political bias
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2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Wen Chen ◽  
Diogo Pacheco ◽  
Kai-Cheng Yang ◽  
Filippo Menczer
Keyword(s):  

2022 ◽  
pp. 133-151
Author(s):  
María Díez-Garrido ◽  
Dafne Calvo ◽  
Lorena Cano-Orón

Fact-checkers have grown recently, facing the decline of journalism and the acceleration of disinformation flows on the internet. Due to the recent scholarly attention to these journalistic outlets, some authors have pointed to diverse critics such as the political bias and the low impact of fact-checking initiatives. In line with the research approaching the weaponization of disinformation in politics, this chapter reflects on the instrumentalization of verifying practices as a fact to consider when studying fact-checking. The investigation applies a combined methodology to compare Bendita and Maldita initiatives. While the latter is internationally recognized as an entity of fact-checking, the second one arises as an imitation of it and lacks recognition and scholarly attention. Conclusions suggest that fact-checking implies more complex activities than refuting specific facts, while alt-right positions can instrumentalize fact-checking for political objectives. The authors call for the importance of definitions that exclude this type of misuse of verification.


2022 ◽  
pp. 103654
Author(s):  
Ruibo Liu ◽  
Chenyan Jia ◽  
Jason Wei ◽  
Guangxuan Xu ◽  
Soroush Vosoughi

Author(s):  
Alessandro Miani ◽  
Thomas Hills ◽  
Adrian Bangerter

AbstractThe spread of online conspiracy theories represents a serious threat to society. To understand the content of conspiracies, here we present the language of conspiracy (LOCO) corpus. LOCO is an 88-million-token corpus composed of topic-matched conspiracy (N = 23,937) and mainstream (N = 72,806) documents harvested from 150 websites. Mimicking internet user behavior, documents were identified using Google by crossing a set of seed phrases with a set of websites. LOCO is hierarchically structured, meaning that each document is cross-nested within websites (N = 150) and topics (N = 600, on three different resolutions). A rich set of linguistic features (N = 287) and metadata includes upload date, measures of social media engagement, measures of website popularity, size, and traffic, as well as political bias and factual reporting annotations. We explored LOCO’s features from different perspectives showing that documents track important societal events through time (e.g., Princess Diana’s death, Sandy Hook school shooting, coronavirus outbreaks), while patterns of lexical features (e.g., deception, power, dominance) overlap with those extracted from online social media communities dedicated to conspiracy theories. By computing within-subcorpus cosine similarity, we derived a subset of the most representative conspiracy documents (N = 4,227), which, compared to other conspiracy documents, display prototypical and exaggerated conspiratorial language and are more frequently shared on Facebook. We also show that conspiracy website users navigate to websites via more direct means than mainstream users, suggesting confirmation bias. LOCO and related datasets are freely available at https://osf.io/snpcg/.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Samuel S. Guimarães ◽  
Julio C. S. Reis ◽  
Marisa Vasconcelos ◽  
Fabrício Benevenuto
Keyword(s):  

2021 ◽  
Author(s):  
Andre Mediote de Sousa ◽  
Karin Becker

Collective imunization is critical to combat COVID, but a large portion of the population in many countries refuses to be vaccinated despite the availability of vaccines. We developed a temporal analysis of pro/against stances towards COVID vaccination in Brazil using Twitter. We summarized the main topics expressed by pro/anti-vaxxers using BERTopic, a dynamic topic modeling technique, and related them to events in the national scenario. The anti-vaxxers were prevalent throughout 2020, expressing concerns about mandatory vaccination with a strong political bias. The pro-vaxxer movement significantly increased by late 2020 with the begging of immunization and became prevalent in 2021. This group expresses joy and anxiety to get vaccinated and criticisms towards the Federal Government.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Wen Chen ◽  
Diogo Pacheco ◽  
Kai-Cheng Yang ◽  
Filippo Menczer

AbstractSocial media platforms attempting to curb abuse and misinformation have been accused of political bias. We deploy neutral social bots who start following different news sources on Twitter, and track them to probe distinct biases emerging from platform mechanisms versus user interactions. We find no strong or consistent evidence of political bias in the news feed. Despite this, the news and information to which U.S. Twitter users are exposed depend strongly on the political leaning of their early connections. The interactions of conservative accounts are skewed toward the right, whereas liberal accounts are exposed to moderate content shifting their experience toward the political center. Partisan accounts, especially conservative ones, tend to receive more followers and follow more automated accounts. Conservative accounts also find themselves in denser communities and are exposed to more low-credibility content.


Societies ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 113
Author(s):  
Andrew S. Franks ◽  
Farhang Hesami

Three studies sought to explore the existence of (a)symmetric bias regarding Donald Trump. In Study 1, participants read one of three statements expressing different degrees of favorability toward electing the President of the United States via a National Popular Vote attributed to Trump or an anonymous source. In Study 2, participants read one of two statements either favoring or disfavoring the name change of the Washington NFL franchise, and the statement was attributed to either Trump or an anonymous source. In Study 3, Trump and Biden voters were asked to rate their support or opposition to counting all the votes in battleground states when continued counting was expected to either help Trump or Biden. Results for all three studies supported the asymmetric bias hypothesis. Trump supporters consistently showed bias in favor of the interests and ostensible positions of Trump, whereas Trump’s detractors did not show an opposing bias.


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