International Journal of Geo-Information Article Perceiving Residents’ Festival Activities Based on Social Media Data: A Case Study in Beijing, China Bingqing Wang 1, Bin Meng 1,*, Juan Wang 1, Siyu Chen 1 and Jian Liu 2 1 College of Applied Arts and Sciences, Beijing Union University, No. 197 Beitucheng West Road, Beijing 100191, China;
[email protected] (B.W.);
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[email protected] (S.C.) 2 College of Resource Environment and Tourism, Capital Normal University, No. 105 West 3rd Ring Road North, Beijing 100048, China;
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[email protected] Abstract: Social media data contains real-time expressed information, including text and geographical location. As a new data source for crowd behavior research in the era of big data, it can reflect some aspects of the behavior of residents. In this study, a text classification model based on the BERT and Transformers framework was constructed, which was used to classify and extract more than 210,000 residents’ festival activities based on the 1.13 million Sina Weibo (Chinese “Twitter”) data collected from Beijing in 2019 data. On this basis, word frequency statistics, part-of-speech analysis, topic model, sentiment analysis and other methods were used to perceive different types of festival activities and quantitatively analyze the spatial differences of different types of festivals. The results show that traditional culture significantly influences residents’ festivals, reflecting residents’ motivation to participate in festivals and how residents participate in festivals and express their emotions. There are apparent spatial differences among residents in participating in festival activities.