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Self-Similarity of Twitter Users
Linnaeus University, Sweden; University of Eastern Finland, Finland.ORCID iD: 0000-0002-3000-0381
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Linnaeus University, Sweden. (iVis, INV)ORCID iD: 0000-0002-1907-7820
Linnaeus University, Sweden; University of Eastern Finland, Finland.ORCID iD: 0000-0003-3123-6932
University of Eastern Finland, Finland.ORCID iD: 0000-0002-9554-2827
2021 (English)In: Proceedings of the 2021 Swedish Workshop on Data Science (SweDS) / [ed] Rafael M. Martins, Morgan Ericsson, Danny Weyns, Kostiantyn Kucher, IEEE , 2021Conference paper, Published paper (Refereed)
Abstract [en]

Earlier studies have established that the (perceived) similarity of users is highly subjective and reflects more on how people respect/admire others rather than their characteristics or behavioral similarities. We study this phenomenon among Twitter users, and while confirm that it is indeed the case, we further explore the components of similarity by investigating it using data from three categories (interactions between egos and alters, profile-based activity history, and linguistic content in the messages). We use interactions as estimation for admiration and observe that it has more impact and a higher correlation to the perceived similarity than other objective measures, including similarity based on user profiles and their use of hashtags.

Place, publisher, year, edition, pages
IEEE , 2021.
Keywords [en]
social network analysis, ego network, user similarity, users interactions, activity history
National Category
Computer Sciences Languages and Literature
Research subject
Computer and Information Sciences Computer Science, Computer Science; Humanities, English
Identifiers
URN: urn:nbn:se:liu:diva-181837DOI: 10.1109/SweDS53855.2021.9638288ISI: 000833296400007ISBN: 9781665418300 (electronic)OAI: oai:DiVA.org:liu-181837DiVA, id: diva2:1620072
Conference
2021 Swedish Workshop on Data Science (SweDS), Växjö, Sweden, December 2-3, 2021
Projects
DISA
Note

Funding: Center for Data Intensive Sciences and Application (DISA) at Linnaeus University

Available from: 2021-12-14 Created: 2021-12-14 Last updated: 2022-08-29Bibliographically approved

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Fatemi, MasoudKucher, KostiantynLaitinen, Mikko

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
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  • en-US
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  • Other locale
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Output format
  • html
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