Identifying and Characterizing Alternative News Media on Facebook

被引：0
|
作者：
Guimaraes, Samuel S. [1 ]
Reis, Julio C. S. [1 ,3 ]
Lima, Lucas [1 ]
Ribeiro, Filipe N. [2 ]
Vasconcelos, Marisa [4 ]
An, Jisun [5 ]
Kwak, Haewoon [5 ]
Benevenuto, Fabricio [1 ]
机构：
[1] Univ Fed Minas Gerais, UFMG, Belo Horizonte, MG, Brazil
[2] Univ Fed Ouro Preto UFOP, Ouro Preto, MG, Brazil
[3] Univ FUMEC, Belo Horizonte, MG, Brazil
[4] IBM Res, Sao Paulo, Brazil
[5] Singapore Management Univ, Singapore, Singapore
来源：
2020 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM) | 2020年
关键词：
Facebook; Social Media; Public Figures; Alternative Media; Mainstream Media; Semi-supervised Learning;
D O I：
10.1109/ASONAM49781.2020.9381424
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
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页码：448 / 452
页数：5
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