Twitter Language Use Reflects Psychological Differences between Democrats and Republicans

Previous research has shown that political leanings correlate with various psychological factors. While surveys and experiments provide a rich source of information for political psychology, data from social networks can offer more naturalistic and robust material for analysis. This research investi...

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Bibliographic Details
Published inPloS one Vol. 10; no. 9; p. e0137422
Main Authors Sylwester, Karolina, Purver, Matthew
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 16.09.2015
Public Library of Science (PLoS)
Subjects
Anxiety
Authoritarianism
Behavior
Computer science
Conservatism
Evaluation
Experiments
Humans
Individual differences
Language
Liberalism
Morality
Obscenities
Online social networks
Personality
Personality traits
Political anthropology
Political parties
Political psychology
Politics
Predictions
Psychological aspects
Psychological factors
Psychology
Public opinion
Religion
Sermons
Social media
Social Networking
Social networks
Social organization
Social research
Studies
Values
United Kingdom > UK
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Summary:Previous research has shown that political leanings correlate with various psychological factors. While surveys and experiments provide a rich source of information for political psychology, data from social networks can offer more naturalistic and robust material for analysis. This research investigates psychological differences between individuals of different political orientations on a social networking platform, Twitter. Based on previous findings, we hypothesized that the language used by liberals emphasizes their perception of uniqueness, contains more swear words, more anxiety-related words and more feeling-related words than conservatives' language. Conversely, we predicted that the language of conservatives emphasizes group membership and contains more references to achievement and religion than liberals' language. We analysed Twitter timelines of 5,373 followers of three Twitter accounts of the American Democratic and 5,386 followers of three accounts of the Republican parties' Congressional Organizations. The results support most of the predictions and previous findings, confirming that Twitter behaviour offers valid insights to offline behaviour.
Bibliography:Conceived and designed the experiments: KS MP. Performed the experiments: KS. Analyzed the data: KS MP. Contributed reagents/materials/analysis tools: KS MP. Wrote the paper: KS MP. Collected the data: KS.
Competing Interests: Purver holds grants for language processing research including concept creation (ConCreTe) and dementia diagnosis (SLADE). The SLADE project is funded by the Queen Mary Innovation Fund; the project ConCreTe acknowledges the financial support of the Future and Emerging Technologies (FET) programme within the Seventh Framework Programme for Research of the European Commission, under FET grant number 611733. He co-founded the social media analytics company Chatterbox Labs Limited in 2011, and remains a shareholder; he is co-inventor on a pending patent application for language analysis for mental health diagnosis. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0137422