MAMI - Multimedia Automatic Misogyny Identification

# MAMI - Multimedia Automatic Misogyny Identification
# Based on Fersini et al., SemEval 2022
# Paper: https://aclanthology.org/2022.semeval-1.74/
# Dataset: https://competitions.codalab.org/competitions/34175
#
# This task asks annotators to identify misogynistic content in memes
# by analyzing both the text overlay and the image description. If
# misogynistic, annotators classify the specific sub-types present.
#
# Binary Classification:
# - Misogynistic: The meme contains misogynistic content
# - Not Misogynistic: The meme does not contain misogynistic content
#
# Sub-type Labels (select all that apply):
# - Stereotype: Reinforces gender stereotypes
# - Shaming: Body-shaming or slut-shaming
# - Objectification: Treats women as objects
# - Violence: Promotes or trivializes violence against women

annotation_task_name: "MAMI - Multimedia Automatic Misogyny Identification"
task_dir: "."

data_files:
  - sample-data.json

item_properties:
  id_key: "id"
  text_key: "text"

output_annotation_dir: "annotation_output/"
output_annotation_format: "json"

port: 8000
server_name: localhost

annotation_schemes:
  - annotation_type: radio
    name: misogyny_label
    description: "Does this meme contain misogynistic content?"
    labels:
      - "Misogynistic"
      - "Not Misogynistic"
    keyboard_shortcuts:
      "Misogynistic": "1"
      "Not Misogynistic": "2"
    tooltips:
      "Misogynistic": "The meme contains content that is hateful, demeaning, or discriminatory toward women"
      "Not Misogynistic": "The meme does not contain misogynistic content"

  - annotation_type: multiselect
    name: misogyny_subtypes
    description: "If misogynistic, select all sub-types that apply"
    labels:
      - "Stereotype"
      - "Shaming"
      - "Objectification"
      - "Violence"
    tooltips:
      "Stereotype": "The meme reinforces harmful gender stereotypes about women"
      "Shaming": "The meme involves body-shaming, slut-shaming, or other forms of shaming women"
      "Objectification": "The meme treats women as objects or reduces them to their physical appearance"
      "Violence": "The meme promotes, trivializes, or jokes about violence against women"

annotation_instructions: |
  You will see a meme's text overlay and a description of its image.
  1. Read both the text and image description carefully.
  2. Determine whether the meme is misogynistic.
  3. If misogynistic, select all applicable sub-types (stereotype, shaming, objectification, violence).
  Note: Consider the combination of text and image, as the misogynistic meaning may emerge from their interaction.

html_layout: |
  <div style="padding: 15px; max-width: 800px; margin: auto;">
    <div style="background: #fef2f2; border: 1px solid #fecaca; border-radius: 8px; padding: 16px; margin-bottom: 16px;">
      <strong style="color: #991b1b;">Meme Text:</strong>
      <p style="font-size: 16px; line-height: 1.7; margin: 8px 0 0 0;">{{text}}</p>
    </div>
    <div style="background: #fefce8; border: 1px solid #fde68a; border-radius: 8px; padding: 16px; margin-bottom: 16px;">
      <strong style="color: #a16207;">Image Description:</strong>
      <p style="font-size: 15px; line-height: 1.6; margin: 8px 0 0 0;">{{image_description}}</p>
    </div>
  </div>

allow_all_users: true
instances_per_annotator: 50
annotation_per_instance: 3
allow_skip: true
skip_reason_required: false