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

Creator/Principal investigator(s)

Björn Ekström

Description

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.

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)

Keywords

classification, social media

Principal organisation

University of Borås

Accessibility status

Access to data through SND
Data are freely accessible

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class.py (7.62 KB)

Responsible department/unit

University of Borås

Creator/Principal investigator(s)

Björn Ekström

Identifiers

SND-ID: SND 1117

Description

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.

Language

English

Time period(s) investigated

2018-06-01 — 2019-10-31

Unit of analysis

Population

Twitter users

Time Method

Sampling procedure

Other

Funding

Horizon 2020 — Ref. 770531

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)

Keywords

classification, social media

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Publications

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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Version 1.0

2019-08-23
https://doi.org/10.5878/akmc-va16

Download data

class.py (7.62 KB)

License

Creative Commons License

Rule-based method for identifying researchers on Twitter

Suggested citation

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="https://doi.org/10.5878/akmc-va16">https://doi.org/10.5878/akmc-va16</a>

Creator/Principal investigator(s)

Björn Ekström

Description

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.

Data format / data structure

Software

Published: 2019-09-20