Multi-modal public opinion analysis method and system, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a multi-modal public opinion analysis method and system, electronic equipment and a storage medium. The method comprises the following steps: acquiring original multi-modal data associated with a target service; performing data processing on the original multi-modal data based on a data processing mode corresponding to each data type, and determining multi-modal public opinion data corresponding to the target service; performing multi-dimensional public opinion analysis on the multi-modal public opinion data based on a preset public opinion analysis model, determining a public opinion analysis result corresponding to the target business, and associating the original multi-modal data with the public opinion analysis result to obtain a public opinion event corresponding to the target business; and performing decision analysis on the public opinion event based on a preset auxiliary decision mode, determining a disposal decision corresponding to the public opinion event, and pushing the disposal decision to a service system to which the target service belongs. Through the technical scheme of the embodiment of the invention, the richness and diversity of the basic data to be subjected to public opinion analysis and the accuracy and comprehensiveness of public opinion analysis can be improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of computer technology, and in particular to a multimodal public opinion analysis method, system, electronic device and storage medium. Background Technology

[0002] With the deepening development of the digital age, social media has become a core channel for the public to express opinions and emotions. For banks, the importance of public opinion monitoring is increasingly prominent. It is not only a window to understand customer needs and improve service quality, but also a key means to prevent reputational risks, maintain brand value, and grasp market competition. Efficient and accurate public opinion monitoring capabilities have become a core component of banks' digital operations and risk management systems.

[0003] Currently, banks commonly rely on keyword matching and basic sentiment analysis of text content for public opinion monitoring. However, these methods typically only cover text information from news websites and some social media platforms, neglecting the wealth of sentiment information contained in rich media such as short videos and images. Furthermore, existing systems have limited analytical dimensions, making it difficult to achieve automated and refined classification of public opinion, and lacking insights into the correlations between multi-source information. At the application level, the systems suffer from poor interactivity, failing to support the personalized monitoring needs of business personnel, and generally only reaching the stage of "identifying problems," failing to provide intelligent support for subsequent decision-making and handling, resulting in low efficiency throughout the entire public opinion management process. Summary of the Invention

[0004] This invention provides a multimodal public opinion analysis method, system, electronic device, and storage medium to perform multi-dimensional public opinion analysis on raw multimodal data and provide targeted public opinion handling decisions, thereby improving the richness and diversity of the basic data to be analyzed, as well as the accuracy and comprehensiveness of the public opinion analysis.

[0005] In a first aspect, embodiments of the present invention provide a multimodal public opinion analysis method, including:

[0006] Obtain raw multimodal data related to the target business;

[0007] The original multimodal data is processed according to the data processing method corresponding to each data type to determine the multimodal public opinion data corresponding to the target business;

[0008] Based on a preset public opinion analysis model, multi-dimensional public opinion analysis is performed on the multimodal public opinion data to determine the public opinion analysis results corresponding to the target business, and the original multimodal data is associated with the public opinion analysis results to obtain the public opinion events corresponding to the target business.

[0009] The public opinion event is analyzed based on a preset auxiliary decision-making method to determine the corresponding handling decision and push the handling decision to the business system to which the target business belongs.

[0010] Optionally, the method further includes: denoising, segmenting, and removing stop words from multimodal data of text type to determine text-based public opinion data corresponding to the target service; extracting text from images and recognizing visual elements from multimodal data of image type to determine image-based public opinion data corresponding to the target service; and performing speech recognition, extracting text from keyframes, and recognizing visual elements from multimodal data of video type to determine video-based public opinion data corresponding to the target service.

[0011] Optionally, the method further includes: storing the multimodal public opinion data obtained after data processing into a multimodal fusion data pool so that multimodal public opinion data corresponding to the target business can be obtained from the multimodal fusion data pool during public opinion analysis; or fusing the multimodal public opinion data obtained after data processing to obtain fused multimodal public opinion data, and storing the fused multimodal public opinion data into a multimodal fusion data pool so that multimodal public opinion data corresponding to the target business can be obtained from the multimodal fusion data pool during public opinion analysis.

[0012] Optionally, the method further includes: determining the sentiment polarity determination result corresponding to the target business based on a preset sentiment polarity determination sub-model and the multimodal public opinion data; determining the public opinion type identification result corresponding to the target business based on a preset public opinion type identification sub-model and the multimodal public opinion data; determining the business entity identification result corresponding to the target business based on a preset business entity identification sub-model and the multimodal public opinion data; and determining the topic identification result corresponding to the target business based on a preset topic identification sub-model and the multimodal public opinion data.

[0013] Optionally, the method further includes: determining the handling priority and decision direction of the public opinion event based on the sentiment polarity determination result and public opinion type identification result corresponding to the public opinion event; determining the in-depth analysis report corresponding to the public opinion event based on the handling priority, the decision direction and the preset large language model; and performing decision execution transformation based on the in-depth analysis report to determine the handling decision corresponding to the public opinion event.

[0014] Secondly, embodiments of the present invention also provide a multimodal public opinion analysis system, the system comprising:

[0015] The data acquisition module is used to acquire raw multimodal data related to the target business.

[0016] The data processing module is used to process the original multimodal data based on the data processing method corresponding to each data type, and determine the multimodal public opinion data corresponding to the target business.

[0017] The public opinion analysis module is used to perform multi-dimensional public opinion analysis on the multimodal public opinion data based on a preset public opinion analysis model, determine the public opinion analysis results corresponding to the target business, and associate the original multimodal data with the public opinion analysis results to obtain the public opinion events corresponding to the target business.

[0018] The auxiliary decision-making module is used to perform decision analysis on the public opinion event based on a preset auxiliary decision-making method, determine the corresponding handling decision for the public opinion event, and push the handling decision to the business system to which the target business belongs.

[0019] Optionally, the system further includes a user interaction module; wherein the user interaction module is used to display the overall public opinion situation of the public opinion event to the user, provide real-time alerts for high-risk public opinion events, and support user conditional queries and full-process tracking of public opinion events.

[0020] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising:

[0021] One or more processors;

[0022] Memory, used to store one or more programs;

[0023] When the one or more programs are executed by the one or more processors, the one or more processors implement the multimodal public opinion analysis method provided in any embodiment of the present invention.

[0024] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the multimodal public opinion analysis method as provided in any embodiment of the present invention.

[0025] Fifthly, embodiments of the present invention provide a computer program product, including a computer program that, when executed by a processor, implements the multimodal public opinion analysis method provided in any embodiment of the present invention.

[0026] The technical solution of this invention acquires raw multimodal data associated with a target business to perform multi-dimensional public opinion analysis on the raw multimodal data, thereby improving the richness and diversity of the basic data to be analyzed. The raw multimodal data is processed according to the data processing method corresponding to each data type to determine the multimodal public opinion data corresponding to the target business. Multi-dimensional public opinion analysis is performed on the multimodal public opinion data based on a preset public opinion analysis model to determine the public opinion analysis results corresponding to the target business, thus obtaining multi-dimensional analysis results to provide accurate public opinion analysis results for subsequent decision analysis, thereby improving the accuracy of decision-making. The raw multimodal data is correlated with the public opinion analysis results to obtain the public opinion event corresponding to the target business. Decision analysis is performed on the public opinion event based on a preset auxiliary decision-making method to determine the corresponding handling decision, and the handling decision is pushed to the business system to which the target business belongs.

[0027] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a flowchart of a multimodal public opinion analysis method provided in Embodiment 1 of the present invention;

[0030] Figure 2 This is a flowchart of a multimodal public opinion analysis method provided in Embodiment 2 of the present invention;

[0031] Figure 3 This is a schematic diagram of the structure of a multimodal public opinion analysis system provided in Embodiment 3 of the present invention;

[0032] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the multimodal public opinion analysis method of this invention. Detailed Implementation

[0033] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0035] Example 1

[0036] Figure 1 This document provides a flowchart of a multimodal public opinion analysis method according to Embodiment 1 of the present invention. This embodiment is applicable to situations involving public opinion analysis of user-published public opinion data. The method can be executed by a multimodal public opinion analysis system, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0037] S110. Obtain the raw multimodal data associated with the target business.

[0038] In this embodiment of the disclosure, the target business can refer to banking services for which public opinion monitoring is conducted. The target business can be a business that bank staff are concerned about. The target business can be understood as a service provided by the bank to users. The target business can take many forms. For example, the target business can include, but is not limited to, products, activities, and services provided by the bank to users. The target business can be an update announcement for the query function in an application (APP). Users can evaluate or provide feedback on their experience using the updated query function through various channels. The target business can also be banking services such as welfare activities related to solar terms or festivals.

[0039] In this embodiment, raw multimodal data can refer to unprocessed user-published public opinion data in multiple modalities, such as text, images, and videos. This public opinion data can be user evaluations of the target business. Public opinion data can be understood as public opinion regarding the target business. Public opinion can refer to the collection of attitudes, emotions, opinions, and evaluations expressed by the general public (including customers, potential customers, investors, employees, media, regulatory agencies, etc.) through various public or semi-public digital channels such as social media, news websites, forums, and video platforms regarding the bank and its products, services, behaviors, and executives. The technical solution of this embodiment can also perform multimodal public opinion analysis on all information related to the bank, including its products, services, behaviors, and executives.

[0040] Specifically, raw multimodal data related to the target business (such as involving the whole or part of the target business) is collected in real time from a designated social media platform through a distributed crawler cluster.

[0041] For example, in this embodiment, the multimodal public opinion analysis system includes a data acquisition module. The data acquisition module is primarily responsible for acquiring raw multimodal data related to the target business from external data sources in real time. The acquired raw multimodal data mainly includes, but is not limited to, text data (such as trending topics, article content, and user comments), image data (such as images and emojis), and video data (such as short video content) from social media platforms. This module uses distributed crawler technology to automate data collection and interfaces with the bank's internal knowledge base (such as product catalogs and procedures) through a data interface. This allows subsequent functional modules to obtain the required data to be analyzed (such as raw multimodal data) and auxiliary analysis data (such as the internal knowledge base) through the interface when conducting public opinion analysis.

[0042] It should be noted that by introducing multimodal data collection and analysis capabilities, the system can effectively identify public opinion information that is difficult to detect by pure text monitoring solutions (such as posters, images, and short videos containing negative information), expanding the coverage and dimensions of public opinion monitoring. This significantly improves the breadth and diversity of data sources, providing banks with a more comprehensive perspective on public opinion.

[0043] S120. Based on the data processing method corresponding to each data type, process the original multimodal data to determine the multimodal public opinion data corresponding to the target business.

[0044] In this embodiment of the disclosure, the data type can refer to various data types corresponding to the pre-set raw multimodal data collected. For example, the data type can include, but is not limited to, text, images, and videos. The data processing method can refer to the pre-set data processing method for each data type. The data processing method can be used to adjust the corresponding type of data into data that can be directly used for subsequent public opinion analysis. The data processing method can also be used to filter out information in the raw multimodal data that is irrelevant to public opinion analysis. Multimodal public opinion data can refer to multimodal data related to public opinion (such as user opinions) that can be directly used for public opinion analysis.

[0045] Specifically, the collected raw multimodal data is cleaned and analyzed. Text data undergoes word segmentation and stop word removal; image data uses OCR and visual recognition technologies to extract text and visual features; and video data is converted into analyzable text and image data through frame extraction and speech recognition technologies. The data is then processed using the methods described above for text and image data. This process yields multimodal public opinion data corresponding to the target business, enabling the collection of text, image, and video data from various publicly available heterogeneous platforms and the unified transformation of this data into analyzable information using OCR, image recognition, and other technologies.

[0046] As an optional implementation of this disclosure, data processing is performed on the original multimodal data based on the data processing method corresponding to each data type to determine the multimodal public opinion data corresponding to the target business. Specifically, this may include: denoising, word segmentation, and stop word removal on text-type multimodal data to determine text-type public opinion data corresponding to the target business; extracting text from images and recognizing visual elements on image-type multimodal data to determine image-type public opinion data corresponding to the target business; and performing speech recognition and extracting text from keyframes and recognizing visual elements on video-type multimodal data to determine video-type public opinion data corresponding to the target business.

[0047] In this embodiment of the disclosure, text-based public opinion data can refer to text-related public opinion data obtained after data processing of raw multimodal data of the text type. Image-based public opinion data can refer to image-related public opinion data obtained after data processing of raw multimodal data of the image type. Video-based public opinion data can refer to video-related public opinion data obtained after data processing of raw multimodal data of the video type. Multimodal public opinion data may include, but is not limited to, text-based public opinion data, image-based public opinion data, and video-based public opinion data.

[0048] For example, in this embodiment, the multimodal public opinion analysis system includes a data processing module. The data processing module is primarily responsible for cleaning and parsing the acquired raw multimodal data. This module includes three core sub-modules. The text processing sub-module is used to perform normalization processing on text-type multimodal data, such as denoising, word segmentation, and stop word removal, to obtain text-based public opinion data corresponding to the target business. The image processing sub-module is used to extract text information from image-type multimodal data using OCR technology and to identify visual elements such as bank logos and specific scenes in the image-type multimodal data using computer vision technology. The video processing sub-module is used to perform frame extraction processing on video-type multimodal data, thereby selecting keyframes with public opinion information that are not repeated from each video frame, and performing image analysis on the keyframes or transmitting the keyframes to the image processing sub-module for image processing. The video processing sub-module is also used to convert the audio content in the video-type multimodal data into text using speech recognition technology, and to perform text analysis on the converted text or transmit the converted text to the text processing sub-module for text processing.

[0049] As an optional implementation of this disclosure, the method further includes: storing the multimodal public opinion data obtained after data processing into a multimodal fusion data pool so that multimodal public opinion data corresponding to the target business can be obtained from the multimodal fusion data pool during public opinion analysis; or fusing the multimodal public opinion data obtained after data processing to obtain fused multimodal public opinion data, and storing the fused multimodal public opinion data into a multimodal fusion data pool so that multimodal public opinion data corresponding to the target business can be obtained from the multimodal fusion data pool during public opinion analysis.

[0050] In this embodiment of the disclosure, the multimodal fusion data pool can refer to a database that stores multimodal public opinion data obtained after data processing. The multimodal fusion data pool can be used to store multimodal public opinion data independently for each user in each target business.

[0051] Specifically, the multimodal public opinion data obtained after data processing is stored in a multimodal fusion data pool, and a correlation is established between different modal data from the same information source (such as the same user).

[0052] For example, the data processing module in the multimodal public opinion analysis system is also used to perform fusion processing on the multimodal public opinion data obtained after data processing, to obtain fused multimodal public opinion data, and store it in the multimodal fusion data pool so as to provide structured feature data (i.e. multimodal public opinion data) for subsequent public opinion analysis.

[0053] It should be noted that the multimodal fusion data pool can query multimodal public opinion data for each user across all banking services, thereby determining the credibility of user public opinion data or whether a user's comments are malicious. This allows target services to make adjustments based on user public opinion data, filtering out public opinion data corresponding to users with credibility below a preset credibility threshold, and further improving the accuracy and effectiveness of adjusting target services based on user public opinion data.

[0054] S130. Based on the preset public opinion analysis model, perform multi-dimensional public opinion analysis on multimodal public opinion data, determine the public opinion analysis results corresponding to the target business, and associate the original multimodal data with the public opinion analysis results to obtain the public opinion events corresponding to the target business.

[0055] In this embodiment of the disclosure, the preset public opinion analysis model can refer to a pre-trained classification model. For example, the preset public opinion analysis model can be a pre-fine-tuned large language model that can be used for multi-dimensional public opinion analysis, or a pre-trained deep learning model that can be used for multi-dimensional public opinion analysis. The public opinion analysis result can refer to the multi-dimensional analysis result obtained by the model after performing multi-dimensional public opinion analysis on the input multi-modal public opinion data. The public opinion event can refer to a public opinion event to be handled separately for each user under the target business. It can be understood as treating each user's public opinion data (such as structured feature data of feedback opinions or evaluations) for the target business as a separate event that needs to be processed.

[0056] Specifically, taking a large language model as an example, the multimodal public opinion analysis model is used. The default public opinion data in the preset public opinion analysis prompts is replaced with multimodal public opinion data corresponding to each user under the target business, resulting in the current public opinion analysis prompts for the current user. For the current user, the current public opinion analysis prompts are input into the large language model for multi-dimensional public opinion analysis to determine the public opinion analysis results corresponding to the target business. The original multimodal data corresponding to the current user is associated with the public opinion analysis results to form a structured public opinion event (i.e., the public opinion event corresponding to the current user under the target business), and this public opinion event is stored in the database, including metadata of the public opinion record, the original multimodal data, and the public opinion analysis results.

[0057] For example, in this embodiment, the multimodal public opinion analysis system includes a public opinion analysis module. The public opinion analysis module is primarily responsible for in-depth analysis and structured processing of the fused multimodal public opinion data. The public opinion analysis module includes two core sub-modules: a public opinion classification sub-module and a public opinion event structured storage sub-module. The public opinion event structured storage sub-module is used to associate the public opinion analysis results of the same user under the target business with the original multimodal data, forming standardized public opinion events and storing them in the database. The stored public opinion records include metadata of the public opinion events, original multimodal data, and public opinion analysis results. Metadata includes, but is not limited to, event ID, timestamp, and data source.

[0058] As an optional implementation of this disclosure, multi-dimensional public opinion analysis is performed on multimodal public opinion data based on a preset public opinion analysis model to determine the public opinion analysis result corresponding to the target business. Specifically, this includes: determining the sentiment polarity determination result corresponding to the target business based on a preset sentiment polarity determination sub-model and multimodal public opinion data; determining the public opinion type identification result corresponding to the target business based on a preset public opinion type identification sub-model and multimodal public opinion data; determining the business entity identification result corresponding to the target business based on a preset business entity identification sub-model and multimodal public opinion data; and determining the topic identification result corresponding to the target business based on a preset topic identification sub-model and multimodal public opinion data.

[0059] In this embodiment of the disclosure, the preset sentiment polarity determination sub-model can refer to a pre-trained deep model for sentiment polarity determination. The sentiment polarity determination result can refer to the classification result of user sentiment polarity in public opinion data. For example, the sentiment polarity determination result can include, but is not limited to, positive, negative, and neutral. The sentiment polarity determination result can also include sentiment scores, and the determination level of sentiment polarity differs when the sentiment score is within different score ranges. The score within the range corresponding to negative results is greater than the score within the range corresponding to neutral results, and the score within the range corresponding to neutral results is greater than the score within the range corresponding to positive results.

[0060] In this embodiment, the preset public opinion type identification sub-model can refer to a pre-trained deep model for public opinion type identification. The public opinion type identification result can refer to the type of content expressed by users in the public opinion data. For example, the public opinion type identification result can include, but is not limited to, complaints, praise, inquiries, suggestions, market news, etc. The preset business entity identification sub-model can refer to a pre-trained deep model for business entity identification. The business entity identification result can refer to the entity presented by the user's evaluation of the target business. When a user uses the product promoted by the target business, they can evaluate or provide opinions on the product, as well as on the product's after-sales service and promotional activities. For example, the business entity identification result can include, but is not limited to, products, services, activities, channels, etc.

[0061] In this embodiment, the preset topic identification sub-model can refer to a pre-trained deep model for topic discovery and clustering. The topic identification result can refer to the core discussion topics automatically summarized from users' multimodal public opinion data. The topic identification result can be a high-level summary of "what specific things users are discussing". For example, the topic identification result in the business category can include, but is not limited to, the reduction of existing mortgage interest rates and the redesign of mobile banking apps; the topic identification result in the event category can include, but is not limited to, a service complaint incident at a branch, an annual performance release conference, and adjustments to credit card points rules; the topic identification result in the public issue category can include, but is not limited to, the pilot experience of digital RMB and the opening of personal pension accounts.

[0062] Specifically, multimodal public opinion data corresponding to each user under the target business is obtained from the multimodal fusion data pool. The multimodal public opinion data for each user is then input into a preset sentiment polarity determination sub-model for sentiment polarity determination, and the sentiment polarity determination result for each user is output based on the sub-model. The multimodal public opinion data for each user is then input into a preset public opinion type identification sub-model for public opinion type identification, and the public opinion type identification result for each user is output based on the sub-model. The multimodal public opinion data for each user is then input into a preset business entity identification sub-model for business entity identification, and the business entity identification result for each user is output based on the sub-model. Finally, the multimodal public opinion data for each user is then input into a preset topic identification sub-model for topic discovery and aggregation, and the topic identification result for each user is output based on the sub-model.

[0063] For example, multimodal public opinion data is fragmented, repetitive, and diverse in expression. For instance, regarding mortgage interest rates, users might express questions like "When will mortgage rates decrease?", "Can monthly payments be reduced?", and "Interest rate reduction policies?". By employing topic discovery and aggregation techniques within a pre-defined topic identification sub-model, clustering algorithms can automatically group semantically similar content into a single category, forming a clear topic cluster. This allows for the automatic and rapid identification of public opinion focus, i.e., the topic. Clustering, based on deep semantic similarity of text, can more intelligently and comprehensively capture different expressions of the same event, ensuring comprehensive topic coverage.

[0064] It should be noted that clustering public opinion data into themes allows for effective quantitative statistics and analysis of target businesses. For example, calculating volume: identifying mortgage interest rates as the most discussed topic this week; analyzing sentiment distribution: finding that negative sentiment accounted for a relatively high proportion under the theme of financial product volatility; tracking evolution: observing how the popularity of the digital RMB theme changes over time.

[0065] For example, the large language model can also call the above four dedicated sub-models to achieve multi-dimensional public opinion analysis and obtain the public opinion analysis results corresponding to each user under the target business.

[0066] For example, the public opinion classification submodule within the public opinion analysis module. This submodule is primarily responsible for in-depth analysis of the fused multimodal public opinion data. It can be used to achieve multi-dimensional public opinion analysis through large language models or multiple parallel deep learning models, including sentiment polarity determination (positive / negative / neutral), public opinion type identification (complaints / praise / inquiries / suggestions / market news, etc.), business entity identification (products / services / activities / channels, etc.), and topic discovery and aggregation.

[0067] S140. Based on the preset auxiliary decision-making method, conduct decision analysis on public opinion events, determine the corresponding handling decisions for public opinion events, and push the handling decisions to the business system to which the target business belongs.

[0068] In this embodiment, the preset auxiliary decision-making method can refer to a pre-set automatic generation method for handling decisions of different public opinion events. The preset auxiliary decision-making method and the execution procedure of this step can be configured in the auxiliary decision-making module of the multimodal public opinion analysis system. The handling decision can refer to a response strategy adaptively formulated for public opinion events. For example, the handling decision can be used to solve problems raised by users regarding the target business, and can also be used to adjust the implementation plan of the target business based on valid suggestions from users. The business system can refer to the project system used to execute the target business. For example, the business system can be, but is not limited to, a work order system or a CRM system.

[0069] Specifically, the system retrieves public opinion records corresponding to the public opinion events from the database storing these events. Each result in the public opinion analysis results within the records is scored based on preset scoring rules to determine the public opinion score for the event. Based on the pre-defined correspondence between public opinion scores and decision-making generation methods, the system determines the decision-making generation method corresponding to the score. This method is then used to generate a decision that aligns with the public opinion records. The decision is automatically pushed to the target business system (e.g., a work order system, CRM system) via an API gateway, and the complete decision execution process is recorded, including the decision basis, execution instructions, and handling status.

[0070] For example, the multimodal public opinion analysis system in this embodiment may further include: a user interaction module; wherein, the user interaction module is used to display the overall public opinion situation of the public opinion event to the user, provide real-time alerts for high-risk public opinion events, and support user conditional queries and full-process tracking of public opinion events.

[0071] In this embodiment, the user interaction module is mainly responsible for providing users with comprehensive public opinion visualization and interactive operation functions. The core functions of this module include: (1) Visual display of public opinion hotspots: displaying the overall situation of public opinion through dashboards, trend charts, heat maps and other forms; (2) Alarm center: providing real-time alarms for high-risk public opinion; (3) Public opinion retrieval: supporting users to flexibly query by keywords, time range, event type and other conditions; (4) Handling process tracking: providing full-process status tracking of public opinion monitoring from the discovery of public opinion to the completion of handling.

[0072] Specifically, the user interaction module enables result display and feedback. This module acquires data from various modules in real time and uses visualization components to show users information such as the distribution of public opinion hotspots and the progress of handling. Users can also use the search function to query specific public opinion events and the filtering function to focus on content of interest. This module provides a handling process tracking function, allowing users to view the handling status and decision-making effects of each public opinion event in real time. Based on the feedback data on the handling effects, the rules for determining the value of public opinion and the decision generation algorithm are continuously optimized.

[0073] It's important to note the interactive mechanism and system architecture where users dynamically configure filtering criteria through the front-end interface, and the system back-end responds in real-time and renders the visualized results. This interactive design allows users with different business backgrounds to flexibly customize monitoring views according to their responsibilities, quickly focusing on key information. Combined with the structured and actionable response suggestions provided by the AI-assisted decision-making engine, it significantly reduces the burden of information filtering and strategy formulation for operations personnel, optimizes the workflow and efficiency from public opinion discovery to response decision-making, and further enhances the flexibility of system operation and the efficiency of decision support.

[0074] The technical solution of this invention acquires raw multimodal data associated with a target business to perform multi-dimensional public opinion analysis on the raw multimodal data, thereby improving the richness and diversity of the basic data to be analyzed. It processes the raw multimodal data based on the data processing methods corresponding to each data type to determine the multimodal public opinion data corresponding to the target business. Based on a preset public opinion analysis model, it performs multi-dimensional public opinion analysis on the multimodal public opinion data to determine the public opinion analysis results corresponding to the target business, thus obtaining multi-dimensional analysis results to provide accurate public opinion analysis results for subsequent decision-making, thereby improving the accuracy of decision-making. The raw multimodal data is correlated with the public opinion analysis results to obtain the public opinion events corresponding to the target business. Based on a preset auxiliary decision-making method, the public opinion events are analyzed to determine the corresponding handling decisions, and the handling decisions are pushed to the business system to which the target business belongs.

[0075] It should be noted that the technical solution of this invention organically integrates the previously relatively independent data collection, analysis, display and processing stages into a collaborative system. Through technical means, it realizes a coherent process from risk perception, analysis and judgment to decision support and action tracking, thereby helping banks build a more agile and efficient modern public opinion management system and realizing an integrated and intelligent public opinion management closed loop.

[0076] Example 2

[0077] Figure 2 This is a flowchart of a multimodal public opinion analysis method provided in Embodiment 2 of the present invention. Based on the above embodiments, this embodiment describes in detail the process of performing decision analysis on public opinion events based on a preset auxiliary decision-making method to determine the corresponding handling decisions for public opinion events. Explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here. Figure 2 As shown, the method includes:

[0078] S210. Obtain the raw multimodal data associated with the target business.

[0079] S220. Based on the data processing method corresponding to each data type, process the original multimodal data to determine the multimodal public opinion data corresponding to the target business.

[0080] S230. Based on the preset public opinion analysis model, perform multi-dimensional public opinion analysis on multimodal public opinion data, determine the public opinion analysis results corresponding to the target business, and associate the original multimodal data with the public opinion analysis results to obtain the public opinion events corresponding to the target business.

[0081] S240. Based on the emotional polarity determination results and public opinion type identification results corresponding to the public opinion event, determine the handling priority and decision-making direction of the public opinion event.

[0082] In this embodiment of the disclosure, the handling priority can refer to the sequential handling order of all public opinion events under the target business. Public opinion events with higher handling priority can generate in-depth analysis reports and / or be handled first. The handling priority can be used to characterize the importance or impact of public opinion events. The decision direction can refer to the direction of decision generation for public opinion events. The decision direction can determine the generation method of the corresponding handling decision for public opinion events. For example, for negative public opinion, handling suggestions (such as appeasing customers) are generated; for positive public opinion, advantage analysis reports (such as marketing promotion) are generated; and for neutral public opinion, optimization strategies (such as process optimization) are generated.

[0083] Specifically, the system retrieves the corresponding public opinion records for each event from a database storing such events. Based on pre-set value judgment criteria and the sentiment polarity and sentiment type identification results in the records, a value judgment is made to determine the priority and direction of action. For example, a public opinion event with a negative sentiment polarity and a sentiment type identification result of "inquiry" has a lower priority than one with a negative sentiment polarity and a sentiment type identification result of "complaint." Furthermore, if a public opinion event with a negative sentiment polarity can be classified as negative public opinion, or a public opinion event with a sentiment type identification result of "complaint" can be classified as negative public opinion, then the decision-making direction for that event is to generate action recommendations.

[0084] For example, the criteria for determining the priority of handling and the direction of decision-making can also include the degree of attention paid to the public opinion data expressed by users, in addition to the above. Among them, the higher the degree of attention paid, the higher the priority of handling and the more formal or lenient the direction of decision-making.

[0085] For example, the emotional polarity determination result and the public opinion type identification result can also be scored by preset scoring rules to obtain the scoring result, so as to use the scoring result and preset decision direction range to determine the priority and decision direction of the handling of public opinion events.

[0086] S250: Based on the priority of handling, decision-making direction, and preset large language model, determine the in-depth analysis report corresponding to the public opinion event.

[0087] In this embodiment of the disclosure, the preset large language model can refer to a large language model that has been pre-tuned and can be used to generate decision-making for handling different public opinion events. The in-depth analysis report can refer to a comprehensive analysis and handling report of public opinion events generated by combining public opinion events and decision-making directions.

[0088] Specifically, public opinion events are sorted from highest to lowest priority for handling. The decision direction of each event is then used to replace the default decision direction in the preset decision generation prompts, and the specific content of the event is used to replace the default public opinion content. This generates decision generation prompts for each public opinion event. These prompts are then input into a preset large language model, which comprehensively considers the specific content of the public opinion event and generates an in-depth analysis report corresponding to the specified decision direction.

[0089] It should be noted that, through cross-modal correlation analysis technology, the system can effectively correlate and integrate scattered public opinion information from different sources and in different forms, thereby helping banks to more clearly grasp the ins and outs, root causes and potential impacts of public opinion events. This allows the analysis conclusions to move from simple factual descriptions to revealing internal connections and providing decision-making basis, further enhancing the depth and correlation insight capabilities of public opinion analysis.

[0090] S260. Based on the in-depth analysis report, the decision-making and execution transformation is carried out to determine the corresponding handling decision for the public opinion event and push the handling decision to the business system to which the target business belongs.

[0091] In this embodiment of the disclosure, the in-depth analysis report of positive public opinion includes an analysis of the advantages of the target business. The in-depth analysis report of neutral public opinion includes optimization strategies for the target business. The in-depth analysis report of negative public opinion includes suggestions for handling the target business or the public opinion event. No decision-making conversion is required for the in-depth analysis report of positive public opinion. Decision-making conversion is required for the in-depth analysis report of negative public opinion. Decision-making conversion is required for the in-depth analysis report of neutral public opinion.

[0092] Specifically, in-depth analysis reports on negative public opinion are transformed into decision-making execution reports, resulting in structured order instructions corresponding to the negative public opinion events. In-depth analysis reports on neutral public opinion are also transformed into decision-making execution reports, resulting in standard response suggestions for neutral public opinion events. These structured order instructions are then pushed to the business systems of the target business.

[0093] Based on the above technical solutions, the multimodal public opinion analysis system in this embodiment includes an auxiliary decision-making module. This module is mainly responsible for making value judgments based on the public opinion analysis results and generating decision instructions. The core functions of this module include: (1) Public opinion value judgment: Based on the emotional polarity judgment results (level or score) and public opinion type identification results of the public opinion event, the priority of handling the public opinion event and the decision direction are automatically determined; (2) Intelligent analysis report generation: Based on the judgment results, in-depth analysis reports are automatically generated using technologies such as large language models, including handling suggestions, advantage analysis or optimization strategies; (3) Public opinion event diversion and push: The decision results are converted into executable instructions and automatically pushed to the bank's internal work order system and other business systems through the system interface.

[0094] It should be noted that the AI-assisted decision engine applied to public opinion management can infer and generate specific implementation methods (including model structure, rule templates and generation logic) from the case library and rule library based on the characteristics of the input public opinion event.

[0095] The technical solution of this invention determines the handling priority and decision-making direction of a public opinion event based on the emotional polarity judgment result and public opinion type identification result. This automatically determines the handling priority (e.g., urgent / high / medium / low) and decision-making direction (e.g., appeasing customers, optimizing processes, marketing promotion) based on emotion (positive / negative) and type (complaint / suggestion, etc.), replacing the subjectivity and lag of manual judgment, ensuring that key events are discovered immediately and guided to the correct handling path. Based on the handling priority, decision-making direction, and a preset large language model, a deep analysis report corresponding to the public opinion event is determined. This report is automatically generated using a large language model (LLM) based on structured information (priority, direction, specific content), replacing the arduous work of analysts manually writing reports. It not only completes quickly but also provides correlation analysis, background supplementation, and compliance suggestions that the human brain might overlook based on the model's knowledge base. The deep analysis report is then used for decision execution transformation to determine the handling decision corresponding to the public opinion event. The system outputs are no longer simple warning signals, but rather directly actionable decisions (such as generating customer follow-up work orders, initiating product bug fixing processes, and forwarding them to the marketing department as success stories), realizing a solution from problem discovery to problem resolution. Furthermore, it can quickly intervene in negative public opinion to control risks, and proactively transform positive public opinion and user suggestions into opportunities for service optimization and product innovation, shifting from passive response to proactive management.

[0096] The following are embodiments of the multimodal public opinion analysis system provided by the present invention. This system and the multimodal public opinion analysis methods of the above embodiments belong to the same inventive concept. For details not described in detail in the embodiments of the multimodal public opinion analysis system, please refer to the embodiments of the above multimodal public opinion analysis methods.

[0097] Example 3

[0098] Figure 3 This is a schematic diagram of the structure of a multimodal public opinion analysis system provided in Embodiment 3 of the present invention. Figure 3 As shown, the system includes: a data acquisition module 310, a data processing module 320, a public opinion analysis module 330, and a decision support module 340.

[0099] The system includes: a data acquisition module 310 for acquiring raw multimodal data related to the target business; a data processing module 320 for processing the raw multimodal data based on the data processing method corresponding to each data type to determine the multimodal public opinion data corresponding to the target business; a public opinion analysis module 330 for performing multi-dimensional public opinion analysis on the multimodal public opinion data based on a preset public opinion analysis model to determine the public opinion analysis results corresponding to the target business, and associating the raw multimodal data with the public opinion analysis results to obtain the public opinion events corresponding to the target business; and a decision support module 340 for performing decision analysis on the public opinion events based on a preset decision support method to determine the corresponding handling decisions for the public opinion events, and pushing the handling decisions to the business system to which the target business belongs.

[0100] The technical solution of this invention acquires raw multimodal data associated with a target business to perform multi-dimensional public opinion analysis on the raw multimodal data, thereby improving the richness and diversity of the basic data to be analyzed. It processes the raw multimodal data based on the data processing methods corresponding to each data type to determine the multimodal public opinion data corresponding to the target business. Based on a preset public opinion analysis model, it performs multi-dimensional public opinion analysis on the multimodal public opinion data to determine the public opinion analysis results corresponding to the target business, thus obtaining multi-dimensional analysis results to provide accurate public opinion analysis results for subsequent decision-making, thereby improving the accuracy of decision-making. The raw multimodal data is correlated with the public opinion analysis results to obtain the public opinion events corresponding to the target business. Based on a preset auxiliary decision-making method, the public opinion events are analyzed to determine the corresponding handling decisions, and the handling decisions are pushed to the business system to which the target business belongs.

[0101] For example, the system also includes a user interaction module; wherein the user interaction module is used to display the overall situation of public opinion events to users, provide real-time alerts for high-risk public opinion events, and support users' conditional queries and full-process tracking of public opinion events.

[0102] Based on the above technical solutions, the data processing module 320 is specifically used for: denoising, segmenting, and removing stop words from multimodal data of text type to determine the text-based public opinion data corresponding to the target business; extracting text from images and recognizing visual elements from multimodal data of image type to determine the image-based public opinion data corresponding to the target business; and performing speech recognition, extracting text from keyframes, and recognizing visual elements from multimodal data of video type to determine the video-based public opinion data corresponding to the target business.

[0103] Based on the above technical solution, the data processing module 320 is also used to store the multimodal public opinion data obtained after data processing into a multimodal fusion data pool, so that multimodal public opinion data corresponding to the target business can be obtained from the multimodal fusion data pool during public opinion analysis; or, the multimodal public opinion data obtained after data processing is fused to obtain fused multimodal public opinion data, and the fused multimodal public opinion data is stored into a multimodal fusion data pool, so that multimodal public opinion data corresponding to the target business can be obtained from the multimodal fusion data pool during public opinion analysis.

[0104] Based on the above technical solution, the public opinion analysis module 330 is specifically used for: determining the sentiment polarity determination result corresponding to the target business based on the preset sentiment polarity determination sub-model and multimodal public opinion data; determining the public opinion type identification result corresponding to the target business based on the preset public opinion type identification sub-model and multimodal public opinion data; determining the business entity identification result corresponding to the target business based on the preset business entity identification sub-model and multimodal public opinion data; and determining the topic identification result corresponding to the target business based on the preset topic identification sub-model and multimodal public opinion data.

[0105] Based on the above technical solution, the auxiliary decision-making module 340 is specifically used to: determine the handling priority and decision direction of the public opinion event based on the sentiment polarity judgment result and public opinion type identification result; determine the in-depth analysis report of the public opinion event based on the handling priority, decision direction and preset large language model; and determine the handling decision of the public opinion event based on the decision execution transformation of the in-depth analysis report.

[0106] The multimodal public opinion analysis system provided in this embodiment of the invention can execute the multimodal public opinion analysis method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the multimodal public opinion analysis method.

[0107] It is worth noting that in the above embodiments of multimodal public opinion analysis, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0108] Example 4

[0109] Figure 4 A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0110] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0111] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0112] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as multimodal sentiment analysis methods.

[0113] In some embodiments, the multimodal public opinion analysis method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the multimodal public opinion analysis method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the multimodal public opinion analysis method by any other suitable means (e.g., by means of firmware).

[0114] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0115] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0116] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0117] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0118] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0119] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0120] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the multimodal public opinion analysis method provided in any embodiment of this application.

[0121] In implementing the computer program product, computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider). This program product belongs to the same inventive concept as the multimodal public opinion analysis method disclosed in the embodiments of this application, and therefore will not be described further here.

[0122] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0123] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A multimodal public opinion analysis method, characterized in that, include: Obtain raw multimodal data related to the target business; The original multimodal data is processed according to the data processing method corresponding to each data type to determine the multimodal public opinion data corresponding to the target business; Based on a preset public opinion analysis model, multi-dimensional public opinion analysis is performed on the multimodal public opinion data to determine the public opinion analysis results corresponding to the target business, and the original multimodal data is associated with the public opinion analysis results to obtain the public opinion events corresponding to the target business. The public opinion event is analyzed based on a preset auxiliary decision-making method to determine the corresponding handling decision and push the handling decision to the business system to which the target business belongs.

2. The method according to claim 1, characterized in that, The process of processing the original multimodal data based on the data processing method corresponding to each data type to determine the multimodal public opinion data corresponding to the target business includes: Denoising, word segmentation, and stop word removal are performed on multimodal text data to determine the text-based public opinion data corresponding to the target business. The text is extracted and visual elements are recognized from multimodal data of image types to determine the image-based public opinion data corresponding to the target business. Speech recognition, keyframe text extraction, and visual element recognition are performed on multimodal video data to determine the video public opinion data corresponding to the target business.

3. The method according to claim 1, characterized in that, The method further includes: The processed multimodal public opinion data is stored in a multimodal fusion data pool so that multimodal public opinion data corresponding to the target business can be retrieved from the multimodal fusion data pool during public opinion analysis; or, The multimodal public opinion data obtained after data processing is fused to obtain fused multimodal public opinion data, and the fused multimodal public opinion data is stored in a multimodal fusion data pool so that the multimodal public opinion data corresponding to the target business can be obtained from the multimodal fusion data pool during public opinion analysis.

4. The method according to claim 1, characterized in that, The step of performing multi-dimensional public opinion analysis on the multimodal public opinion data based on a preset public opinion analysis model to determine the public opinion analysis results corresponding to the target business includes: Based on the preset sentiment polarity determination sub-model and the multimodal public opinion data, the sentiment polarity determination result corresponding to the target business is determined; Based on the preset public opinion type identification sub-model and the multimodal public opinion data, the public opinion type identification result corresponding to the target business is determined; Based on the preset business entity identification sub-model and the multimodal public opinion data, the business entity identification result corresponding to the target business is determined; Based on the preset topic recognition sub-model and the multimodal public opinion data, the topic recognition result corresponding to the target business is determined.

5. The method according to claim 1, characterized in that, The step of performing decision analysis on the public opinion event based on a preset auxiliary decision-making method to determine the corresponding handling decision for the public opinion event includes: Based on the sentiment polarity determination results and public opinion type identification results corresponding to the public opinion event, the handling priority and decision-making direction corresponding to the public opinion event are determined; Based on the aforementioned handling priorities, decision-making directions, and a preset large language model, a deep analysis report corresponding to the public opinion event is determined. Based on the in-depth analysis report, decision-making and execution are carried out to determine the corresponding handling decisions for the public opinion event.

6. A multimodal public opinion analysis system, characterized in that, The system includes: The data acquisition module is used to acquire raw multimodal data related to the target business. The data processing module is used to process the original multimodal data based on the data processing method corresponding to each data type, and determine the multimodal public opinion data corresponding to the target business. The public opinion analysis module is used to perform multi-dimensional public opinion analysis on the multimodal public opinion data based on a preset public opinion analysis model, determine the public opinion analysis results corresponding to the target business, and associate the original multimodal data with the public opinion analysis results to obtain the public opinion events corresponding to the target business. The auxiliary decision-making module is used to perform decision analysis on the public opinion event based on a preset auxiliary decision-making method, determine the corresponding handling decision for the public opinion event, and push the handling decision to the business system to which the target business belongs.

7. The system according to claim 6, characterized in that, The system further includes: a user interaction module; wherein... The user interaction module is used to display the overall situation of public opinion events to users, provide real-time alerts for high-risk public opinion events, and support users' conditional queries and full-process tracking of public opinion events.

8. An electronic device, characterized in that, The electronic device includes: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the multimodal public opinion analysis method as described in any one of claims 1-5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the multimodal public opinion analysis method as described in any one of claims 1-5.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the multimodal public opinion analysis method as described in any one of claims 1-5.

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