Moral Foundations in Tweets

# Moral Foundations in Tweets
# Based on Johnson & Goldwasser, ACL 2018
# Paper: https://aclanthology.org/P18-1067/
# Dataset: https://aclanthology.org/P18-1067/
#
# This task asks annotators to identify moral foundations expressed in tweets
# about social and political issues. Moral Foundations Theory (Haidt, 2012)
# posits six foundational moral dimensions that shape political and social
# reasoning. Annotators classify which foundations are present and whether
# the tweet contains moral content at all.
#
# Moral Foundations:
# - Care/Harm: Concerns about suffering, nurturing, protection
# - Fairness/Cheating: Concerns about justice, rights, reciprocity
# - Loyalty/Betrayal: Concerns about group cohesion, patriotism, self-sacrifice
# - Authority/Subversion: Concerns about hierarchy, respect, tradition
# - Purity/Degradation: Concerns about sanctity, disgust, contamination
# - Liberty/Oppression: Concerns about freedom, autonomy, coercion
#
# Annotation Guidelines:
# 1. Read the tweet and its associated topic
# 2. Determine if the tweet expresses moral sentiment
# 3. If moral, select all applicable moral foundations
# 4. Multiple foundations can co-occur in a single tweet

annotation_task_name: "Moral Foundations in Tweets"
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:
  # Step 1: Is this tweet moral or non-moral?
  - annotation_type: radio
    name: moral_sentiment
    description: "Does this tweet express moral sentiment?"
    labels:
      - "Moral"
      - "Non-Moral"
    keyboard_shortcuts:
      "Moral": "1"
      "Non-Moral": "2"
    tooltips:
      "Moral": "The tweet expresses judgments about right/wrong, good/bad, or moral values"
      "Non-Moral": "The tweet is factual, neutral, or does not invoke moral reasoning"

  # Step 2: Which moral foundations are present?
  - annotation_type: multiselect
    name: moral_foundations
    description: "Which moral foundations are expressed in this tweet? (select all that apply)"
    labels:
      - "Care/Harm"
      - "Fairness/Cheating"
      - "Loyalty/Betrayal"
      - "Authority/Subversion"
      - "Purity/Degradation"
      - "Liberty/Oppression"
    tooltips:
      "Care/Harm": "Concerns about suffering, compassion, cruelty, or protection of the vulnerable"
      "Fairness/Cheating": "Concerns about justice, equal treatment, rights, or proportionality"
      "Loyalty/Betrayal": "Concerns about in-group loyalty, patriotism, or betrayal of the group"
      "Authority/Subversion": "Concerns about respect for authority, tradition, hierarchy, or rebellion"
      "Purity/Degradation": "Concerns about sanctity, purity, contamination, or disgust"
      "Liberty/Oppression": "Concerns about individual freedom, tyranny, coercion, or autonomy"

annotation_instructions: |
  You will be shown tweets about social and political topics. Your task is to:
  1. Determine whether the tweet expresses moral sentiment (moral judgments, values, or ethical reasoning).
  2. If the tweet is moral, identify which moral foundations are present. You may select multiple foundations.

  A tweet is "moral" if it makes judgments about right/wrong, expresses values, or frames issues in moral terms.
  A tweet is "non-moral" if it is purely factual, descriptive, or does not invoke moral reasoning.

html_layout: |
  <div style="padding: 15px; max-width: 800px; margin: auto;">
    <div style="background: #faf5ff; border: 1px solid #e9d5ff; border-radius: 8px; padding: 16px; margin-bottom: 16px;">
      <div style="display: flex; justify-content: space-between; align-items: center; margin-bottom: 8px;">
        <strong style="color: #7e22ce;">Tweet:</strong>
        <span style="background: #f3e8ff; color: #7e22ce; padding: 2px 10px; border-radius: 12px; font-size: 13px;">Topic: {{topic}}</span>
      </div>
      <p style="font-size: 16px; line-height: 1.7; margin: 8px 0 0 0;">{{text}}</p>
    </div>
  </div>

allow_all_users: true
instances_per_annotator: 50
annotation_per_instance: 2
allow_skip: true
skip_reason_required: false