Word-of-mouth information evaluation method based on data analysis

By using web crawling technology and the BERT model to filter content from online forums and combining it with NLP technology for sentiment analysis, the problem of efficiently evaluating word-of-mouth information in online forums was solved, achieving high-accuracy extraction of word-of-mouth information and assessment of its positivity.

CN119691188BActive Publication Date: 2025-11-14NANJING UNIV
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Patent Information

Application Number
CN202411765888.8
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-12-04
Publication Date
2025-11-14
Estimated Expiration
2044-12-04

AI Technical Summary

Technical Problem

The amount of reputation information in online forums is huge, heterogeneous, noisy, and dynamically changing, making it difficult to analyze and evaluate efficiently and accurately.

Method used

We used web crawling technology to obtain forum content, filtered and used the BERT model to screen word-of-mouth, used NLP technology to extract adjectives and degree adverbs for sentiment analysis, and combined negative words to evaluate the positivity of word-of-mouth, thus establishing a scoring method for the positivity of word-of-mouth evaluation.

Benefits of technology

It achieves high accuracy in word-of-mouth information extraction and evaluation with limited training data, alleviating the problems of data scarcity and annotation quality, and accurately judging the positivity of word-of-mouth evaluations.

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Abstract

This invention discloses a data analysis-based method for evaluating word-of-mouth information, belonging to the field of information evaluation technology. It utilizes web crawling technology to acquire content generated in forums; the original sentences are placed into a filter, and after filtering, formal word-of-mouth information is obtained; adjectives, degree adverbs, and negation words in the original sentences are extracted using NLP technology and evaluated; the sentiment assignment of degree adverbs and adjectives is combined to score the positivity of the word-of-mouth evaluation, and the positivity of the word-of-mouth evaluation is determined based on the score results; the obtained word-of-mouth polarity and positivity of the word-of-mouth evaluation are output. This invention divides the entire word-of-mouth mining task into multiple sub-tasks for simplification, greatly alleviating the problems of data scarcity and annotation quality. Furthermore, by calculating the positivity score of the word-of-mouth, it can maintain high accuracy while extracting more word-of-mouth information and judging the positivity of the word-of-mouth evaluation.
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