In conjunction with ECML PKKD 2020, 14-18 September 2020, Ghent, Belgium.
NEWS: Due to the corona virus pandemic, in coordination with ECML PKDD organizers, we have decided to extend the paper submission deadline for the 8th International Workshop on News Recommendation and Analytics (INRA 2020) until the end of June. The new submission deadline is 30 June 2020.
We also would like to inform you that our workshop will be held digitally. We will be using the special software provided by the ECML PKDD.
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:
– Innovative algorithms for news personalization
– Reader Profiling
– News context and trend modelling
– Big data technologies for news streams
– Practical applications
– News semantics and ontologies
– News summarization, classification, and sentiment analysis
– Large-scale news mining and analytics
– News evolution and trends
– News from social media
Ethical Aspects of News Recommendation
– Detection and analysis of fake news and disinformation
– News diversity and filter bubbles
– Privacy and security in news recommender systems