Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

12-2020

Abstract

As Internet users increasingly rely on social media sites to receive news, they are faced with a bewildering number of news media choices. For example, thousands of Facebook pages today are registered and categorized as some form of news media outlets. This situation boosted the so-called independent journalism, also known as alternative news media. Identifying and characterizing all the news pages that play an important role in news dissemination is key for understanding the news ecosystems of a country. In this work, we propose a graph-based semi-supervised method to measure the political bias of pages on most countries and show the political split of the alternative media, mainstream media, and public figures pages. We validate our method using the publicly available U.S. dataset and then apply it to Brazilian pages, where we found a larger number of right-wing pages in general, except for alternative news media.

Keywords

Alternative Media, Facebook, Mainstream Media, Public Figures, Semi-supervised Learning, Social Media

Discipline

Communication Technology and New Media | Numerical Analysis and Scientific Computing | Social Media

Research Areas

Data Science and Engineering

Publication

2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining12th ASONAM: Virtual, December 7-10: Proceedings

First Page

448

Last Page

452

ISBN

9781728110561

Identifier

10.1109/ASONAM49781.2020.9381424

Publisher

IEEE

City or Country

Piscataway, NJ

Embargo Period

5-7-2021

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1109/ASONAM49781.2020.9381424

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