Emotional Dynamics in the Age of Misinformation
arXiv:1505.08001 · doi:10.1371/journal.pone.0138740
Abstract
According to the World Economic Forum, the diffusion of unsubstantiated rumors on online social media is one of the main threats for our society. The disintermediated paradigm of content production and consumption on online social media might foster the formation of homophile communities (echo-chambers) around specific worldviews. Such a scenario has been shown to be a vivid environment for the diffusion of false claims, in particular with respect to conspiracy theories. Not rarely, viral phenomena trigger naive (and funny) social responses -- e.g., the recent case of Jade Helm 15 where a simple military exercise turned out to be perceived as the beginning of the civil war in the US. In this work, we address the emotional dynamics of collective debates around distinct kind of news -- i.e., science and conspiracy news -- and inside and across their respective polarized communities (science and conspiracy news). Our findings show that comments on conspiracy posts tend to be more negative than on science posts. However, the more the engagement of users, the more they tend to negative commenting (both on science and conspiracy). Finally, zooming in at the interaction among polarized communities, we find a general negative pattern. As the number of comments increases -- i.e., the discussion becomes longer -- the sentiment of the post is more and more negative.
References in corpus (3)
Cited by in corpus (33)
- Sentiment of Emojis
- The Effects of Twitter Sentiment on Stock Price Returns
- Users Polarization on Facebook and Youtube
- Multilingual Twitter Sentiment Classification: The Role of Human Annotators
- The role of bot squads in the political propaganda on Twitter
- The Web of False Information: Rumors, Fake News, Hoaxes, Clickbait, and Various Other Shenanigans
- Flow of online misinformation during the peak of the COVID-19 pandemic in Italy
- An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changes
- Auditing YouTube's Recommendation Algorithm for Misinformation Filter Bubbles
- On the statistical properties of viral misinformation in online social media
- "Everything I Disagree With is #FakeNews": Correlating Political Polarization and Spread of Misinformation
- Writing about COVID-19 vaccines: Emotional profiling unravels how mainstream and alternative press framed AstraZeneca, Pfizer and vaccination campaigns
- The role of voting intention in public opinion polarization
- Exposing Influence Campaigns in the Age of LLMs: A Behavioral-Based AI Approach to Detecting State-Sponsored Trolls
- Public discourse and social network echo chambers driven by socio-cognitive biases
- Entropy-based detection of Twitter echo chambers
- A model for the Twitter sentiment curve
- Online Hate: Behavioural Dynamics and Relationship with Misinformation
- Agent Based Rumor Spreading in a scale-free network
- Community Fact-Checks Trigger Moral Outrage in Replies to Misleading Posts on Social Media
- The Anatomy of Brexit Debate on Facebook
- (Mis)Information Operations: An Integrated Perspective
- A network model of conviction-driven social segregation
- It's Always April Fools' Day! On the Difficulty of Social Network Misinformation Classification via Propagation Features
- Lexical convergence and collective identities on Facebook
- MP Twitter Abuse in the Age of COVID-19: White Paper
- Soros, Child Sacrifices, and 5G: Understanding the Spread of Conspiracy Theories on Web Communities
- Networks of plants: how to measure similarity in vegetable species
- Towards the Modeling of Behavioral Trajectories of Users in Online Social Media
- Disagreement as a way to study misinformation and its effects
- Towards Understanding the Information Ecosystem Through the Lens of Multiple Web Communities
- Fake news as we feel it: perception and conceptualization of the term "fake news" in the media
- Impact of memory and bias in kinetic exchange opinion models on random networks