Digital Trace Data in the Study of Public Opinion: An Indicator of Attention Toward Politics Rather Than Political Support. (June 2017)

• Record Type: Journal Article
• Authors: Jungherr, Andreas; Schoen, Harald; Posegga, Oliver; Jürgens, Pascal
• Is Part Of: Social science computer review. Volume 35:Number 3(2017:Jun.)
• Page Start: 336
• Page End: 356
• Publication Date: 2017-06
• Subjects: computational social science -- digital trace data -- mediation of politics -- Twitter -- electoral predictions -- public opinion; Social sciences -- Data processing -- Periodicals; Computers -- Social aspects -- Periodicals; Microcomputers -- Periodicals; Sciences sociales -- Informatique -- Périodiques; Micro-ordinateurs -- Périodiques; 300.285
• DOI: 10.1177/0894439316631043
• Languages: English
• ISSNs: 0894-4393

Abstract

In this article, we examine the relationship between metrics documenting politics-related Twitter activity with election results and trends in opinion polls. Various studies have proposed the possibility of inferring public opinion based on digital trace data collected on Twitter and even the possibility to predict election results based on aggregates of mentions of political actors. Yet, a systematic attempt at a validation of Twitter as an indicator for political support is lacking. In this article, building on social science methodology, we test the validity of the relationship between various Twitter-based metrics of public attention toward politics with election results and opinion polls. All indicators tested in this article suggest caution in the attempt to infer public opinion or predict election results based on Twitter messages. In all tested metrics, indicators based on Twitter mentions of political parties differed strongly from parties' results in elections or opinion polls. This leads us to question the power of Twitter to infer levels of political support of political actors. Instead, Twitter appears to promise insights into temporal dynamics of public attention toward politics.