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

Creator/Principal investigator(s):

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.

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class.py (7.62 KB)
Rule-based method for identifying researchers on Twitter

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Creator/Principal investigator(s):

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

Population:

Twitter users

Time Method:

Sampling procedure:

Other

Funding:

Horizon 2020 —770531

Publications

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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:

Download data:

class.py (7.62 KB)
Rule-based method for identifying researchers on Twitter

License:

Creative Commons License

Rule-based method for identifying researchers on Twitter

Citation:

Björn Ekström. University of Borås (2019). Rule-based method for identifying researchers on Twitter. Swedish National Data Service. Version 1.0. https://doi.org/10.5878/akmc-va16

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