Deriving the Political Affinity of Twitter Users from Their Followers

Abstract

In this work, we show that Twitter users can reveal valuable political information about particular Nodes of Interest (NOIs) they opt to follow. More precisely, we utilize an interesting graph projection method and a series of algorithmic approaches, such as modularity clustering, a minimum linear arrangement (MinLA) approximation algorithm and the DeGroot opinion update model in order to reveal the political affinity of selected NOIs. Our methods, which are purely structure-based, are applied to a snapshot of the Twitter network based on the user accounts of NOIs, consisting of the members of the current Greek Parliament along with their respective followers. The findings confirm that the information obtained can portray with significant precision the political affinity of the NOIs. We, furthermore, argue that these methods are of general interest for imprinting the political leaning of other NOIs, for example news media, and potentially classifying them in respect to their political bias.

Supplementary Material

Download PDF Download Dataset

The file socialcom-bipartite.edges is the main graph used in this work, extracted from the Twitter network. It is a bipartite graph consisting of 162 members of the Greek parliament along with their respective followers.

The file socialcom-projection.edges is the respective projected (uni-partite) graph using the overlap coefficient.

Files are ASCII encoded text files with CRLF line terminators.

Twitter snapshot as of 14-04-2018.

Citation

@inproceedings{stamatelatos2018deriving,
title={Deriving the Political Affinity of Twitter Users from Their Followers},
author={Stamatelatos, Giorgos and Gyftopoulos, Sotirios and Drosatos, George and Efraimidis, Pavlos S},
booktitle={Proceedings of the 11th IEEE International Conference on Social Computing},
doi = {10.1109/BDCloud.2018.00173},
year={2018},
organization={IEEE}
}

BibTeX

@inproceedings{stamatelatos2018deriving,
  title={Deriving the Political Affinity of Twitter Users from Their Followers},
  author={Stamatelatos, Giorgos and Gyftopoulos, Sotirios and Drosatos, George and Efraimidis, Pavlos S},
  booktitle={Proceedings of the 11th IEEE International Conference on Social Computing},
  doi = {10.1109/BDCloud.2018.00173},
  year={2018},
  organization={IEEE}
}