{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T03:42:16Z","timestamp":1778643736455,"version":"3.51.4"},"reference-count":45,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,7,5]],"date-time":"2024-07-05T00:00:00Z","timestamp":1720137600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Sponsored by the team-building subsidy of \u201cXuezhi Professorship\u201d of the College of Applied Arts and Science of Beijing Union University","award":["BUUCAS-XZJSTD-2024005"],"award-info":[{"award-number":["BUUCAS-XZJSTD-2024005"]}]},{"name":"Sponsored by the team-building subsidy of \u201cXuezhi Professorship\u201d of the College of Applied Arts and Science of Beijing Union University","award":["No.ZKZD202305"],"award-info":[{"award-number":["No.ZKZD202305"]}]},{"name":"The Academic Research Projects of Beijing Union University","award":["BUUCAS-XZJSTD-2024005"],"award-info":[{"award-number":["BUUCAS-XZJSTD-2024005"]}]},{"name":"The Academic Research Projects of Beijing Union University","award":["No.ZKZD202305"],"award-info":[{"award-number":["No.ZKZD202305"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>With the support of big data mining techniques, utilizing social media data containing location information and rich semantic text information can construct large-scale daily activity OD flows for urban populations, providing new data resources and research perspectives for studying urban spatiotemporal structures. This paper employs the ST-DBSCAN algorithm to identify the residential locations of Weibo users in four communities and then uses the BERT model for activity-type classification of Weibo texts. Combined with the TF-IDF method, the results are analyzed from three aspects: temporal features, spatial features, and semantic features. The research findings indicate: \u2460 Spatially, residents\u2019 daily activities are mainly centered around their residential locations, but there are significant differences in the radius and direction of activity among residents of different communities; \u2461 In the temporal dimension, the activity intensities of residents from different communities exhibit uniformity during different time periods on weekdays and weekends; \u2462 Based on semantic analysis, the differences in activities and venue choices among residents of different communities are deeply influenced by the comprehensive characteristics of the communities. This study explores methods for OD information mining based on social media data, which is of great significance for expanding the mining methods of residents\u2019 spatiotemporal behavior characteristics and enriching research on the configuration of public service facilities based on community residents\u2019 activity spaces and facility demands.<\/jats:p>","DOI":"10.3390\/info15070392","type":"journal-article","created":{"date-parts":[[2024,7,5]],"date-time":"2024-07-05T12:30:59Z","timestamp":1720182659000},"page":"392","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Research on Resident Behavioral Activities Based on Social Media Data: A Case Study of Four Typical Communities in Beijing"],"prefix":"10.3390","volume":"15","author":[{"given":"Zhiyuan","family":"Ou","sequence":"first","affiliation":[{"name":"College of Applied Arts and Sciences, Beijing Union University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bingqing","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Applied Arts and Sciences, Beijing Union University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1605-4826","authenticated-orcid":false,"given":"Bin","family":"Meng","sequence":"additional","affiliation":[{"name":"College of Applied Arts and Sciences, Beijing Union University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changsheng","family":"Shi","sequence":"additional","affiliation":[{"name":"College of Applied Arts and Sciences, Beijing Union University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4575-0652","authenticated-orcid":false,"given":"Dongsheng","family":"Zhan","sequence":"additional","affiliation":[{"name":"School of Management, Zhejiang University of Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,5]]},"reference":[{"key":"ref_1","unstructured":"Yu, M. (2023, December 20). Beijing Seventh National Population Census Bulletin (No. 3), Available online: http:\/\/www.beijing.gov.cn\/gongkai\/shuju\/sjjd\/202105\/t20210519_2392888.html."},{"key":"ref_2","unstructured":"Zhu, Y. (2023, April 05). Beijing Urban Master Plan (2016\u20132035), Available online: http:\/\/www.gov.cn\/xinwen\/2017-09\/30\/content_5228705.html."},{"key":"ref_3","unstructured":"Planning Department (2023, June 06). The Fourteenth Five-Year Plan for National Economic and Social Development and the Long-Term Goals for 2035 of Beijing, Available online: https:\/\/www.ndrc.gov.cn\/fggz\/fzzlgh\/dffzgh\/202103\/t20210331_1271321.html?code=&state=123."},{"key":"ref_4","first-page":"1106","article-title":"Urban space study based on the temporal characteristics of residents\u2019 behavior","volume":"37","author":"Weijing","year":"2018","journal-title":"Prog. Geogr."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"490","DOI":"10.2307\/2981088","article-title":"Urban population densities","volume":"114","author":"Clark","year":"1951","journal-title":"J. R. Stat. Soc. Ser. A"},{"key":"ref_6","first-page":"69","article-title":"Origins and review of urban time-space structure studies","volume":"25","author":"Gu","year":"2016","journal-title":"World Reg. Stud."},{"key":"ref_7","first-page":"2069","article-title":"A comparative study on the commuting behavior of residents in large residential areas in Beijing\u2014Take Wangjing and Tiantongyuan residential area as examples","volume":"31","author":"Bin","year":"2012","journal-title":"Geogr. Res."},{"key":"ref_8","first-page":"1187","article-title":"Spatial Voronoi partitioning algorithm and OD flow visualization analysis considering the distribution density of taxi OD points","volume":"17","author":"Rui","year":"2015","journal-title":"J. Geo-Inf. Sci."},{"key":"ref_9","first-page":"1160","article-title":"Overview of visual analysis of OD data","volume":"33","author":"Le","year":"2021","journal-title":"J. Comput. Aided Des. Comput. Graph."},{"key":"ref_10","first-page":"1273","article-title":"Visualization of movement trajectory data","volume":"24","author":"Jiansu","year":"2012","journal-title":"J. Comput. Aided Des. Comput. Graph."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Tao, F., Wu, J., Lin, S., Lv, Y., Wang, Y., and Zhou, T. (2023). Revealing the impact of COVID-19 on urban residential travel structure based on floating Car trajectory data: A case study of nantong, China. ISPRS Int. J. Geo-Inf., 12.","DOI":"10.3390\/ijgi12020055"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Guo, X., Xu, Z., Zhang, J., Lu, J., and Zhang, H. (2020). An OD flow clustering method based on vector constraints: A case study for Beijing taxi origin-destination data. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9020128"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"7943","DOI":"10.1109\/TITS.2023.3266371","article-title":"Deep Learning for Metro Short-Term Origin-Destination Passenger Flow Forecasting Considering Section Capacity Utilization Ratio","volume":"24","author":"Zhang","year":"2023","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"19054","DOI":"10.1109\/JIOT.2023.3281648","article-title":"MG-ASTN: Multi-Graph Framework with Attentive Spatial-Temporal Networks for Crowd Mobility Prediction","volume":"10","author":"Luo","year":"2023","journal-title":"IEEE Internet Things J."},{"key":"ref_15","first-page":"128","article-title":"Demand forecasting of taxi travel based on GPS data","volume":"39","author":"Lishan","year":"2021","journal-title":"J. Transp. Inf. Saf."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"11628","DOI":"10.1109\/TKDE.2023.3236060","article-title":"Multi-Task Weakly Supervised Learning for Origin-Destination Travel Time Estimation","volume":"35","author":"Wang","year":"2023","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_17","first-page":"1023","article-title":"Visual Analysis of Group Behavior Based on Origin-Destination Data","volume":"30","author":"Wenda","year":"2018","journal-title":"J. Comput. Aided Des. Comput. Graph."},{"key":"ref_18","first-page":"718","article-title":"Citizen Commuting Analysis Using Mobile Trajectory Data","volume":"46","author":"Qiong","year":"2021","journal-title":"Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_19","first-page":"1352","article-title":"Research methods of urban spatiotemporal behavior in the era of big data","volume":"32","author":"Xiao","year":"2013","journal-title":"Prog. Geogr."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.landurbplan.2018.08.020","article-title":"Measuring human perceptions of a large-scale urban region using machine learning","volume":"180","author":"Zhang","year":"2018","journal-title":"Landsc. Urban Plan."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Wang, B., Meng, B., Wang, J., Chen, S., and Liu, J. (2021). Perceiving Residents\u2019 Festival Activities Based on Social Media Data: A Case Study in Beijing, China. ISPRS Int. J. Geo-Inf., 10.","DOI":"10.3390\/ijgi10070474"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"580","DOI":"10.18306\/dlkxjz.2021.04.004","article-title":"Measurement of community daily activity space and influencing factors of vitality based on residents\u2019 spatiotemporal behavior: Taking Shazhou and Nanyuan streets in Nanjing as examples","volume":"40","author":"Sicong","year":"2021","journal-title":"Prog. Geogr."},{"key":"ref_23","unstructured":"Beijing Infinite Forward Technology Co., Ltd. (2017). Talking Data: Observation Report on Travel in Large Beijing Communitie, Beijing Infinite Forward Technology Co., Ltd."},{"key":"ref_24","unstructured":"Sina Weibo Data Center (2021). 2020 Weibo User Development Report, Weibo Corporation."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.compenvurbsys.2018.11.001","article-title":"Social Media data: Challenges, opportunities and limitations in urban studies","volume":"74","author":"Marti","year":"2019","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_26","first-page":"51","article-title":"Mining urban perceptions from social media data","volume":"20","author":"Liu","year":"2020","journal-title":"J. Spat. Int. Sci."},{"key":"ref_27","first-page":"290","article-title":"The Mining and Analysis of Emergency Information Sudden Events Based on Social Media","volume":"41","author":"Yandong","year":"2016","journal-title":"Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.compenvurbsys.2015.01.002","article-title":"A scalable framework for spatiotemporal analysis of location-based social media data","volume":"51","author":"Cao","year":"2015","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"101551","DOI":"10.1016\/j.compenvurbsys.2020.101551","article-title":"Activity knowledge discovery: Detecting collective and individual activities with digital footprints and open source geographic data","volume":"85","author":"Liu","year":"2021","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_30","first-page":"14","article-title":"Big Data and Its Cause of Formation","volume":"4","author":"Zipei","year":"2014","journal-title":"Sci. Society."},{"key":"ref_31","unstructured":"Devlin, J., Chang, M.W., Lee, K., and Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv."},{"key":"ref_32","unstructured":"Kai, J. (2014). Social Media Mining and Application with Geographic Location Information, University of Science and Technology of China."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Liu, J., Meng, B., Wang, J., Chen, S., Tian, B., and Zhi, G. (2021). Exploring the Spatiotemporal Patterns of Residents\u2019 Daily Activities Using Text-Based Social Media Data: A Case Study of Beijing, China. ISPRS Int. J. Geo-Inf., 10.","DOI":"10.3390\/ijgi10060389"},{"key":"ref_34","unstructured":"Driver, H.E., and Kroeber, A.L. (1932). Quantitative Expression of Cultural Relationships, University of California Press."},{"key":"ref_35","unstructured":"Tryon, R.C. (1939). Cluster Analysis, Edwards Brothers."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"4459","DOI":"10.1007\/s11192-022-04463-x","article-title":"A new clustering method to explore the dynamics of research communities","volume":"127","author":"Cambe","year":"2022","journal-title":"Scientometrics"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Lukauskas, M., and Ruzgas, T. (2022). A New Clustering Method Based on the Inversion Formula. Mathematics, 10.","DOI":"10.3390\/math10152559"},{"key":"ref_38","unstructured":"Ester, M., Kriegel, H.P., Sander, J., and Xu, X. (1996, January 2\u20134). A density-based algorithm for discovering clusters in large spatial databases with noise. Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, Portland, OR, USA."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1007\/BF02948834","article-title":"Approaches for scaling DBSCAN algorithm to large spatial database","volume":"15","author":"Aoying","year":"2000","journal-title":"J. Comput. Sci. Technol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1023\/A:1008729828172","article-title":"Multidimensional index structures in relational databases","volume":"15","author":"Bo","year":"2000","journal-title":"J. Intell. Inf. Syst."},{"key":"ref_41","unstructured":"Salton, G. (1971). The SMART Retrieval System\u2014Experiments in Automatic Document Processing, Prentice-Hall Inc."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1108\/eb026526","article-title":"A statistical interpretation of term specificity and its application in retrieval","volume":"28","year":"1972","journal-title":"J. Doc."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1016\/0020-0271(73)90043-0","article-title":"Index term weighting","volume":"9","author":"Jones","year":"1973","journal-title":"Inf. Storage Retr."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.datak.2006.01.013","article-title":"ST-DBSCAN: An algorithm for clustering spatial\u2013temporal data","volume":"60","author":"Birant","year":"2007","journal-title":"Data Knowl. Eng."},{"key":"ref_45","first-page":"790","article-title":"Research and implementation of Chinese text classification related algorithms","volume":"47","author":"Xu","year":"2009","journal-title":"J. Jinlin Univ."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/15\/7\/392\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:10:32Z","timestamp":1760109032000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/15\/7\/392"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,5]]},"references-count":45,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2024,7]]}},"alternative-id":["info15070392"],"URL":"https:\/\/doi.org\/10.3390\/info15070392","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,5]]}}}