Results 21 to 30 of about 1,666,598 (158)
Bad News Travels Slowly: Size, Analyst Coverage and the Profitability of Momentum Strategies
, 1998 Various theories have been proposed to explain momentum in stock returns. We test the gradual-information-diffusion model of Hong and Stein ~1999! and establish three key results.
Harrison G. Hong, Terence Lim, J. Stein
semanticscholar +1 more source
ACM Computing Surveys, 2020 The explosive growth in fake news and its erosion to democracy, justice, and public trust has increased the demand for fake news detection and intervention.
Xinyi Zhou
semanticscholar +1 more source
Framing European politics: a content analysis of press and television news
, 2000 We investigated the prevalence of 5 news frames identified in earlier studies on framing and framing effects: attribution of responsibility, conflict, human interest, economic consequences, and morality.
H. Semetko, P. Valkenburg
semanticscholar +1 more source
Less than you think: Prevalence and predictors of fake news dissemination on Facebook
Science Advances, 2019 Fake news sharing in 2016 was rare but significantly more common among older Americans. So-called “fake news” has renewed concerns about the prevalence and effects of misinformation in political campaigns. Given the potential for widespread dissemination
A. Guess +2 more
semanticscholar +1 more source
Politicization and Polarization in COVID-19 News Coverage
Science communication, 2020 This study examines the level of politicization and polarization in COVID-19 news in U.S. newspapers and televised network news from March to May 2020.
P. S. Hart, Sedona Chinn, S. Soroka
semanticscholar +1 more source
CSI: A Hybrid Deep Model for Fake News Detection [PDF]
International Conference on Information and Knowledge Management, 2017 The topic of fake news has drawn attention both from the public and the academic communities. Such misinformation has the potential of affecting public opinion, providing an opportunity for malicious parties to manipulate the outcomes of public events ...
Natali Ruchansky, Sungyong Seo, Yan Liu
semanticscholar +1 more source
ProFairRec: Provider Fairness-aware News Recommendation [PDF]
arXiv, 2022 News recommendation aims to help online news platform users find their preferred news articles. Existing news recommendation methods usually learn models from historical user behaviors on news. However, these behaviors are usually biased on news providers. Models trained on biased user data may capture and even amplify the biases on news providers, and
arxiv
Modeling Multi-interest News Sequence for News Recommendation [PDF]
arXiv, 2022 A session-based news recommender system recommends the next news to a user by modeling the potential interests embedded in a sequence of news read/clicked by her/him in a session. Generally, a user's interests are diverse, namely there are multiple interests corresponding to different types of news, e.g., news of distinct topics, within a session ...
arxiv
Aspect-driven User Preference and News Representation Learning for News Recommendation [PDF]
arXiv, 2021 News recommender systems are essential for helping users to efficiently and effectively find out those interesting news from a large amount of news. Most of existing news recommender systems usually learn topic-level representations of users and news for recommendation, and neglect to learn more informative aspect-level features of users and news for ...
arxiv
Annotation-Scheme Reconstruction for "Fake News" and Japanese Fake News Dataset [PDF]
arXiv, 2022 Fake news provokes many societal problems; therefore, there has been extensive research on fake news detection tasks to counter it. Many fake news datasets were constructed as resources to facilitate this task. Contemporary research focuses almost exclusively on the factuality aspect of the news.
arxiv