@inproceedings{e13df330caad467cb7d248c44bead81b,
title = "IdeoTrace: A framework for ideology tracing with a case study on the 2016 U.S. presidential election",
abstract = "The 2016 United States presidential election has been characterized as a period of extreme divisiveness that was exacerbated on social media by the influence of fake news, trolls, and social bots. However, the extent to which the public became more polarized in response to these influences over the course of the election is not well understood. In this paper we propose IdeoTrace, a framework for (i) jointly estimating the ideology of social media users and news websites and (ii) tracing changes in user ideology over time. We apply this framework to the last two months of the election period for a group of 47508 Twitter users and demonstrate that both liberal and conservative users became more polarized over time.",
author = "Indu Manickam and Lan, {Andrew S.} and Gautam Dasarathy and Baraniuk, {Richard G.}",
note = "Funding Information: ACKNOWLEDGMENTS This work was supported in part by ONR grant N00014-17-1-2551. Publisher Copyright: {\textcopyright} 2019 Copyright is held by the owner/author(s).; 11th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019 ; Conference date: 27-08-2019 Through 30-08-2019",
year = "2019",
month = aug,
day = "27",
doi = "10.1145/3341161.3342887",
language = "English (US)",
series = "Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019",
publisher = "Association for Computing Machinery, Inc",
pages = "274--281",
editor = "Francesca Spezzano and Wei Chen and Xiaokui Xiao",
booktitle = "Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019",
}