Online misogyny has become a universal phenomenon spread widely across social media platforms. Similar to their peers all over the world, women in the Arab region are subjected to several types of online misogyny, through which, gender inequality, violence against women, and underestimation of women are, unfortunately, reinforced and justified (bailey, 2016). The automatic identification of online Arabic misogyny is highly needed to assist in prohibiting the misogynistic Arabic contents and, thus, enabling Arab females to explore social media safely and express their opinions freely (Mulki and Ghanem, 2021). Therefore, we propose Arabic Misogyny Identification (ArMI) task with two sub-tasks to be the first shared task that addresses the problem of automatic identification of Arabic online misogyny. The ArMI shared task aims at identifying the misogynistic content and recognizing different misogynistic behaviors in a collection of Arabic (MSA/dialectal) tweets.

The participants can choose to participate in one or both of the following sub-tasks:

Sub-task A - Misogyny Content Identification:

This sub-task is a coarse-grained binary classification in which the participating systems are required to classify the tweets into two classes, namely:

1. Misogynistic (Misogyny).

2. Non-misogynistic (None).

Sub-task B - Misogyny Behavior Identification:

This sub-task is a fine-grained, multi-class classification of misogynistic behaviors where the misogynistic tweets from the sub-task A are further classified into seven categories:

1. Damning (Damn): tweets under this class contain cursing content.

2. Derailing (Der): tweets under this class combine justification of women abuse or mistreatment.

3. Discredit (Disc): tweets under this class bear slurs and offensive language against women.

4. Dominance (Dom): tweets under this class imply the superiority of men over women.

5. Sexual Harassment (Harass): tweets under this class describe sexual advances and sexual nature abuse.

6. Stereotyping & Objectification (Obj): tweets under this class promote a fixed image of women or describe women's physical appeal.

7. Threat of Violence (Vio): tweets under this class have an intimidating content with threats of physical violence.

8. None: if no misogynistic behaviors exist.

References

• 30th April – Training data release.

• 15th June – Test data release.

• 25th June – Run submission deadline.

• 15th July – Results declared.

• 10th September – Submission of participants' working notes.

• 25th September – Working notes reviews due.

• 5th October – Camera ready version of the working notes to be submitted to FIRE.

• By submitting results to this competition, you consent to the public release of your scores at the ArMI-2021 workshop.

• You accept that the ultimate decision of metric choice and score value is that of the task organisers.

• You further agree that your system may be named according to the team name provided at the time of submission, or to a suitable shorthand as determined by the task organisers.

• You agree not to redistribute the test data except in the manner prescribed by its licence.

Contact

armi2021.sharedtask@gmail.com

Organization committee

• Hala Mulki, ORSAM Center for Middle Eastern Studies, Turkey.

• Bilal Ghanem, University of Alberta, Canada.