{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:34:28Z","timestamp":1760243668873,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2022,10,7]],"date-time":"2022-10-07T00:00:00Z","timestamp":1665100800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>In our era of big data and information overload, content consumers utilise a variety of sources to meet their data and informational needs for the purpose of acquiring an in-depth perspective on a subject, as each source is focused on specific aspects. The same principle applies to the online social networks (OSNs), as usually, the end-users maintain accounts in multiple OSNs so as to acquire a complete social networking experience, since each OSN has a different philosophy in terms of its services, content, and interaction. Contrary to the current literature, we examine the users\u2019 behavioural and disseminated content patterns under the assumption that accounts maintained by users in multiple OSNs are not regarded as distinct accounts, but rather as the same individual with multiple social instances. Our social analysis, enriched with information about the users\u2019 social influences, revealed behavioural patterns depending on the examined OSN, its social entities, and the users\u2019 exerted influence. Finally, we ranked the examined OSNs based on three types of social characteristics, revealing correlations between the users\u2019 behavioural and content patterns, social influences, social entities, and the OSNs themselves.<\/jats:p>","DOI":"10.3390\/computers11100149","type":"journal-article","created":{"date-parts":[[2022,10,8]],"date-time":"2022-10-08T01:52:21Z","timestamp":1665193941000},"page":"149","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["User Analytics in Online Social Networks: Evolving from Social Instances to Social Individuals"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8504-3234","authenticated-orcid":false,"given":"Gerasimos","family":"Razis","sequence":"first","affiliation":[{"name":"Computer Science and Biomedical Informatics Department, University of Thessaly, 35131 Lamia, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stylianos","family":"Georgilas","sequence":"additional","affiliation":[{"name":"Computer Science and Biomedical Informatics Department, University of Thessaly, 35131 Lamia, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giannis","family":"Haralabopoulos","sequence":"additional","affiliation":[{"name":"Henley Business School, University of Reading, Reading RG6 6UD, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ioannis","family":"Anagnostopoulos","sequence":"additional","affiliation":[{"name":"Computer Science and Biomedical Informatics Department, University of Thessaly, 35131 Lamia, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1504\/IJWBC.2006.010305","article-title":"SIOC: An approach to connect web-based communities","volume":"2","author":"Breslin","year":"2006","journal-title":"Int. J. Web Based Communities IJWBC"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Li, G., Chu, L., Wang, S., Zhang, W., and Huang, Q. (2013, January 15\u201319). Cross-media topic detection: A multi-modality fusion framework. Proceedings of the 2013 IEEE International Conference on Multimedia and Expo (ICME), San Jose, CA, USA.","DOI":"10.1109\/ICME.2013.6607487"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"32166","DOI":"10.1109\/ACCESS.2019.2899989","article-title":"A Unified Semantic Model for Cross-Media Events Analysis in Online Social Networks","volume":"7","author":"Fang","year":"2019","journal-title":"IEEE Access"},{"key":"ref_4","unstructured":"Mander, J., Kavanagh, D., and Buckle, C. (2022, August 20). GlobalWebIndex\u2019s Flagship Report on the Latest Trends in Social Media. GlobalWebIndex. Available online: https:\/\/www.gwi.com\/hubfs\/Downloads\/2019%20Q2-Q3%20Social%20Report.pdf."},{"key":"ref_5","unstructured":"Golbeck, J., and Rothstein, M. (2008, January 13\u201317). Linking Social Networks on the Web with FOAF: A Semantic Web Case. Proceedings of the 23rd AAAI Conference on Artificial Intelligence, AAAI Press, Chicago, IL, USA."},{"key":"ref_6","unstructured":"Rowe, M. (2009, January 20). Interlinking distributed social graphs. Proceedings of the WWW2009 Workshop on Linked Data on the Web, LDOW 2009, Madrid, Spain."},{"key":"ref_7","first-page":"424","article-title":"Matching User Profiles Across Social Networks","volume":"Volume 8484","author":"Jarke","year":"2014","journal-title":"Advanced Information Systems Engineering, Proceedings of the CAiSE 2014, Thessaloniki, Greece, 16\u201320 June 2014"},{"key":"ref_8","first-page":"275","article-title":"Large-Scale Parallel Matching of Social Network Profiles","volume":"Volume 542","author":"Khachay","year":"2015","journal-title":"Analysis of Images, Social Networks and Texts, Proceedings of the 4th International Conference, AIST 2015, Yekaterinburg, Russia, 9\u201311 April 2015"},{"key":"ref_9","first-page":"54","article-title":"Profile Matching Across Online Social Networks","volume":"Volume 12282","author":"Meng","year":"2020","journal-title":"Information and Communications Security, Proceedings of the 22nd International Conference, ICICS 2020, Copenhagen, Denmark, 24\u201326 August 2020"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Diao, M., Zhang, Z., Su, S., Gao, S., and Cao, H. (2020, January 19\u201323). UPON: User Profile Transferring across Networks. Proceedings of the 29th ACM International Conference on Information & Knowledge Management (CIKM \u201820), Virtual.","DOI":"10.1145\/3340531.3411964"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Malhotra, A., Totti, L., Meira, W., Kumaraguru, P., and Almeida, V. (2012, January 26\u201329). Studying User Footprints in Different Online Social Networks. In Proceeding of the 2012 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining, Istanbul, Turkey.","DOI":"10.1109\/ASONAM.2012.184"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Moshkin, V. (2020, January 7\u20139). The approach to building a graph knowledge base using social media data. Proceedings of the 2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT), Tashkent, Uzbekistan.","DOI":"10.1109\/AICT50176.2020.9368794"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"4297","DOI":"10.1007\/s10115-020-01498-5","article-title":"SNOWL model: Social networks unification-based semantic data integration","volume":"62","author":"Hiba","year":"2020","journal-title":"Knowl. Inf. Syst."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"702","DOI":"10.1108\/AJIM-04-2017-0098","article-title":"Gender and image sharing on Facebook, Twitter, Instagram, Snapchat and WhatsApp in the UK: Hobbying alone or filtering for friends?","volume":"69","author":"Thelwall","year":"2017","journal-title":"Aslib J. Inf. Manag."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.chb.2017.02.041","article-title":"Uses and gratifications of social networking sites for bridging and bonding social capital: A comparison of Facebook, Twitter, Instagram, and Snapchat","volume":"72","author":"Phua","year":"2017","journal-title":"Comput. Hum. Behav."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.chb.2018.04.041","article-title":"Why do college students prefer Facebook, Twitter, or Instagram? Site affordances, tensions between privacy and self-expression, and implications for social capital","volume":"86","author":"Manago","year":"2018","journal-title":"Comput. Hum. Behav."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.jretconser.2019.03.012","article-title":"Measuring social media influencer index- insights from facebook, Twitter and Instagram","volume":"49","author":"Arora","year":"2019","journal-title":"J. Retail. Consum. Serv."},{"key":"ref_18","first-page":"136","article-title":"The effects of social media usage on loneliness and well-being: Analysing friendship connections of Facebook, Twitter and Instagram","volume":"49","author":"Ye","year":"2021","journal-title":"Inf. Discov. Deliv."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Delle, F.A., Clayton, R.B., Jordan Jackson, F.F., and Lee, J. (Psychol. Pop. Media, 2022). Facebook, Twitter, and Instagram: Simultaneously examining the association between three social networking sites and relationship stress and satisfaction, Psychol. Pop. Media, online ahead of print.","DOI":"10.1037\/ppm0000415"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1080\/10888691.2018.1440233","article-title":"Interactants and activities on Facebook, Instagram, and Twitter: Associations between social media use and social adjustment to college","volume":"24","author":"Lee","year":"2020","journal-title":"Appl. Dev. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Boulianne, S., and Larsson, A.O. (New Media Soc., 2021). Engagement with candidate posts on Twitter, Instagram, and Facebook during the 2019 election, New Media Soc., online ahead of print.","DOI":"10.1177\/14614448211009504"},{"key":"ref_22","first-page":"184","article-title":"InfluenceTracker: Rating the impact of a Twitter account","volume":"Volume 437","author":"Iliadis","year":"2014","journal-title":"Artificial Intelligence Applications and Innovations, Proceedings of the Artificial Intelligence Applications and Innovations Workshops (AIAI 2014), Rhodes, Greece, 19\u201321 September 2014"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Razis, G., and Anagnostopoulos, I. (2014, January 6\u20137). Semantifying Twitter: The Influence Tracker Ontology. Proceedings of the 9th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP), Corfu, Greece.","DOI":"10.1109\/SMAP.2014.23"},{"key":"ref_24","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_25","doi-asserted-by":"crossref","unstructured":"Razis, G., Theofilou, G., and Anagnostopoulos, I. (2021). Latent Twitter Image Information for Social Analytics. 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