Call for Papers


IJCAI 2016 Workshop

July 9-11, New York

Call for Papers

With the advent of the digital era, journalism faces what seems to be a major change in its history - data processing. While much journalistic effort has been (and still is) dedicated to information gathering, now a great deal of information is readily available – but is dispersed in a large quantity of data. Thus processing a continuous and very large flow of data has become a central challenge in today's journalism.

With the recognition of this challenge, it has become widely accepted that data-driven journalism is the future. Tools which perform big data mining in order to pick out and link together what is interesting from various multi media resources are needed; these tools will be used as commonly as typewriters once were. Their scope is well beyond data classification: They need to construct sense and structure out of the never- ending flow of reported facts, ascertaining what is important and relevant. They need to be able to detect what is behind the text, what authors' intentions are, what opinions are expressed and how, whose propagandistic goal an article might serve, etc. What's more, they need to go beyond an intelligent search engine: They need to be picky and savvy, just like good journalists, in order to help people see what is really going on.

At this workshop we anticipate papers that report on state-of-the-art inquiries into the analysis and use of large to huge news corpora. A news corpus is generally understood as scoping over newspapers, social networks, the web, etc. The papers should present computational techniques able to manage a huge quantity of information and/or to perform deep analyses that extend over actual state of the art. We welcome reports on the recent progress on overcoming the bottlenecks in open domain relation extraction, paraphrasing, textual entailments and semantic similarity, and on their results in analyzing news content. However, we are also greatly interested in technologies for enhancing the communicative function of language in this context more generally, including in computational humor, nlp creativity for advertising, or plagiarism for example.


  • Advanced NLP news applications

  • Automatic temporal annotation

  • Automatic advertising and slogan generation

  • Causality and relatedness in news

  • Crowd-sourcing information gathering and reporting

  • Epochs and styles in journalism

  • Entity and event linking in social networks

  • Discourse similarity

  • Detecting patterns in developing news

  • Dissemination of news through social media

  • Fact checking on corpus extracted information

  • Fact Checking and Journalism Ethic

  • Intelligent tools for journalists, publishers, news readers

  • Linking multi media information

  • News and content recommendation and personalization

  • New approaches to news commenting

  • News summarization

  • Analyzing and Detecting Biased Language

  • Trust and credibility

  • Tools, Platforms and Languages by/for Journalists

  • Opinion changing and event drifting

  • Patterns and cliché detection

  • Plagiarism detection

  • Political and social discourse analysis

  • Predicting changes in news flow

  • Propagandistic style detection

  • Providing and encouraging information diversity

  • Sense and discourse shifting

  • Social media analytics for news

  • Spotting important events on social networks

  • Story tools and narrative frameworks

  • Technologies for providing context to news

  • Trend prediction

Important Dates

Submission Deadline: April 09, 2016

Accepted Paper Announcement: May 11, 2016


The IJCAI official format is requested. The recommended length is 4 pages, including references. The form of the presentation maybe oral or poster, while in the proceedings there is no difference between the accepted papers.


The submission is anonymous. Each paper will be reviewed but at least two independent reviewers.

Submission is made via Easychair:

Program Committee (confirmed)

Enrique Alfonseca, Google, CH

Dan Cristea, Iasi University, RO

Song Feng, IBM Research, US

Radu Gheorghiu, Uefiscdi, RO

Daniela Gifu, Iasi University, RO

Jay Hamilton, Stanford University, US

Mark Hansen, Columbia University, US

Orin Hargraves, Colorado University, US

Daisuke Kawahara, Kyoto University, JP

Zornitsa Kozareva, Yahoo! Research, US

Shervin Malmasi, Harvard University, US

Rada Mihalcea, University of Michigan, US

Preslav Nakov, UC Berkley, US

Vivi Nastase, FBK, IT

Gozde Ozbal, FBK , IT

Daniele Pighin, Google, CH

Mattia Rigotti, IBM Research, US

Paolo Rosso, Universitat de Valencia, Spain

Olga Uryupina, FBK, IT

Marcos Zampieri, Saarland University, DE

Torsten Zesch, Universität Duisburg-Essen, DE


Larry Birnbaum, Northwestern University, US

Octavian Popescu, IBM Research , US

Carlo Strapparava, FBK, Italy