[Corpora-List] Training dataset available - EXIST 2022: task on sEXism Identification in Social neTworks

Jorge Carrillo de Albornoz jcalbornoz at lsi.uned.es
Wed Mar 2 22:46:00 CET 2022


Please consider contributing and/or forwarding to appropriate colleagues and groups.

****We apologize for the multiple copies of this e-mail****

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Call for Participation ----------------------------------------------------------------------------------------------------

TRAINING DATASET RELEASED:

EXIST2022 at IberLEF 2022:

Task: EXIST 2022 - sEXism Identification in Social neTworks

Website: http://nlp.uned.es/exist2022/

It will take place as part of IberLEF 2022, the 4th Workshop on Iberian Languages Evaluation Forum at the SEPLN 2022 Conference, which will be held in September 2022 in Spain.

We are launching the Second Shared Task on sEXism Identification in Social neTworks (EXIST 2022) at IberLEF 2022. The aim of EXIST is to automatically identify sexism content on Twitter. Detecting online sexism may be difficult, as it may be expressed in very different forms. Sexism may sound “friendly”: the statement “Women must be loved and respected, always treat them like a fragile glass” may seem positive, but is actually considering that women are weaker than men. Sexism may sound “funny”, as it is the case of sexist jokes or humour (“You have to love women… just that… You will never understand them.”). Sexism may sound “offensive” and “hateful”, as in “Humiliate, expose and degrade yourself as the fucking bitch you are if you want a real man to give you attention”. Our aim is the detection of sexism in a broad sense, from explicit misogyny to other subtle expressions that involve implicit sexist behaviours. The automatic identification of sexisms in a broad sense may help to create, design and determine the evolution of new equality policies, as well as encourage better behaviors in society.

Participants will be asked to classify “tweets” (in English and Spanish) according to the following two tasks:

Task 1 - The first subtask is a binary classification. The systems have to decide whether or not a given text (tweets) contains sexist expressions or behaviours (i.e., it is sexist itself, describes a sexist situation or criticizes a sexist behaviour).

Task 2 - Once a message has been classified as sexist, the second task aims to categorize the message in different types of sexism (according to the categorization proposed by experts and that takes into account the different facets of women that are undermined). In particular, we propose a five-classification task: (i) IDEOLOGICAL AND INEQUALITY, (ii) STEREOTYPING AND DOMINANCE, (iii) OBJECTIFICATION, (iv) SEXUAL VIOLENCE and (v) MISOGYNY AND NON-SEXUAL VIOLENCE.

Although we recommend participating in both subtasks, participants are allowed to participate just in one of them (e.g., subtask 1).

During the training phase, the task organizers will provide to the participants the manually-annotated EXIST 2021 dataset (tweets and gabs). For the evaluation of the teams, the unlabelled test data will be released (tweets).

We encourage participation from both academic institutions and industrial organizations. We invite the participants to fill this form https://bit.ly/3HpQRKx. You will receive information about how to join the Google Group about the EXIST 2022 shared task.

Important Dates:

* 1 Feb 2022 Registration open * 15 Feb 2022 Training set available. * 22 Mar 2022 Test set available. * 12 Apr 2022 Systems results due to organizers. * 26 Apr 2022 Results notification to participants. * 17 May 2022 Submission of Working Notes by participants. * 31 May 2022 Reviews to participants (peer-reviews). * 16 Jun 2022 Camera-ready due to organizers. * Sep 2022 EXIST at IberLEF 2022

**Note: All deadlines are 11:59PM UTC-12:00 ("anywhere on Earth").**

Organizers: Francisco Rodríguez-Sánchez, Universidad Nacional de Educación a Distancia (UNED) Jorge Carrillo-de-Albornoz, Universidad Nacional de Educación a Distancia (UNED) Laura Plaza, Universidad Nacional de Educación a Distancia (UNED) Julio Gonzalo, Universidad Nacional de Educación a Distancia (UNED) Paolo Rosso, Universitat Politècnica de Valencia (UPV) Damiano Spina, Royal Melbourne Institute of Technology (RMIT) Adrián Mendieta-Aragón, Universidad Nacional de Educación a Distancia (UNED) Guillermo Marco, Universidad Nacional de Educación a Distancia (UNED) Maria Plaza, Collaborator Maryna Makeienko, Universidad Nacional de Educación a Distancia (UNED)

Contact:

Contact the organizers by writing to: jcalbornoz at lsi.uned.es<mailto:jcalbornoz at lsi.uned.es>

Website: http://nlp.uned.es/exist2022/

We invite participants to join the Google group in order to be kept up to date with the latest news related to the task: https://groups.google.com/g/exist2022atiberlef2022

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