NLPM 2016 - NATURAL LANGUAGE PROCESSING MEETS JOURNALISM

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.
Topics
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