In conjunction with RecSys 2021.
Workshop program is now announced!
The workshop addresses technical, societal, and ethical questions related to news analytics. Publishers increasingly rely on automation to supply information to readers. Conversely, readers face information overload as more and more stories become easily accessible. Both trends combine to create an “attention economy.” Historically, editors functioned as gatekeepers to information. Increasingly, publishers replace editors with news recommender systems which also provide a personalized selection of articles. These systems tailor news feeds to readers’ interests by exploiting patterns in interaction data. Even though the workshop has a technical focus, we welcome interdisciplinary contributions that shed light on legal, ethical, and societal ramifications of algorithmic news curation. The workshop introduces a more holistic view of news as a particular application domain of machine learning and knowledge discovery.
Publishers increasingly automate content curation and personalization to present the most relevant stories to readers. This task is challenging due to the dynamics of the news eco-system and lack of information concerning readers’ preferences and interests. Besides, ethical and legal issues emerge from recent trends such as deliberate misinformation campaigns and ignoring privacy regulations. This workshop invites contributions in the realm of news recommendation and analytics. In addition to technical papers, we welcome interdisciplinary submissions. Topics of interests include but are not limited to:
News Personalization
Context-aware news recommender systems
News recommendation in social media
Multi-modal news recommendation
User behavior analysis and user interest modeling in the news domain
User modeling and user profiling
Applications of data mining for personalized search and navigation
Personalized news user interface and visualization
Diversity and multiperspectivity in news personalization and recommendation
News Analytics
News semantics and ontologies
Adaptive and personalized news summarization, categorization, and opinion mining
Social Graph and heterogeneous network analysis
User segmentation and community discovery
Big data technologies for news streams
News framing research
Automated news generation
News political leaning and tone
News trends and evolution
Psychological, Societal, and Ethical Aspects of News Personalization Systems
Privacy and security issues
Clickbait, fake news, and misinformation detection
Diversity and fairness of news search/recommendation
Bias in online news
Transparency and explainability
Emotion and cognition in news reception