Developing a rule-based method for identifying researchers on Twitter: The case of vaccine discussions

SND-ID: SND 1117

Description Data and documentation

Creator/Principal investigator(s)

Björn Ekström


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. The script used for the study is here deposited.



Research principal, contributors, and funding

Research principal

University of Borås

Responsible department/unit

University of Borås


  • Funding agency: Horizon 2020
  • Funding agency�s reference number: 770531
Protection and ethical review


Twitter users

Time Method

Sampling procedure


Time period(s) investigated


Geographic coverage
Topic and keywords

Subject area

Higher and further education, Information society, Language and linguistics (CESSDA Topic Classification)
Language Technology (Computational Linguistics), Social Sciences, Information Studies (The Swedish standard of fields of research 2011)


Ekström, B. (2019). Developing a rule-based method for identifying researchers on Twitter: The case of vaccine discussions. Poster abstract accepted to ISSI, 17th International Society of Scientometrics and Informetrics Conference, Rome, 2-5 September.

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Rule-based method for identifying researchers on Twitter

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Method development for Twitter biography classification concerning occurrences of academics, academically related groups and individuals, media, other groups and members of the general public. Written in the Python programming language.

Version 1.0


Björn Ekström. University of Borås (2019). <em>Rule-based method for identifying researchers on Twitter</em>. Swedish National Data Service. Version 1.0. <a href=""></a>

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Data format / data structure


Creator/Principal investigator(s)

Björn Ekström


Creative Commons  Attribution 4.0 International (CC BY 4.0)
Published: 2019-09-20