IDEAS home Printed from https://ideas.repec.org/p/mos/moswps/2022-12.html
   My bibliography  Save this paper

Predicting Political Ideology from Digital Footprints

Author

Listed:
  • Michael Kitchener

    (SoDa Laboratories, Monash University)

  • Nandini Anantharama

    (SoDa Laboratories, Monash University)

  • Simon D. Angus

    (Department of Economics and SoDa Laboratories, Monash University)

  • Paul A. Raschky

    (Department of Economics and SoDa Laboratories, Monash University)

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.

Suggested Citation

  • Michael Kitchener & Nandini Anantharama & Simon D. Angus & Paul A. Raschky, 2022. "Predicting Political Ideology from Digital Footprints," Monash Economics Working Papers 2022-12, Monash University, Department of Economics.
  • Handle: RePEc:mos:moswps:2022-12
    as

    Download full text from publisher

    File URL: http://monash-econ-wps.s3-ap-southeast-2.amazonaws.com/RePEc/mos/moswps/2022-12.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    More about this item

    Keywords

    data mining; political ideolog; digital footprint; Reddit;
    All these keywords.

    JEL classification:

    • A10 - General Economics and Teaching - - General Economics - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mos:moswps:2022-12. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Simon Angus (email available below). General contact details of provider: https://edirc.repec.org/data/dxmonau.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.