[Corpora-List] The 2nd Workshop on Noisy User-generated Text (WNUT'16): Call for Paper

Wei Xu xwe at cis.upenn.edu
Wed Jul 6 19:36:27 CEST 2016

== The 2nd Workshop on Noisy User-generated Text (WNUT'16) ==

The WNUT Workshop will be held with COLING in Osaka, Japan, on December 11, 2016. The website for the workshop is at:


WNUT workshop focuses on Natural Language Processing applied to noisy user-generated text, such as that found in social media, web forums, online reviews, clinic records and language learner essays. This year, there will be two *shared tasks*: 1) Geolocation Prediction in Twitter and 2) Named Entity Recognition in Twitter.

We seek submissions of both long and short papers on original and unpublished work (same page limit as COLING main conference). 1-page abstracts on work-in-progress or work published elsewhere are also welcome and will *not* be included in the conference proceedings. All accepted submissions will be presented as posters. Additionally, selected submissions will be presented orally.

Topics of interest include but are not limited to:

* NLP Preprocessing of Noisy Text

- Part of speech tagging

- Named entity tagging, including a wide range of categories, e.g. product names

- Chunking of user-generated text

- Parsing * Text Normalization and Error Correction

- Normalizing noisy text for downstream tasks and for human readability

- Error detection and correction * Paraphrase extraction and detection in noisy text * Semantics in noisy text * Bilingual translation of noisy text * Multilingual NLP in noisy text * Colloquial language, e.g. idiom detection * Domain adaptation to user-generated text


* January 24 2015: First call for workshop papers * September 2016: Shared-task evaluations * September 25, 2016: Workshop paper due * October 16, 2016: Notification of acceptance * October 30, 2016: Camera-ready papers due * December 11, 2016: Workshop date


* Task #1: Geolocation Prediction in Twitter (around September) * Task #2: Named Entity Recognition in Twitter (September 9-16 )


Bo Han (Hugo AI) Alan Ritter (The Ohio State University) Leon Derczynski (The University of Sheffield) Wei Xu (University of Pennsylvania) Tim Baldwin (The University of Melbourne)


Ming-Wei Chang (Microsoft Research) Barbara Plank (University of Copenhagen) Kentaro Torisawa (National Institute of Information and Communications Technology)


Kalina Bontcheva (University of Sheffield) Claire Cardie (Cornell University) Colin Cherry (National Research Council Canada) Grzegorz Chrupała (Tilburg University) Marina Danilevsky (IBM Research) Seza Doğruöz (Tilburg University) Heba Elfardy (Columbia University) Eric Fosler-Lussier (The Ohio State University) Kevin Gimpel (Toyota Technological Institute at Chicago) Weiwei Guo (Yahoo! Research) Ben Hachey (Hugo AI) Masato Hagiwara (Duolingo) Ed Hovy (Carnegie Mellon University) Jing Jiang (Singapore Management University) Nobuhiro Kaji (Yahoo! Research) Emre Kiciman (Microsoft Research) Chen Li (University of Texas at Dallas) Wang Ling (Google DeepMind) Huan Liu (Arizona State University) Rada Mihalcea (University of Michigan) Smaranda Muresan (Columbia University) Naoaki Okazaki (Tohoku University) Miles Osborne (Bloomberg) Ellie Pavlick (University of Pennsylvania) Daniel Preoţiuc-Pietro (University of Pennsylvania) Will Radford (Hugo AI) Alla Rozovskaya (City University of New York) Andrew Schwartz (Stony Brook University) Djamé Seddah (University Paris-Sorbonne) Richard Sproat (Google Research) Anders Søgaard (University of Copenhagen) Jeniya Tabassum (The Ohio State University) Joel Tetreault (Yahoo! Research) Byron C. Wallace (University of Texas at Austin) Svitlana Volkova (Pacific Northwest National Laboratory) Xiaojun Wan (Peking University) Jun-Ming Xu (University of Wisconsin-Madison) Diyi Yang (Carnegie Mellon University) Yi Yang (Georgia Tech) Guido Zarrella (MITRE) Ming Zhou (Microsoft Research)


Formatting should be according to COLING 2016 specifications. Dual submission is allowed, but must state at the time of submission.

Please submit through the START system at the following url:

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