*Introduction and Motivation*
Emotion is a concept that is challenging to describe. Yet, as human beings, we understand the emotional effect situations have or could have on us and other people.
How can we transfer this knowledge to machines? Is it possible to learn the link between situations and the emotions they trigger in an automatic way?
In the light of these questions, we propose the WASSA 2018 Shared Task on Implicit Emotions.
The Shared Task on Implicit Emotion Recognition, organized as part of WASSA 2018 <http://www.wassa2018.com/>at EMNLP 2018 <http://implicitemotions.wassa2018.com/EMNLP%202018>aims at developing models which can recognize the emotion label for a situation described in a text, belonging to the following emotion categories: Anger, Fear, Sadness, Joy, Disgust, Surprise without having access to an explicit mention of an emotion word.
You will be given a tweet from which a certain emotion word is removed. That word is one of the following: "sad", "happy", "disgusted", "surprised", "angry", "afraid" or a synonym of one of them. Your task is to predict the emotion the excluded word expresses: Sadness, Joy, Disgust, Surprise, Anger, or Fear.
With this formulation of the task, we provide data instances which are likely to express an emotion. However, the emotion needs to be inferred from the causal description, which is typically more implicit than an emotion word. We therefore presume that successful systems will take into account world knowledge in a structured or statistical manner.
"It's [#TARGETWORD#] when you feel like you are invisible to others."
"My step mom got so [#TARGETWORD#] when she came home from work and saw that the boys didn't come to Austin with me."
"We are so #[#TARGETWORD#] that people must think we are on good drugsor just really good actors."
9th of February 2018: Publication of sample data set [Done]
15th of March: Publication of training data, development data, and
evaluation script [Done]
1st of June: Codalab competition website goes online
2nd of July 2018: Evaluation period/phase begins (test data released)
9th of July 2018: Evaluation period/phase ends
16th of July 2018: Announcement of results
6th of August 2018: Submission of system description papers for review
17th of August 2018: Reviews due (teams review each other’s submissions)
31st of August 2018: Camera Ready Deadline of System Description:
(same deadline as WASSA main workshop papers)
31st of October 2018 or 1st of November 2018: Workshop in Brussels
at EMNLP 2018
Contact the organizers at iest at wassa2018.com <mailto:iest at wassa2018.com>
Roman Klinger, Evgeny Kim, Institut für Maschinelle
Sprachverarbeitung, University of Stuttgart
(roman.klinger at ims.uni-stuttgart.de, evgeny.kim at ims.uni-stuttgart.de)
Alexandra Balahur, European Commission Joint Research Centre,
Directorate I - Competences Text and Data Mining Unit (I3),
alexandra.balahur at jrc.ec.europa.eu
Saif M. Mohammad, National Research Council Canada,
saif.mohammad at nrc-cnrc.gc.ca
Veronique Hoste, Orphee de Clercq, Department of Translation,
Interpreting and Communication LT³ - Language and Translation
Technology Team, veronique.hoste at ugent.be, orphee.declercq at ugent.be
Participation and More Information
Please register in our Google Group at
Fill out the form at https://goo.gl/forms/HXe6rloBkhbsdv6l2to get
access to training data.
All information will be shared in the Google Group. Updates will also be shared on our Twitter account at https://twitter.com/wassa_2018
More information is available on our website: http://implicitemotions.wassa2018.com/
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