Predicting Political Ideology from Digital Footprints

Michael Kitchener (), Nandini Anantharama (), Simon Angus () and Paul Raschky
Additional contact information
Michael Kitchener: SoDa Laboratories, Monash University
Nandini Anantharama: SoDa Laboratories, Monash University

No 2022-12, Monash Economics Working Papers from Monash University, Department of Economics

Abstract: This paper proposes a new method to predict individual political ideology from digital footprints on one of the world's largest online discussion forum. We compiled a unique data set from the online discussion forum reddit that contains information on the political ideology of around 91,000 users as well as records of their comment frequency and the comments' text corpus in over 190,000 different subforums of interest. Applying a set of statistical learning approaches, we show that information about activity in non-political discussion forums alone, can very accurately predict a user's political ideology. Depending on the model, we are able to predict the economic dimension of ideology with an accuracy of up to 90.63\% and the social dimension with an accuracy of up to 83.09\%. In comparison, using the textual features from actual comments does not improve predictive accuracy. Our paper highlights the importance of revealed digital behaviour to complement stated preferences from digital communication when analysing human preferences and behaviour using online data.

Keywords: data mining; political ideolog; digital footprint; Reddit (search for similar items in EconPapers)
JEL-codes: A10 (search for similar items in EconPapers)
Date: 2022-06
New Economics Papers: this item is included in nep-big, nep-pay and nep-pol
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Related works:
Working Paper: Predicting Political Ideology from Digital Footprints (2022)
Working Paper: Predicting Political Ideology from Digital Footprints (2022)
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