Filter bubbles and fake news
@article{DiFranzo2017FilterBA, title={Filter bubbles and fake news}, author={Dominic DiFranzo and Marie Joan Kristine Gloria}, journal={XRDS: Crossroads, The ACM Magazine for Students}, year={2017}, volume={23}, pages={32 - 35} }
The results of the 2016 Brexit referendum in the U.K. and presidential election in the U.S. surprised pollsters and traditional media alike, and social media is now being blamed in part for creating echo chambers that encouraged the spread of fake news that influenced voters.
69 Citations
Fake news and ideological polarization
- Sociology
- 2017
This article addresses questions of ideological polarization and the filter bubble in social media. It develops a theoretical analysis of ideological polarization on social media by considering a…
Fake News in Social Media: Bad Algorithms or Biased Users?
- Computer Science
- 2019
Although fake news has been present in human history at any time, nowadays, with social media, deceptive information has a stronger effect on society than before. This article answers two research…
Fake news as a two-dimensional phenomenon: a framework and research agenda
- SociologyAnnals of the International Communication Association
- 2019
ABSTRACT Based on an extensive literature review, we suggest that ‘fake news’ alludes to two dimensions of political communication: the fake news genre (i.e. the deliberate creation of…
Fighting fake news in the COVID-19 era: policy insights from an equilibrium model
- Political SciencePolicy sciences
- 2020
A formal mathematical model is introduced to understand factors influencing the behavior of social media users when encountering fake news and illustrates that direct efforts by social media platforms and governments, along with informal pressure from social networks, can reduce the likelihood that users who encounter fake news embrace and further circulate it.
Examining Trolls and Polarization with a Retweet Network
- Business
- 2018
This research examines the relationship between political homophily and organized trolling efforts. This is accomplished by analyzing how Russian troll accounts were retweeted on Twitter in the…
“Brave New World” of Fake News: How It Works
- BusinessJavnost - The Public
- 2021
The spread of fake news poses a serious threat to democracy and journalism. Fake news has found the ideal tools to thrive in the digital world. Therefore, it is urgent to understand this phenomenon.…
Freedom from Social Echo Chambers: Policy Implications of an Algorithmic Bias
- Sociology
- 2017
Search engines and social networking sites use a number of signals to track interests and preferences online in order to continually display content that retains readership and activity. Building on…
The Influence of Political Ideology on Fake News Belief: The Portuguese Case
- PsychologyPubl.
- 2021
The results show the belief and dissemination of (fake) news are related to the political ideology of the participants, with right-wing subjects exhibiting a greater tendency to accept fake news, regardless of whether it is pro-left or pro-right fake news.
Bubble Trouble: Strategies Against Filter Bubbles in Online Social Networks
- Computer ScienceHCI
- 2019
It can be concluded that in today’s digital age, it is important not only to inform users about the existence of filter bubbles, but also about various possible strategies for dealing with them.
Challenging Misinformation: Exploring Limits and Approaches
- Computer ScienceINTERACT
- 2019
This workshop will challenge participants to critically reflect the limits of existing socio-technical approaches and co-create scenarios in which digital platforms support misinformation resilience, to unpack the challenge at hand.
References
SHOWING 1-10 OF 49 REFERENCES
Bursting your (filter) bubble: strategies for promoting diverse exposure
- Computer ScienceCSCW '13
- 2013
What scholars know about selectivity of exposure preferences and actual exposure and what the authors in the CSCW field can do to develop and test ways of promoting diverse exposure, openness to the diversity they actually encounter are reviewed.
Exposure to ideologically diverse news and opinion on Facebook
- SociologyScience
- 2015
Examination of the news that millions of Facebook users' peers shared, what information these users were presented with, and what they ultimately consumed found that friends shared substantially less cross-cutting news from sources aligned with an opposing ideology.
The spreading of misinformation online
- Computer ScienceProceedings of the National Academy of Sciences
- 2016
A massive quantitative analysis of Facebook shows that information related to distinct narratives––conspiracy theories and scientific news––generates homogeneous and polarized communities having similar information consumption patterns, and derives a data-driven percolation model of rumor spreading that demonstrates that homogeneity and polarization are the main determinants for predicting cascades’ size.
Bots and Automation over Twitter during the Second U.S. Presidential Debate
- Computer Science
- 2016
Twitter is much more actively pro-Trump than pro-Clinton and more of the pro- Trump twitter traffic is driven by bots, but a significant number of (human) users still use Twitter for relatively neutral political expression in critical moments.
Friends, Fans, and Followers: Do Ads Work on Social Networks?
- Computer ScienceJournal of Advertising Research
- 2011
A model of content-related, structural, and socialization factors that affect users' attitudes toward social-networking advertising is proposed and empirical support for these propositions is lacking.
A 61-million-person experiment in social influence and political mobilization
- PsychologyNature
- 2012
Results from a randomized controlled trial of political mobilization messages delivered to 61 million Facebook users during the 2010 US congressional elections show that the messages directly influenced political self-expression, information seeking and real-world voting behaviour of millions of people.
Epidemiological modeling of news and rumors on Twitter
- Computer ScienceSNAKDD '13
- 2013
This work uses epidemiological models to characterize information cascades in twitter resulting from both news and rumors, using the SEIZ enhanced epidemic model that explicitly recognizes skeptics to characterize eight events across the world and spanning a range of event types.
Botnet Campaign Detection on Twitter
- Computer Science, EducationArXiv
- 2018
Thesis is recommended for acceptance as a thesis in partial fulfillment of the requirements for the degree of Master of Science in Computer and Information Sciences.
The Filter Bubble: How the New Personalized Web Is Changing What We Read and How We Think
- Art
- 2012
In December 2009, Google began customizing its search results for all users, and we entered a new era of personalization. With little notice or fanfare, our online experience is changing, as the…
Will the Global Village Fracture Into Tribes? Recommender Systems and Their Effects on Consumer Fragmentation
- BusinessManag. Sci.
- 2014
Whether personalization is in fact fragmenting the online population does not appear to do so in this study, and appears to be a tool that helps users widen their interests, which in turn creates commonality with others.