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| Analysis of Public Sentiment in Libraries Based on Text Mining |
| Chengdu Technological University |
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Abstract With the increasing influence of mobile Internet on young readers in university libraries, the proportion of new generation
readers using QQ instant messaging software is increasing, text mining of library QQ group text information can be used to under‐
stand the public sentiment of the library, which can be used for library public sentiment warning and provide strong public sentiment
response capabilities for library decision-makers. Web crawler technology is used to crawl chat records in QQ groups from Septem‐
ber 2022 to December 2022 as library public sentiment data, then performing data preprocessing operations such as deduplication
and cleaning on the original public sentiment data. Then, Tsinghua University's Thulac segmentation technology is used to extract
keywords and calculate their weights from the public sentiment data, and them the WordCloud library is used for visualization. Next,
the spaCy library is used to to calculate specific emotional tendencies and scores for public opinion data, and finally the emotional
tendencies of library public opinion are analyzed through experiments.
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Published: 02 July 2024
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