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A Machine Learning Approach Towards Detecting Extreme Adopters in Digital Communities
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. FOI, Stockholm, Sweden..
FOI, Stockholm, Sweden..
2017 (English)In: 2017 28th International Workshop on Database and Expert Systems Applications (DEXA) / [ed] Tjoa, AM Wagner, RR, IEEE, 2017, p. 1-5Conference paper, Published paper (Other academic)
Abstract [en]

In this study we try to identify extreme adopters on a discussion forum using machine learning. An extreme adopter is a user that has adopted a high level of a community-specific jargon and therefore can be seen as a user that has a high degree of identification with the community. The dataset that we consider consists of a Swedish xenophobic discussion forum where we use a machine learning approach to identify extreme adopters using a number of linguistic features that are independent on the dataset and the community. The results indicates that it is possible to separate these extreme adopters from the rest of the discussants on the discussion forum with more than 80% accuracy. Since the linguistic features that we use are highly domain independent, the results indicates that there is a possibility to use this kind of techniques to identify extreme adopters within other communities as well.

Place, publisher, year, edition, pages
IEEE, 2017. p. 1-5
Series
International Workshop on Database and Expert Systems Applications-DEXA, ISSN 1529-4188
Keywords [en]
Discussion forums, Support vector machines, Pragmatics, Manuals, Radio frequency, Electronic mail, Social network services
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:uu:diva-351187DOI: 10.1109/DEXA.2017.17ISI: 000426078300001ISBN: 978-1-5386-1051-0 (electronic)OAI: oai:DiVA.org:uu-351187DiVA, id: diva2:1209677
Conference
28th International Workshop on Database and Expert Systems Applications (DEXA), AUG 28-31, 2017, Lyon3 Univ, Lyon, FRANCE
Available from: 2018-05-23 Created: 2018-05-23 Last updated: 2018-05-23Bibliographically approved

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Shrestha, AmendraKaati, Lisa

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf