7th International Workshop on News Recommendation and Analytics (INRA 2019) will be held in conjunction with 13th ACM Conference on Recommender Systems (RecSys 2019) , 16-20 September 2019, Copenhagen, Denmark.

The news domain is characterized by a constant flow of unstructured, fragmentary, and unreliable news stories from numerous sources and different perspectives. Compared to recommender systems in domains like music, movies and books, news recommender systems pose some particular challenges that call for new and deeper analyses of both users and content.
Quickly finding relevant information, either in terms of individual news stories or aggregated knowledge from analyzing entire news streams, is a tremendous challenge that necessitates a wide range of technologies and a deep understanding of user preferences, news contents, and their relationships. The spread of increasing concerns about disinformation coupled with privacy violations necessitates improving news recommender systems.
This workshop primarily addresses news recommender systems and analytics. The news ecosystem engulfs a variety of actors including publishers, journalists, and readers. The news may originate in large media companies or digital social networks. INRA aims to connect researchers, media companies, and practitioners to exchange ideas about creating and maintaining a reliable and sustainable environment for digital news production and consumption.
In this year’s edition, we focus on three main categories: News recommendation, news analytics, and ethical aspects of news recommendation.

Topics of interests for this workshop include but are not limited to:

• News Recommendation

– Innovative algorithms for news recommendation
– News context modelling
– Big data technologies for news streams
– Practical applications

• News Analytics

– News semantics and ontologies
– News summarisation, 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
– Spread mechanisms of disinformation