First International Workshop on Recent Trends in News Information Retrieval (NewsIR’16)

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9626)


The news industry has gone through seismic shifts in the past decade with digital content and social media completely redefining how people consume news. Readers check for accurate fresh news from multiple sources throughout the day using dedicated apps or social media on their smartphones and tablets. At the same time, news publishers rely more and more on social networks and citizen journalism as a frontline to breaking news. In this new era of fast-flowing instant news delivery and consumption, publishers and aggregators have to overcome a great number of challenges. These include the verification or assessment of a source’s reliability; the integration of news with other sources of information; real-time processing of both news content and social streams in multiple languages, in different formats and in high volumes; deduplication; entity detection and disambiguation; automatic summarization; and news recommendation. Although Information Retrieval (IR) applied to news has been a popular research area for decades, fresh approaches are needed due to the changing type and volume of media content available and the way people consume this content. The goal of this workshop is to stimulate discussion around new and powerful uses of IR applied to news sources and the intersection of multiple IR tasks to solve real user problems. To promote research efforts in this area, we released a new dataset consisting of one million news articles to the research community and introduced a data challenge track as part of the workshop.


Social Medium Information Retrieval News Article Sentiment Analysis News Source 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    De Francisci, G., Morales, A.G., Lucchese, C.: From chatter to headlines: harnessing the real-time web for personalized news recommendation. In: Proceedings of WSDM (2012)Google Scholar
  2. 2.
    Mathioudakis, M., Koudas, N.: Twittermonitor: trend detection over the Twitter stream. In: Proceedings of SIGMOD (2010)Google Scholar
  3. 3.
    Aslam, J., Ekstrand-Abueg, M., Pavlu, V., Diaz, F., Sakai, T.: TrREC temporal summarization. In: Proceedings of TREC (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Signal MediaLondonUK
  2. 2.University of EssexColchesterUK
  3. 3.LumiLondonUK
  4. 4.University of GlasgowGlasgowScotland
  5. 5.LIAAD-INESC TECInstituto Politécnico de TomarTomarPortugal

Personalised recommendations