{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T23:04:39Z","timestamp":1773702279710,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2017,8,5]],"date-time":"2017-08-05T00:00:00Z","timestamp":1501891200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National; Science Center, Poland","award":["UMO-2015\/17\/D\/HS4\/00272"],"award-info":[{"award-number":["UMO-2015\/17\/D\/HS4\/00272"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Social media is a rich source of spatial data but it has also many flaws and well-known limitations, especially in regard to representation and representativeness, since very little is known about the demographics of the user population. At the same time, the use of locational services, is in fact, dependent on those characteristics. We address this gap in knowledge by exploring divides between Twitter users, based on the spatial and temporal distribution of the content they produce. We chose five cities and data from 2015 to represent different socio-spatial contexts. Users were classified according to spatial and non-spatial measures: home range estimation; standard distance; nearest neighbor index, and; proposed localness index. There are distinct groups of geosocial media producers, which suggests that such datasets cannot be treated as uniform representations. We found a positive correlation between spatial behavior and posting activity. It is suggested that there are universal patterns of behavior that are conditioned by software services\u2014the example of Foucauldian \u201ctechnologies of self\u201d. They can also represent the dominance of the most prolific users over the whole data stream. Results are discussed in the context of the importance and role of user location in social media.<\/jats:p>","DOI":"10.3390\/ijgi6080236","type":"journal-article","created":{"date-parts":[[2017,8,9]],"date-time":"2017-08-09T06:32:14Z","timestamp":1502260334000},"page":"236","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Spatial Characteristics of Twitter Users\u2014Toward the Understanding of Geosocial Media Production"],"prefix":"10.3390","volume":"6","author":[{"given":"Michal","family":"Rzeszewski","sequence":"first","affiliation":[{"name":"Faculty of Geographical and Geological Sciences, Adam Mickiewicz University, Krygowskiego 10, 61-680 Poznan, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lukasz","family":"Beluch","sequence":"additional","affiliation":[{"name":"Institute of Geography and Spatial Management, Jagiellonian University, 30-387 Cracow, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,8,5]]},"reference":[{"key":"ref_1","unstructured":"Mayer-Sch\u00f6nberger, V., and Cukier, K. (2013). Big Data: A Revolution that Will Transform How We Live, Work, And Think, Houghton Mifflin Harcourt."},{"key":"ref_2","unstructured":"Kitchin, R. (2014). The Data Revolution, SAGE Publications Ltd."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1177\/2043820613513388","article-title":"Big data and human geography: Opportunities, challenges and risks","volume":"3","author":"Kitchin","year":"2013","journal-title":"Dialogues Hum. Geogr."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1177\/2043820613515379","article-title":"Big data and the fabric of human geography","volume":"3","year":"2013","journal-title":"Dialogues Hum. Geogr."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1177\/2043820613514321","article-title":"Rethinking empirical social sciences","volume":"3","author":"Ruppert","year":"2013","journal-title":"Dialogues Hum. Geogr."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Housley, W., Procter, R., Edwards, A., Burnap, P., Williams, M., Sloan, L., Rana, O., Morgan, J., Voss, A., and Greenhill, A. (2014). Big and broad social data and the sociological imagination: A collaborative response. Big Data Soc., 1.","DOI":"10.1177\/2053951714545135"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Asur, S., and Huberman, B.A. (September, January 31). Predicting the future with social media. Proceedings of the 2010 IEEE\/WIC\/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), Toronto, ON, Canada.","DOI":"10.1109\/WI-IAT.2010.63"},{"key":"ref_8","first-page":"1","article-title":"From tweets to polls: Linking text sentiment to public opinion time series","volume":"11","author":"Balasubramanyan","year":"2010","journal-title":"ICWSM"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Achrekar, H., Gandhe, A., Lazarus, R., Yu, S.-H., and Liu, B. (2011, January 10\u201315). Predicting flu trends using twitter data. Proceedings of the 2011 IEEE Conference on the Computer Communications Workshops (INFOCOM WKSHPS), Shanghai, China.","DOI":"10.1109\/INFCOMW.2011.5928903"},{"key":"ref_10","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":"Herfort","year":"2015","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Gordon, E., and de Souza e Silva, A. (2011). Net Locality: Why Location Matters in a Networked World, Wiley-Blackwell.","DOI":"10.1002\/9781444340679"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1737","DOI":"10.1080\/13658816.2011.604636","article-title":"The convergence of GIS and social media: Challenges for GIScience","volume":"25","author":"Sui","year":"2011","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1177\/0894439309332299","article-title":"Mapping for the Masses","volume":"27","author":"Batty","year":"2009","journal-title":"Soc. Sci. Comput. Rev."},{"key":"ref_14","unstructured":"Morstatter, F., Pfeffer, J., Liu, H., and Carley, K.M. (2013, January 8\u201311). Is the Sample Good Enough? Comparing Data from Twitter\u2019s Streaming API with Twitter\u2019s Firehose. Proceedings of the 7th International AAAI Conference on Weblogs and Social Media, ICWSM 2013, Cambridge, MA, USA."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Sloan, L., and Morgan, J. (2015). Who Tweets with Their Location? Understanding the Relationship between Demographic Characteristics and the Use of Geoservices and Geotagging on Twitter. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0142209"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"662","DOI":"10.1080\/1369118X.2012.678878","article-title":"Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon","volume":"15","author":"Boyd","year":"2012","journal-title":"Inf. Commun. Soc."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1177\/2043820613513392","article-title":"The quality of big (geo) data","volume":"3","author":"Goodchild","year":"2013","journal-title":"Dialogues Hum. Geogr."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1177\/2043820613514323","article-title":"Big data, little history","volume":"3","author":"Barnes","year":"2013","journal-title":"Dialogues Hum. Geogr."},{"key":"ref_19","first-page":"21","article-title":"Exploring place through user-generated content: Using Flickr tags to describe city cores","volume":"2010","author":"Hollenstein","year":"2010","journal-title":"J. Spat. Inf. Sci."},{"key":"ref_20","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. Manag."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Frias-Martinez, V., Soto, V., Hohwald, H., and Frias-Martinez, E. (2012, January 3\u20135). Characterizing urban landscapes using geolocated tweets. Proceedings of the 2012 International Conference on Privacy, Security, Risk and Trust (PASSAT) and 2012 International Confernece on Social Computing (SocialCom), Amsterdam, The Netherlands.","DOI":"10.1109\/SocialCom-PASSAT.2012.19"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1080\/15230406.2014.890072","article-title":"Geo-located Twitter as proxy for global mobility patterns","volume":"41","author":"Hawelka","year":"2014","journal-title":"Cartogr. Geogr. Inf. Sci."},{"key":"ref_23","first-page":"525","article-title":"Uncovering latent mobility patterns from twitter during mass events","volume":"1","author":"Steiger","year":"2015","journal-title":"GI Forum"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Li, Y., Li, Q., and Shan, J. (2017). Discover Patterns and Mobility of Twitter Users\u2014A Study of Four US College Cities. ISPRS Int. J. Geo-Inf., 6.","DOI":"10.3390\/ijgi6020042"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1007\/s10708-011-9438-2","article-title":"Harvesting ambient geospatial information from social media feeds","volume":"78","author":"Stefanidis","year":"2013","journal-title":"GeoJournal"},{"key":"ref_26","first-page":"5","article-title":"Understanding the Demographics of Twitter Users","volume":"11","author":"Mislove","year":"2011","journal-title":"ICWSM"},{"key":"ref_27","unstructured":"Kulshrestha, J., Kooti, F., Nikravesh, A., and Gummadi, P.K. (2012, January 4\u20138). Geographic Dissection of the Twitter Network. Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media, Dublin, Ireland."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Brus, J., Vondrakova, A., and Vozenilek, V. (2015). Demography of Twitter Users in the City of London: An Exploratory Spatial Data Analysis Approach. Modern Trends in Cartography, Springer.","DOI":"10.1007\/978-3-319-07926-4"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1068\/a130122p","article-title":"The geotemporal demographics of Twitter usage","volume":"47","author":"Longley","year":"2015","journal-title":"Environ. Plan. A"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1080\/00330124.2014.907699","article-title":"Where in the world are you? Geolocation and language identification in Twitter","volume":"66","author":"Graham","year":"2014","journal-title":"Prof. Geogr."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1080\/15230406.2015.1088801","article-title":"Bumps and bruises in the digital skins of cities: Unevenly distributed user-generated content across US urban areas","volume":"43","author":"Robertson","year":"2016","journal-title":"Cartogr. Geogr. Inf. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Kitchin, R., and Dodge, M. (2011). Code\/Space: Software and Everyday Life, MIT Press. Software Studies.","DOI":"10.7551\/mitpress\/9780262042482.001.0001"},{"key":"ref_33","unstructured":"Foucault, M., Martin, L.H., Gutman, H., and Hutton, P.H. (1988). Technologies of the Self: A Seminar with Michel Foucault, University of Massachusetts Press."},{"key":"ref_34","unstructured":"Leighton, E. (2015). Locative Social Media, Palgrave Mcmilan."},{"key":"ref_35","first-page":"7","article-title":"Twitter Jako Zr\u00f3dlo Informacji Geograficznej\/the Twitter as a Source of Geographic Information","volume":"7","author":"Beluch","year":"2015","journal-title":"Pr. Geogr."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Zafarani, R., Abbasi, M.A., and Liu, H. (2014). Social Media Mining: An Introduction, Cambridge University Press.","DOI":"10.1017\/CBO9781139088510"},{"key":"ref_37","unstructured":"Bui, R., Buliung, R.N., Remmel, T.K., and Buliung, M.R.N. (2012, December 01). Available online: https:\/\/cran.r-project.org\/web\/packages\/aspace\/index.html."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1016\/j.ecolmodel.2006.03.017","article-title":"The package \u201cadehabitat\u201d for the R software: A tool for the analysis of space and habitat use by animals","volume":"197","author":"Calenge","year":"2006","journal-title":"Ecol. Model."},{"key":"ref_39","unstructured":"Levine, N. (2004). CrimeStat III."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1068\/b2691","article-title":"Segueways into cyberspace: Multiple geographies of the digital divide","volume":"28","author":"Warf","year":"2001","journal-title":"Environ. Plan. B Plan. Des."},{"key":"ref_41","first-page":"173","article-title":"Where Freedom Matters: Internet Adoption among the Former Socialist Countries","volume":"67","author":"Dimitrova","year":"2005","journal-title":"Int. Commun. Gaz."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1177\/146499341001100303","article-title":"Time machines and virtual portals the spatialities of the digital divide","volume":"11","author":"Graham","year":"2011","journal-title":"Prog. Dev. Stud."},{"key":"ref_43","first-page":"5","article-title":"The Tweets They Are a-Changin: Evolution of Twitter Users and Behavior","volume":"30","author":"Liu","year":"2014","journal-title":"ICWSM"},{"key":"ref_44","unstructured":"Calenge, C. (2011). Home Range Estimation in R: The Adehabitathr Package, Office National de la Classe et de la Faune Sauvage."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1080\/10630732.2011.578412","article-title":"Visualizing global cyberscapes: Mapping user-generated placemarks","volume":"18","author":"Graham","year":"2011","journal-title":"J. Urban Technol."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Welles, B.F. (2014). On minorities and outliers: The case for making Big Data small. Big Data Soc., 1.","DOI":"10.1177\/2053951714540613"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Agresti, A. (2007). An Introduction to Categorical Data Analysis, Wiley-Interscience. [2nd ed.].","DOI":"10.1002\/0470114754"},{"key":"ref_48","unstructured":"Cohen, J. (1988). Statistical Power Analysis for the Social Sciences, Erlbaum. [2nd ed.]."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1111\/geoj.12009","article-title":"Geography\/internet: Ethereal alternate dimensions of cyberspace or grounded augmented realities?","volume":"179","author":"Graham","year":"2013","journal-title":"Geogr. J."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Yin, J., Gao, Y., Du, Z., and Wang, S. (2016). Exploring Multi-Scale Spatiotemporal Twitter User Mobility Patterns with a Visual-Analytics Approach. ISPRS Int. J. Geo-Inf., 5.","DOI":"10.3390\/ijgi5100187"},{"key":"ref_51","first-page":"37","article-title":"Geocoding location expressions in Twitter messages: A preference learning method","volume":"2014","author":"Zhang","year":"2014","journal-title":"J. Spat. Inf. Sci."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Rzeszewski, M. (2016). Geosocial capta in geographical research\u2014A critical analysis. Cartogr. Geogr. Inf. Sci., 1\u201313.","DOI":"10.1080\/15230406.2016.1229221"}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/6\/8\/236\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:41:33Z","timestamp":1760208093000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/6\/8\/236"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,8,5]]},"references-count":52,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2017,8]]}},"alternative-id":["ijgi6080236"],"URL":"https:\/\/doi.org\/10.3390\/ijgi6080236","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,8,5]]}}}