Identifying and characterizing alternative news media on Facebook

• Main Authors: Guimaraes, Samuel S., Reis, Julia C. S., Lima, Lucas, Ribeiro, Filipe N., Vasconcelos, Marisa, AN, Jisun, KWAK, Haewoon, Benevenuto, Fabricio
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Alternative Media; Facebook; Mainstream Media; Public Figures; Semi-supervised Learning; Social Media; Communication Technology and New Media; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/5913; https://ink.library.smu.edu.sg/context/sis_research/article/6916/viewcontent/Alternative_Media_Facebook_2020_av.pdf
• Institution: Singapore Management University

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.