A Comparative Study of News Exposure and Consumption On and Off Facebook
Nardjes Amieur, Salim Chouaki, Oana Goga, Beatrice Roussillon
摘要
Social media giants like Meta, Google, and X leverage powerful algorithms to personalize user feeds, a practice now under intense public scrutiny. These algorithms can inadvertently skew the information users consume, potentially influencing political opinions and voting decisions. This raises critical questions: Do social media platforms foster misinformation and contribute to echo chambers?
To address this ongoing debate, our study directly compares news exposure on Facebook (where algorithmic influence is strong) with news consumption off-platform (where user behavior plays a larger role). Specifically, we investigate: (1) Are users exposed to more/less misinformation on Facebook compared with their off-platform misinformation consumption? (2) Is news exposure on Facebook more/less diverse than off-platform news consumption? (3) To what extent do socio-demographic and psychological factors influence misinformation exposure on Facebook and consumption off Facebook? (4) Is there a relationship between socio-demographic and psychological factors and news diversity on and off Facebook? and (5) Is users' exposure to misinformation on Facebook correlated to off-platform news consumption?
The longstanding biggest barrier to answering these questions has been the lack of access to data on what information users see and consume while browsing the Internet. In this paper, we use a measurement approach that asks a panel of users to donate data about the content they see online. For this, we designed a tool to collect traces of all news articles that individuals encounter on their desktop Facebook timeline and while they browse the Internet (off Facebook), along with signals about how users interact with them (e.g., clicks, time spent reading). Our tool observes content and interactions on and off Facebook on 4,149 news media domains sourced from Media Bias Fact Check and NewsGuard. Alongside the news post and article collection, we conduct surveys to gather socio-demographic and psychological data from our participants.
Our study of 123,995 news-related posts on Facebook and 70,587 news articles visits off Facebook, collected from 642 users during 12 weeks, reveals the following central findings: (1) Only a small fraction 4% of users' news consumption off Facebook is driven by news exposure on Facebook, and only 5.7% of misinformation consumption off Facebook is driven by news exposure on Facebook. (2) There is a higher prevalence of misinformation in user-received content on Facebook compared to deliberately consumed content off-platform. On Facebook, 5.9% of our users' news exposure comes from sources known for spreading misinformation, while off-platform, only 2.6% of our users' news consumption is from misinformation sources. Conversely, Facebook presents more diverse content -22% of users received content from only one political leaning on Facebook, compared to 36% of users who consumed content from only one political leaning off-platform.
(3) Several socio-demographic and psychological factors showed a statistically significant correlation with misinformation exposure on Facebook but not misinformation consumption off Facebook. (4) The proportion of misinformation consumed off Facebook emerged as a statistically significant predictor of users' exposure to misinformation on Facebook, independent of news consumption on Facebook.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
它引用的顶会 Paper11
- Exploring Lightweight Interventions at Posting Time to Reduce the Sharing of Misinformation on Social MediaFarnaz Jahanbakhsh, Amy X. Zhang, Adam J. Berinsky, Gordon Pennycook 等CSCW 2021 · 被引用 116 次
- Countering Fake News: A Comparison of Possible Solutions Regarding User Acceptance and EffectivenessJan Kirchner, Christian ReuterCSCW 2020 · 被引用 89 次
- Cookie Swap Party: Abusing First-Party Cookies for Web TrackingQuan Chen, Panagiotis Ilia, Michalis Polychronakis, Alexandros KapravelosWWW 2021 · 被引用 57 次
- Understanding Effects of Algorithmic vs. Community Label on Perceived Accuracy of Hyper-partisan MisinformationChenyan Jia, Alexander Boltz, Angie Zhang, Anqing Chen 等CSCW 2022 · 被引用 47 次
- "The Headline Was So Wild That I Had To Check": An Exploration of Women's Encounters With Health Misinformation on Social MediaLisa Mekioussa Malki, Dilisha Patel, Aneesha SinghCSCW 2024 · 被引用 26 次
相关 Paper
- What News Do People Get on Social Media? Analyzing Exposure and Consumption of News through Data DonationsSalim Chouaki, Abhijnan Chakraborty, Oana Goga, Savvas ZannettouWWW 2024 · 被引用 8 次
- Optimal Engagement-Diversity Tradeoffs in Social MediaFabian Baumann, Daniel Halpern, Ariel D. Procaccia, Iyad Rahwan 等WWW 2024 · 被引用 6 次
- Will the Crowd Game the Algorithm?: Using Layperson Judgments to Combat Misinformation on Social Media by Downranking Distrusted SourcesZiv Epstein, Gordon Pennycook, David G. RandCHI 2020 · 被引用 68 次
- Profiling the Dynamics of Trust & Distrust in Social Media: A Survey StudyYixuan Zhang, Yimeng Wang, Nutchanon Yongsatianchot, Joseph D. Gaggiano 等CHI 2024 · 被引用 15 次
- Others Are to Blame: Whom People Consider Responsible for Online MisinformationGabriel Lima, Jiyoung Han, Meeyoung ChaCSCW 2022 · 被引用 17 次
