{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T15:12:13Z","timestamp":1774365133000,"version":"3.50.1"},"reference-count":64,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,10,26]],"date-time":"2020-10-26T00:00:00Z","timestamp":1603670400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41971162"],"award-info":[{"award-number":["41971162"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Social Media Big Data (SMBD) is widely used to serve the economic and social development of human beings. However, as a young research and practice field, the understanding of SMBD in academia is not enough and needs to be supplemented. This paper took Web of Science (WoS) core collection as the data source, and used traditional statistical methods and CiteSpace software to carry out the scientometrics analysis of SMBD, which showed the research status, hotspots and trends in this field. The results showed that: (1) More and more attention has been paid to SMBD research in academia, and the number of journals published has been increased in recent years, mainly in subjects such as Computer Science Engineering and Telecommunications. The results were published primarily in IEEE Access Sustainability and Future Generation Computer Systems the International Journal of eScience and so on; (2) In terms of contributions, China, the United States, the United Kingdom and other countries (regions) have published the most papers in SMBD, high-yield institutions also mainly from these countries (regions). There were already some excellent teams in the field, such as the Wanggen Wan team at Shanghai University and Haoran Xie team from City University of Hong Kong; (3) we studied the hotspots of SMBD in recent years, and realized the summary of the frontier of SMBD based on the keywords and co-citation literature, including the deep excavation and construction of social media technology, the reflection and concerns about the rapid development of social media, and the role of SMBD in solving human social development problems. These studies could provide values and references for SMBD researchers to understand the research status, hotspots and trends in this field.<\/jats:p>","DOI":"10.3390\/ijgi9110632","type":"journal-article","created":{"date-parts":[[2020,10,26]],"date-time":"2020-10-26T10:38:35Z","timestamp":1603708715000},"page":"632","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":50,"title":["Research Progress and Development Trend of Social Media Big Data (SMBD): Knowledge Mapping Analysis Based on CiteSpace"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9055-6798","authenticated-orcid":false,"given":"Ziyi","family":"Wang","sequence":"first","affiliation":[{"name":"School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Debin","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ru","family":"Pang","sequence":"additional","affiliation":[{"name":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fan","family":"Xie","sequence":"additional","affiliation":[{"name":"Faculty of Urban Construction, Beijing University of Technology, Beijing 100124, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingxiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongqi","family":"Sun","sequence":"additional","affiliation":[{"name":"Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing 100101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,10,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Hansen, D.L., Shneiderman, B., and Smith, M.A. (2020). Twitter: Information flows, influencers, and organic communities. Analyzing Social Media Networks with NodeXL, Morgan Kaufmann.","DOI":"10.1016\/B978-0-12-817756-3.00011-X"},{"key":"ref_2","first-page":"417","article-title":"Social media big data analytics: A survey","volume":"101","author":"Abdul","year":"2018","journal-title":"Comput. Hum. Behav."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.indmarman.2019.04.005","article-title":"Role of big data and social media analytics for business to business sustainability: A participatory web context","volume":"86","author":"Sivarajah","year":"2020","journal-title":"Ind. Market. Manag."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ijinfomgt.2018.09.003","article-title":"Towards a big data framework for analyzing social media content","volume":"44","year":"2019","journal-title":"Int. J. Inform. Manag."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Yang, C.C., and Mao, W. (2013). Privacy-preserving social network integration, analysis, and mining. Intelligent Systems for Security Informatics, Academic Press.","DOI":"10.1016\/B978-0-12-404702-0.00003-3"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Gilbert, E., and Karahalios, K. (2009, January 4\u20139). Predicting Tie Strength with Social Media. Proceedings of the 27th International Conference on Human Factors in Computing Systems, Boston, MA, USA.","DOI":"10.1145\/1518701.1518736"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.is.2014.07.006","article-title":"The rise of \u201cbig data\u201d on cloud computing: Review and open research issues","volume":"47","author":"Hashem","year":"2015","journal-title":"Inform. Syst."},{"key":"ref_8","first-page":"429","article-title":"Computational analysis and understanding of natural languages: Principles, methods and applications","volume":"Volume 38","author":"Gudivada","year":"2018","journal-title":"Handbook of Statistics"},{"key":"ref_9","first-page":"270","article-title":"Integrating SysML into a Systems Development Environment","volume":"39","author":"Friedenthal","year":"2008","journal-title":"Pract. Guide SysML"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1016\/j.comnet.2017.06.013","article-title":"The role of big data analytics in Internet of Things","volume":"129","author":"Ahmed","year":"2017","journal-title":"Comput. Netw."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Akerkar, R. (2013). Big social data analysis. Big Data Computing, Chapman and Hall\/CRC.","DOI":"10.1201\/b16014"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1111\/hcre.12114","article-title":"Vectors into the future of mass and interpersonal communication research: Big data, social media, and computational social science","volume":"43","author":"Cappella","year":"2017","journal-title":"Hum. Commun. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2373","DOI":"10.1109\/ACCESS.2016.2607218","article-title":"Sentiment computing for the news event based on the Big Social Media Data","volume":"99","author":"Jiang","year":"2017","journal-title":"IEEE Access"},{"key":"ref_14","first-page":"1","article-title":"Integration of social media with healthcare big data for improved service delivery","volume":"20","author":"Sibulela","year":"2018","journal-title":"S. Afr. J. Ind. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1109\/TBDATA.2018.2824812","article-title":"On scalable and robust truth discovery in big data social media sensing applications","volume":"5","author":"Zhang","year":"2019","journal-title":"IEEE Trans. Big Data"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Han, X., Wang, J., and Zhang, M. (2020). Using social media to mine and analyze public opinion related to COVID-19 in China. Int. J. Env. Res. Pub. Health, 17.","DOI":"10.3390\/ijerph17082788"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"125702","DOI":"10.1109\/ACCESS.2020.3004933","article-title":"Risk Assessment of COVID-19 based on multisource data from a geographical viewpoint","volume":"8","author":"Zhang","year":"2020","journal-title":"IEEE Access"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1357","DOI":"10.1007\/s10796-018-9839-6","article-title":"Assimilation of big data innovation: Investigating the roles of IT, social media, and relational capital","volume":"21","author":"Bharati","year":"2019","journal-title":"Inform. Syst. Front."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"198","DOI":"10.3390\/horticulturae10030198","article-title":"Statistical analysis of WOS citation of journal \u2018Northern Horticulture\u2019","volume":"10","author":"Wang","year":"2016","journal-title":"North. Hortic."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"119908","DOI":"10.1016\/j.jclepro.2019.119908","article-title":"Trends in global research in forest carbon sequestration: A bibliometric analysis","volume":"252","author":"Huang","year":"2019","journal-title":"J. Clean. Prod."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/j.jclepro.2018.12.157","article-title":"Mapping the bike sharing research published from 2010 to 2018: A scientometric review","volume":"213","author":"Si","year":"2019","journal-title":"J. Clean. Prod."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1007\/s11192-014-1517-y","article-title":"Visualizing the intellectual structure and evolution of innovation systems research: A bibliometric analysis","volume":"103","author":"Liu","year":"2015","journal-title":"Scientometrics"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"16569","DOI":"10.1073\/pnas.0507655102","article-title":"An index to quantify an individual\u2019s scientific research output","volume":"102","author":"Hirsch","year":"2005","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1002\/asi.20317","article-title":"CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature","volume":"57","author":"Chen","year":"2006","journal-title":"J. Am. Soc. Inf. Sci. Technol."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Ullah, H., Wan, W., and Haidery, S.A. (2019). Analyzing the spatiotemporal patterns in green spaces for urban studies using location-based social media data. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8110506"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Ebrahimpour, Z., Wan, W.G., and Cervantes, O. (2019). Comparison of main approaches for extracting behavior features from crowd flow analysis. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8100440"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1911","DOI":"10.1007\/s10067-016-3513-5","article-title":"Public health awareness of autoimmune diseases after the death of a celebrity","volume":"36","author":"Bragazzi","year":"2017","journal-title":"Clin. Rheumatol."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Bragazzi, N.L., Alicino, C., and Trucchi, C. (2017). Global reaction to the recent outbreaks of Zika virus: Insights from a Big Data analysis. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0185263"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.neunet.2014.05.017","article-title":"Exploring personalized searches using tag-based user profiles and resource profiles in folksonomy","volume":"58","author":"Cai","year":"2014","journal-title":"Neural. Netw."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.neunet.2014.05.009","article-title":"Community-aware user profile enrichment in folksonomy","volume":"58","author":"Xie","year":"2014","journal-title":"Neural. Netw."},{"key":"ref_31","first-page":"1","article-title":"Twitter mood predicts the stock market","volume":"2","author":"Bollen","year":"2010","journal-title":"J. Comput. Sci.-Neth."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.ins.2014.01.015","article-title":"Data-intensive applications, challenges, techniques and technologies: A survey on Big Data","volume":"275","author":"Chen","year":"2014","journal-title":"Inform. Sci."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1203","DOI":"10.1126\/science.1248506","article-title":"The parable of google flu: Traps in big data analysis","volume":"343","author":"Lazer","year":"2014","journal-title":"Science"},{"key":"ref_34","first-page":"662","article-title":"Critical questions for big data","volume":"15","author":"Boyd","year":"2012","journal-title":"Nform. Commun. Soc."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1012-U4","DOI":"10.1038\/nature07634","article-title":"Detecting influenza epidemics using search engine query data","volume":"457","author":"Ginsberg","year":"2009","journal-title":"Nature"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Manovich, L. (2011, July 15). Trending: The Promises and the Challenges of Big Social Data. In Debates in the Digital Humanities. Available online: http:\/\/www.manovich.net\/DOCS\/Manovich_trending_paper.pdf.","DOI":"10.5749\/minnesota\/9780816677948.003.0047"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.inffus.2015.08.005","article-title":"Social big data: Recent achievements and new challenges","volume":"28","author":"Jung","year":"2016","journal-title":"Inform. Fusion"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1007\/s11036-013-0489-0","article-title":"Big data: A survey","volume":"19","author":"Chen","year":"2014","journal-title":"Mob. Netw. Appl."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"122679","DOI":"10.1016\/j.jclepro.2020.122679","article-title":"A bibliometric analysis of corporate social responsibility in sustainable development","volume":"272","author":"Ye","year":"2020","journal-title":"J. Clean. Prod."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"101360","DOI":"10.1016\/j.ijdrr.2019.101360","article-title":"Determining disaster severity through social media analysis: Testing the methodology with South East Queensland Flood tweets","volume":"42","author":"Kankanamge","year":"2020","journal-title":"Int. J. Disast. Risk Reduct."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"106150","DOI":"10.1016\/j.addbeh.2019.106150","article-title":"The interplay between neuroticism, extraversion, and social media addiction in young adult Facebook users: Testing the mediating role of online activity using objective data","volume":"102","author":"Marengo","year":"2019","journal-title":"Addict. Behav."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Seo, E.J., Park, J.W., and Choi, Y.J. (2020). The effect of social media usage characteristics on e-WOM, trust, and brand equity: Focusing on users of airline social media. Sustainability, 12.","DOI":"10.3390\/su12041691"},{"key":"ref_43","first-page":"9","article-title":"The perils and promises of big data research in information systems","volume":"21","author":"Grover","year":"2020","journal-title":"J. Assoc. Inf. Syst."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1186\/s12942-020-00214-4","article-title":"Spatio-temporal distribution of negative emotions on Twitter during floods in Chennai, India, in 2015: A post hoc analysis","volume":"19","author":"Karmegam","year":"2020","journal-title":"Int. J. Health Geogr."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"102619","DOI":"10.1016\/j.trc.2020.102619","article-title":"Evaluation and prediction of transportation resilience under extreme weather events: A diffusion graph convolutional approach","volume":"115","author":"Wang","year":"2020","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"101860","DOI":"10.1016\/j.tre.2020.101860","article-title":"When blockchain meets social-media: Will the result benefit social media analytics for supply chain operations management?","volume":"135","year":"2020","journal-title":"Transp. Res. Part E Logist. Transp. Rev."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"4610","DOI":"10.1080\/00207543.2020.1761565","article-title":"The potential of emergent disruptive technologies for humanitarian supply chains: The integration of blockchain, artificial intelligence and 3D printing","volume":"58","author":"Chowdhury","year":"2020","journal-title":"Int. J. Prod. Res."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/s00778-019-00569-6","article-title":"Microblogs data management: A survey","volume":"29","author":"Magdy","year":"2020","journal-title":"VLDB J."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"3629","DOI":"10.1109\/ACCESS.2019.2923270","article-title":"Blending big data analytics: Review on challenges and a recent study","volume":"8","author":"Amalina","year":"2019","journal-title":"IEEE Access"},{"key":"ref_50","first-page":"288","article-title":"Showing the essential science structure of a scientific domain and its evolution","volume":"9","year":"2010","journal-title":"Inform. Visual."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Liu, Q., Ullah, H., and Wan, W. (2020). Categorization of green spaces for a sustainable environment and smart city architecture by utilizing big data. Electronics, 9.","DOI":"10.3390\/electronics9061028"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1007\/s13349-020-00386-4","article-title":"A big data analytics strategy for scalable urban infrastructure condition assessment using semi-supervised multi-transform self-training","volume":"10","author":"Alipour","year":"2020","journal-title":"J. Civ. Struct. Health"},{"key":"ref_53","first-page":"1","article-title":"If you build it, they will come: Unintended future uses of organised health data collections","volume":"17","author":"Christofides","year":"2016","journal-title":"BMC Med. Ethics"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1023\/A:1024940629314","article-title":"Bursty and hierarchical structure in streams","volume":"7","author":"Kleinberg","year":"2003","journal-title":"Data Min. Knowl. Disc."},{"key":"ref_55","first-page":"3111","article-title":"Distributed representations of words and phrases and their compositionality","volume":"26","author":"Mikolov","year":"2013","journal-title":"Neural Inf. Process. Syst."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.neunet.2014.09.003","article-title":"Deep learning in neural networks: An overview","volume":"61","author":"Schmidhuber","year":"2015","journal-title":"Neural. Netw."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.ijinfomgt.2014.10.007","article-title":"Beyond the hype: Big data concepts, methods, and analytics","volume":"35","author":"Gandomi","year":"2015","journal-title":"Int. J. Inform. Manag."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1145\/2818717","article-title":"The rise of social bots","volume":"59","author":"Ferrara","year":"2014","journal-title":"Commun. Acm."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"556","DOI":"10.1016\/j.comnet.2012.06.006","article-title":"Design and analysis of a social botnet","volume":"57","author":"Boshmaf","year":"2013","journal-title":"Comput. Netw."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Cao, Q., Yang, X., and Yu, J. (2014, January 3\u20137). Uncovering large groups of active malicious accounts in online social networks. Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security (CCS 2014), Scottsdale, AZ, USA.","DOI":"10.1145\/2660267.2660269"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1177\/0956797614557867","article-title":"Psychological language on twitter predicts county-level heart disease mortality","volume":"26","author":"Eichstaedt","year":"2015","journal-title":"Psychol. Sci."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"e1500779","DOI":"10.1126\/sciadv.1500779","article-title":"Rapid assessment of disaster damage using social media activity","volume":"2","author":"Kryvasheyeu","year":"2016","journal-title":"Sci. Adv."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/disa.12092","article-title":"Social media and disasters: A functional framework for social media use in disaster planning, response, and research","volume":"39","author":"Houston","year":"2015","journal-title":"Disasters"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"667","DOI":"10.1080\/13658816.2014.996567","article-title":"A geographic approach for combining social media and authoritative data towards identifying useful information for disaster management","volume":"29","author":"Albuquerque","year":"2015","journal-title":"Int. J. Geogr. Inf. Sci."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/11\/632\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:28:23Z","timestamp":1760178503000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/11\/632"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,26]]},"references-count":64,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2020,11]]}},"alternative-id":["ijgi9110632"],"URL":"https:\/\/doi.org\/10.3390\/ijgi9110632","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,26]]}}}