July 12, 2023 | BY firojalam
Shared Task On Propaganda And Disinformation Detection In Arabic (co-located with EMNLP 2023)
You are invited to participate ArAIEval shared task on (i) persuasion technique, and (ii) disinformation detection, in Arabic, which will held with the First Arabic Natural Language Processing Conference (WANLP 2023) co-located this with the EMNLP2023 Conference in Singapore (6-10 Dec, 2023). You can find detailed information here: https://araieval.gitlab.io/.
Tasks
February 13, 2023 | BY b.ross
June 26, 2022 | BY Wei Xu
Contact:
Tim Baldwin
Afshin Rahimi
Wei Xu
Alan Ritter
The 8th Workshop on Noisy User-generated Text (WNUT 2022)
The WNUT Workshop will be collocated with COLING 2022 (Hybrid - Gyeongju, Republic of Korea). The website for the workshop is at:
http://noisy-text.github.io/
The WNUT workshop focuses on Natural Language Processing applied to noisy user-generated text, such as that found in social media, online reviews, crowdsourced data, web forums, clinical records, and language learner essays.
February 11, 2022 | BY b.ross
Location:
Co-located with ICWSM 2022
Contact:
Björn Ross
Roberto Navigli
Agostina Calabrese
The automatic or semiautomatic analysis of textual data is a key approach to analyse the massive amounts of user-generated content online, from the identification of sentiment in text and topic classification to the detection of abusive language, misinformation or propaganda. However, the development of such systems faces a crucial challenge.
May 12, 2020 | BY Lun-Wei Ku
Abbreviated Title:
SocialNLP/EmotionGIF Challenge@ACL 2020
Location:
ACL 2020 (online conference)
With the proliferation of animated GIFs in social networks, their importance as a way to express affective states, including emotions, is growing. Given their expressiveness, GIFs offer a more nuanced and precise way to convey emotions.
In this year's EmotionX challenge we present a novel challenge EmotionGIF. Our dataset contains around 40,000 tweets and their GIF responses, labeled with the categories of the animated GIFs provided with the corresponding GIF files. Given unlabeled tweets, the challenge is to predict the category of a GIF response.
Join us now!
April 27, 2020 | BY Wei Xu
Location:
collocated with EMNLP 2020
== The 6th Workshop on Noisy User-generated Text (WNUT 2020) ==
The WNUT Workshop will be collocated with EMNLP 2020 (going virtual!). The website for the workshop is at:
http://noisy-text.github.io/
The WNUT workshop focuses on Natural Language Processing applied to noisy user-generated text, such as that found in social media, online reviews, crowdsourced data, web forums, clinical records and language learner essays. This year, there will be a [shared task] on Named Entity Recognition over Wet-lab Protocols.
December 19, 2019 | BY arkaitz
Contact:
Ahmet Aker
Arkaitz Zubiaga
Kalina Bontcheva
Maria Liakata
Rob Procter
Symeon Papadopoulos
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Third International Workshop on Rumours and Deception in Social Media (RDSM)
held in conjunction with COLING 2020
Barcelona, 14th September 2020
https://www.pheme.eu/rdsm2020/
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++ Important Dates ++
January 15, 2019 | BY dweissen
Contact:
Graciela Gonzalez
Davy Weissenbacher
#SMM4H: Social Media Mining for Health Applications Workshop & Shared Task at ACL 2019
Location: Florence, Italy
Date: August 2, 2019
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call for papers
call for shared task participation
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* Apologies if you received multiple copies of this CFP *
Important links:
Workshop: SMM4H Workshop
July 10, 2018 | BY Wei Xu
Contact:
Wei Xu
Alan Ritter
Tim Baldwin
4th Workshop on Noisy User-generated Text at EMNLP 2018
Call for Papers
The WNUT workshop focuses on Natural Language Processing applied to noisy user-generated text, such as that found in social media, online reviews, crowdsourced data, web forums, clinical records and language learner essays.
April 26, 2018 | BY Wei Xu
Contact:
Wei Xu
Alan Ritter
Tim Baldwin
4th Workshop on Noisy User-generated Text at EMNLP 2018
Call for Papers
The WNUT workshop focuses on Natural Language Processing applied to noisy user-generated text, such as that found in social media, online reviews, crowdsourced data, web forums, clinical records and language learner essays.
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