27.3160, Calls: Computing News Storylines 2016 : Computational Linguistics, Discourse Analysis/USA

Wed Aug 3 17:23:13 UTC 2016

LINGUIST List: Vol-27-3160. Wed Aug 03 2016. ISSN: 1069 - 4875.

Subject: 27.3160, Calls: Computing News Storylines 2016 : Computational Linguistics, Discourse Analysis/USA

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Date: Wed, 03 Aug 2016 13:22:44
From: Tommaso Caselli [t.caselli at vu.nl]
Subject: Computing News Storylines 2016

Full Title: Computing News Storylines 2016 
Short Title: CNewsStory 2016 

Date: 05-Nov-2016 - 05-Nov-2016
Location: Austin, Texas, USA 
Contact Person: Tommaso Caselli
Meeting Email: t.caselli at vu.nl
Web Site: https://sites.google.com/site/newsstorylines2016/home 

Linguistic Field(s): Computational Linguistics; Discourse Analysis 

Call Deadline: 12-Aug-2016 

Meeting Description:

Today’s digital media ecosystem generates massive streams of news, largely in
the form of individual documents (‘articles’) within which news events and
narrative structures are communicated using natural language text. The
increasing quantity of text documents produced by the ecosystem has presented
challenges to those seeking to understand and contextualize news events and
narratives over long periods of time, leading to demands for new
multidimensional, multimodal and distributed representations of news events
and of the narrative structures that are constructed from them. Currently,
most work on cross-document temporal processing focuses on linear timelines
(i.e. representations of chronologically ordered events), however not every
timeline necessarily forms a good and useful storyline.

This multidisciplinary workshop aims at gathering researchers in NLP, AI,
knowledge representation and structured journalism together with journalists,
policy makers and stakeholders in the news industry to discuss how NLP
technology can help to deal with the current stream of information, manage the
risks of information overload, identify different sources and perspectives,
and provide unitary and easily intelligible representations of the larger and
long-term storylines behind news articles.

We invite work on all aspects relating to the computational generation,
representation, analysis or use of news storylines or their components, and on
the relationships between news storylines or their components. This includes
(but is not limited to) the following topics:

- Identifying and filtering relevant events
- Accumulating information from news streams
- Detecting opinions and perspectives on events
- Tracing perspective change through time
- Modelling plot structures
- Storyline stability and completeness
- Annotating storylines
- Crowdsourcing Storylines
- Temporal or causal ordering of events
- Script activation
- Big data for storylines
- Evaluation of storylines
- Discourse structure and storylines
- Visualisation of storylines
- Visualisation of news clusters
- Event factuality profiling
- Multimodal storyline generation
- Event-centred structured journalism
- Event-centered natural language generation
- Event taxonomies and ontologies
- Characteristics of journalistic events and narratives
- Representation of journalistic events and narratives
- Narrative networks
- Pattern detection in news
- Advanced NLP news applications
- Automatic Temporal Processing
- Tools for automatic fact-checking on information extracted from corpora
- News summarisation
- Pattern detection in news reports
- Trend prediction

Organizing Committee:

Tommaso Caselli, Vrije Universiteit Amsterdam (NL)
Ben Miller, Georgia State University (U.S.A)
Marieke van Erp, VU University Amsterdam (NL)
Piek Vossen, VU University Amsterdam (NL)
David Caswell, Reynolds Journalism Institute, University of Missouri (U.S.A)

Call for Papers:

Computing News Storylines 2016 (CNewsStory 2016)-  in conjunction with EMNLP
2016, Austin, Texas, U.S.A

More info: https://sites.google.com/site/newsstorylines2016/home 

Important Dates:

Paper submission: Extended Deadline: 12 August 2016 23:59 Hawaii time 
Notification: 5 September 2016 23:59 Hawaii time
Camera-ready due: 26 September 2016 23:59 Hawaii time
Workshop:  5 November 2016

This workshop aims at gathering researchers in NLP, AI, knowledge
representation, and structured journalism together with journalists, policy
makers and stakeholders in the news industry to discuss how NLP technology can
help to deal with the current stream of information, manage the risks of
information overload, identify different sources and perspectives, and provide
unitary and easily intelligible representations of the larger and long-term
storylines behind news articles.

We invite work on all aspects relating to the computational generation,
representation, analysis or use of news storylines or their components. This
includes (but is not limited to) the following topics:

Submissions:

Full papers should emphasize obtained results rather than intended work, and
should indicate clearly the state of completion of the reported results.
Submission should not exceed a maximum 8 pages plus two additional pages
containing references.

Authors are also invited to submit short papers not exceeding 4 pages (plus
two additional pages for references). Short papers should describe:

- A small, focused contribution
- Work in progress
- A negative result
- A position paper

The reviewing process will be double blind and papers should not include the
authors' names and affiliations. Accepted papers will be published in the
workshop proceedings and available at the ACL Anthology.

Submissions must be in PDF format and formatted following the official EMNLP
2016 submission styles

Contributions should be submitted in PDF via the submission site:
https://www.softconf.com/emnlp2016/CNS/

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