number of vocabularies, vocabulary position information of a first vocabulary, and a vocabulary basic emotional tendency score of the first vocabulary, wherein the first vocabulary is any vocabulary in the user information, and the vocabulary basic emotional tendency score corresponds to the first vocabulary one by one;

[0097] determining a target emotional tendency score of the first vocabulary in the user information by a first formula according to the number of vocabularies, the vocabulary position, and the vocabulary basic emotional tendency score, wherein the first semantic information includes the target emotional tendency score, and the first formula includes:

[0098]

[0099] In the formula, C is the target sentiment tendency score; c' is a preset sentiment tendency adjustment factor, s is the word-based sentiment tendency score, p(i) is the position of the first word in the user information, p(m) is the position of the word located in the middle position in the user information, and N is the total number of words in the user information. is the average of the total number of words in the historical user information.

[0100] In an optional embodiment, the determining the psychological education strategy based on the first semantic information comprises:

[0101] determining a sentiment tendency score of the user information based on the target sentiment tendency score of the first word;

[0102] determining the psychological education strategy as a first strategy if the sentiment tendency score is less than a first threshold value, or as a second strategy otherwise.

[0103] From the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software and a general hardware platform required, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as a ROM / RAM, a magnetic disk, or an optical disk) and includes a plurality of instructions for causing a terminal device (which can be a mobile phone, a computer, a server, or a network device) to execute the method described in each embodiment of the present application.

[0104] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program, and the computer program is configured to execute the steps in any of the above method embodiments when running.

[0105] In an exemplary embodiment, the above computer readable storage medium can include, but is not limited to, a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store computer programs.

[0106] The embodiments of the present application also provide an electronic device, which includes a memory and a processor, the memory stores a computer program, and the processor is configured to execute the computer program to perform the steps in any of the above method embodiments.

[0107] In one example embodiment, the electronic device described above can further include a transmission device connected to the processor and an input / output device connected to the processor.

[0108] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above functional modules is taken as an example for illustration, and in actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above.

[0109] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of modules or units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another device, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0110] The units described as separate components can or can not be physically separated, and the components shown as units can be one physical unit or multiple physical units, that is, they can be located in one place or distributed to multiple different places. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0111] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0112] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application essentially or say the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The software product is stored in a storage medium, and includes a plurality of instructions for causing an apparatus (which can be a single-chip microcomputer, a chip, etc.) or a processor to execute all or part of the steps of the method of each embodiment of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0113] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any change or replacement within the technical scope disclosed in the present application should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A remote digital information psychological education system, characterized in that: include: An information collection module is used to obtain user information input by the user, wherein the user information is the information input by the user in replying to a preset psychological education questionnaire; a semantic recognition module, configured to perform semantic recognition on the user information to obtain first semantic information; a strategy determination module, configured to determine a psychological education strategy based on the first semantic information, and obtain voice broadcast text information and voice broadcast sound information according to the psychological education strategy; A combining module, configured to combine the voice broadcast text information and the voice broadcast sound information to determine a psychological education voice file; A voice broadcast module, configured to perform voice broadcasting according to the psychological education voice file to achieve psychological education; The performing semantic recognition on the user information to obtain first semantic information includes: Performing vocabulary recognition on the user information to obtain vocabulary quantity, vocabulary position information of a first vocabulary, and a vocabulary-based sentiment tendency score of the first vocabulary, wherein the first vocabulary is any vocabulary in the user information, and the vocabulary-based sentiment tendency score corresponds one-to-one to the first vocabulary; Determine a target sentiment tendency score of the first word in the user information according to the number of words, the position of the words, and the basic sentiment tendency score of the words by a first formula, wherein the first semantic information includes the target sentiment tendency score, and the first formula includes: Where, Score the target sentiment tendency; is the preset emotional tendency adjustment factor, Score the vocabulary-based sentiment tendency, is the position of the first word in the user information, is the position of the word in the middle of the user information, N is the total number of words in the user information, is the average value of the total number of words in historical user information; Determining the psychological education strategy based on the first semantic information includes: Determining a sentiment tendency score of the user information based on the target sentiment tendency score of the first vocabulary; When the emotional tendency score is less than a first threshold, the psychological education strategy is determined to be the first strategy; otherwise, the psychological education strategy is determined to be the second strategy.

2. The system according to claim 1, wherein: The system further comprises: a vocabulary detection module, configured to construct a vocabulary detection matrix based on the vocabulary quantity and vocabulary position after semantic recognition is performed on the user information to obtain first semantic information; A calculation module, configured to perform a correlation detection calculation on the vocabulary detection matrix to obtain a correlation value; The abnormality judgment module is used to determine that there is an abnormality in the first semantic information when the correlation value does not meet the preset threshold condition.

3. The system according to claim 1, wherein: The system further comprises: a video information acquisition module, configured to obtain user facial image information and voice information before determining the psychological education strategy based on the first semantic information, wherein the user facial information and voice information are obtained by performing a remote video operation on the user; an information analysis module, configured to perform image recognition analysis on the user's facial information to obtain image information, and perform voiceprint analysis on the voice information to obtain voiceprint information, wherein the image information includes eye movement information and expression change information; The second strategy judgment module is used to determine the psychological education strategy based on the image information, voiceprint information and the first semantic information.

4. A remote digital information psychological education method, characterized in that: Applied to the system according to claim 1, the method comprises: Acquiring user information input by a user, wherein the user information is information input by the user in response to a preset psychological education questionnaire; Performing semantic recognition on the user information to obtain first semantic information; Determining a psychological education strategy based on the first semantic information, and obtaining voice broadcast text information and voice broadcast sound information according to the psychological education strategy; Combining the voice broadcast text information and the voice broadcast sound information to determine a psychological education voice file; Voice broadcasting is performed according to the psychological education voice file to achieve psychological education.

5. The method according to claim 4, characterized in that The performing semantic recognition on the user information to obtain first semantic information includes: Performing vocabulary recognition on the user information to obtain vocabulary quantity, vocabulary position information of a first vocabulary, and a vocabulary-based sentiment tendency score of the first vocabulary, wherein the first vocabulary is any vocabulary in the user information, and the vocabulary-based sentiment tendency score corresponds one-to-one to the first vocabulary; Determine a target sentiment tendency score of the first word in the user information according to the number of words, the position of the words, and the basic sentiment tendency score of the words by a first formula, wherein the first semantic information includes the target sentiment tendency score, and the first formula includes: Where, Score the target sentiment tendency; is the preset emotional tendency adjustment factor, Score the vocabulary-based sentiment tendency, is the position of the first word in the user information, is the position of the word in the middle of the user information, N is the total number of words in the user information, is the average value of the total number of words in historical user information.

6. The method according to claim 5, characterized in that Determining the psychological education strategy based on the first semantic information includes: Determining a sentiment tendency score of the user information based on the target sentiment tendency score of the first vocabulary; When the emotional tendency score is less than a first threshold, the psychological education strategy is determined to be the first strategy; otherwise, the psychological education strategy is determined to be the second strategy.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein the computer program is configured to execute the method according to any one of claims 4 to 6 when executed.

8. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to perform the method according to any one of claims 4 to 6.

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