{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T17:12:40Z","timestamp":1790701960344,"version":"4.1.0"},"reference-count":59,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2020,11,20]],"date-time":"2020-11-20T00:00:00Z","timestamp":1605830400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Plan","award":["2018YFB0505300"],"award-info":[{"award-number":["2018YFB0505300"]}]},{"name":"2017YFB0503703","award":["2017YFB0503703"],"award-info":[{"award-number":["2017YFB0503703"]}]},{"name":"Guangxi Science and Technology Major Special Project","award":["AA18118025"],"award-info":[{"award-number":["AA18118025"]}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2020M670024"],"award-info":[{"award-number":["2020M670024"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>The Shanghai New Year\u2019s Eve stampede on 31 December 2014, caused 36 deaths and 47 other injuries, generating attention from around the world. This research aims to explore crowd aggregation from the perspective of Sina Weibo check-in data and evaluate the potential of crowd detection based on social media data. We develop a framework using Weibo check-in data in three dimensions: the aggregation level of check-in data, the topic changes in posts and the sentiment fluctuations of citizens. The results show that the numbers of check-ins in all of Shanghai on New Years\u2019 Eve is twice that of other days and that Moran\u2019s I reaches a peak on this date, implying a spatial autocorrelation mode. Additionally, the results of topic modeling indicate that 72.4% of the posts were related to the stampede, reflecting public attitudes and views on this incident from multiple angles. Moreover, sentiment analysis based on Weibo posts illustrates that the proportion of negative posts increased both when the stampede occurred (40.95%) and a few hours afterwards (44.33%). This study demonstrates the potential of using geotagged social media data to analyze population spatiotemporal activities, especially in emergencies.<\/jats:p>","DOI":"10.3390\/ijerph17228640","type":"journal-article","created":{"date-parts":[[2020,11,20]],"date-time":"2020-11-20T09:46:18Z","timestamp":1605865578000},"page":"8640","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Crowd Detection in Mass Gatherings Based on Social Media Data: A Case Study of the 2014 Shanghai New Year\u2019s Eve Stampede"],"prefix":"10.3390","volume":"17","author":[{"given":"Jiexiong","family":"Duan","sequence":"first","affiliation":[{"name":"School of Earth and Space Sciences, Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing 100871, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weixin","family":"Zhai","sequence":"additional","affiliation":[{"name":"College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China"},{"name":"Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengqi","family":"Cheng","sequence":"additional","affiliation":[{"name":"College of Engineering, Peking University, Beijing 100871, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1016\/j.tim.2014.08.004","article-title":"Behavioral insights on big data: Using social media for predicting biomedical outcomes","volume":"22","author":"Young","year":"2014","journal-title":"Trends Microbiol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.tourman.2009.02.016","article-title":"Role of social media in online travel information search","volume":"31","author":"Xiang","year":"2010","journal-title":"Tour. 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