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Developing a rule-based method for identifying researchers on Twitter: The case of vaccine discussions
University of Borås, Faculty of Librarianship, Information, Education and IT.ORCID iD: 0000-0003-4187-7004
2019 (English)In: 17th International Conference on Scientometrics and Informetrics, ISSI 2019 - Proceedings Volume 2, 2019, Rom, 2019, p. 2618-2619Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

This study seeks to develop a method for identifying the occurrences and proportions of researchers, media and other professionals active in Twitter discussions. As a case example, an anonymised dataset from Twitter vaccine discussions is used. The study proposes a method of using keywords as strings within lists to identify classes from user biographies. This provides a way to apply multiple classification principles to a set of Twitter biographies using semantic rules through the Python programming language.

Place, publisher, year, edition, pages
Rom, 2019. p. 2618-2619
National Category
Social Sciences Information Studies Language Technology (Computational Linguistics)
Research subject
Library and Information Science
Identifiers
URN: urn:nbn:se:hb:diva-21917OAI: oai:DiVA.org:hb-21917DiVA, id: diva2:1367435
Conference
17th International Conference on Scientometrics and Informetrics, ISSI 2019; Sapienza University of Rome; Italy; 2-5 September, 2019.
Projects
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 770531Available from: 2019-11-04 Created: 2019-11-04 Last updated: 2019-11-05Bibliographically approved

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Ekström, Björn

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • 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