Change search
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
Hashtags and followers An experimental study of the online social network Twitter
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Twitter Inc, San Francisco, CA USA..
2016 (English)In: SOCIAL NETWORK ANALYSIS AND MINING, ISSN 1869-5450, Vol. 6, no 1, UNSP 12Article in journal (Refereed) Published
Abstract [en]

We have conducted an analysis of data from 502,891 Twitter users and focused on investigating the potential correlation between hashtags and the increase of followers to determine whether the addition of hashtags to tweets produces new followers. We have designed an experiment with two groups of users: one tweeting with random hashtags and one tweeting without hashtags. The results showed that there is a correlation between hashtags and followers: on average, users tweeting with hashtags increased their followers by 2.88, while users tweeting without hashtags increased 0.88 followers. We present a simple, reproducible approach to extract and analyze Twitter user data for this and similar purposes.

Place, publisher, year, edition, pages
Springer, 2016. Vol. 6, no 1, UNSP 12
Keyword [en]
Experimental study, Correlational analysis, Hashtags, Followers
National Category
Media and Communication Technology Other Computer and Information Science
Identifiers
URN: urn:nbn:se:bth-13048DOI: 10.1007/s13278-016-0320-6ISI: 000381220500012OAI: oai:DiVA.org:bth-13048DiVA: diva2:1006904
Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2016-11-10Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Martin, Eva GarciaLavesson, Niklas
By organisation
Department of Computer Science and Engineering
Media and Communication TechnologyOther Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 36 hits
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