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Analyzing temporal networks in social media
Umeå University, Faculty of Science and Technology, Department of Physics. Department of Energy Science, Sungkyunkwan University Suwon, South Korea. (IceLab)ORCID iD: 0000-0003-2156-1096
2014 (English)In: Proceedings of the IEEE, ISSN 0018-9219, E-ISSN 1558-2256, Vol. 102, no 12, 1922-1933 p.Article, review/survey (Refereed) Published
Abstract [en]

Many types of social media metadata come in forms of temporal networks, networks where we have information about not only who is in contact with whom but also when contacts happen. In this paper, we review methods to analyze temporal networks developed in the last few years applied to social media data. These methods seek to identify important spreaders and, in more generality, how the temporal and topological structure of interaction affects spreading processes.

Place, publisher, year, edition, pages
2014. Vol. 102, no 12, 1922-1933 p.
Keyword [en]
network analysis, social network services, temporal networks
National Category
Information Systems
Identifiers
URN: urn:nbn:se:umu:diva-96754DOI: 10.1109/JPROC.2014.2361326ISI: 000345524100007Scopus ID: 2-s2.0-84914118377OAI: oai:DiVA.org:umu-96754DiVA: diva2:767598
Funder
Swedish Research Council
Note

This paper reviews methods for analyzing recently temporal networks applied to socialmedia data.

Available from: 2014-12-02 Created: 2014-12-02 Last updated: 2017-12-05Bibliographically approved

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Holme, Petter

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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