Dear corpora-list members,

We are glad to announce SemEval shared task 11: Bridging the Gap in Text-Based Emotion Detection. New textual datasets will be provided for 33 languages: Afrikaans, Algerian Arabic, Amharic, Hausa, Igbo, Kinyarwanda, Moroccan Arabic, Mozambican Portuguese, Nigerian-Pidgin, Oromo, Setswana, Somali, Swahili, Tigrinya,Xitsonga, isiXhosa, Yoruba, isiZulu, Modern Standard Arabic, Chinese, Hindi, Indonesian, Javanese, Marathi English, German, Romanian, Russian, Latin American Spanish, Tatar, Ukrainian, Swedish Brazilian Portuguese.

This shared task is on perceived emotion and focuses on:

• Determining what emotion most people will think the speaker may be feeling given a sentence or short text snippet uttered by the speaker.

The task is not about:

• The emotion evoked in the reader.

• The emotion of someone else mentioned in the text.

• Or even the true emotion of the speaker (which cannot be definitively known from just a short text snippet).

  
  

We acknowledge the importance of this distinction as perceived emotions can differ from actual emotions due to various factors such as cultural context, individual differences in emotional expression, and the limitations of text-based communication. (See more here.)

Participants can participate in one or more of the following tracks:

Track A: Multi-label Emotion Detection

Given a target text snippet, predict the perceived emotion(s) of the speaker. A training dataset with gold emotion labels will be provided for this track.

Track B: Emotion Intensity

Given a target text and a target perceived emotion, predict the intensity for each of the classes.

Track C: Cross-lingual Emotion Detection

Given a labeled training set in one of the languages, predict the perceived emotion labels of a new text instance in a different target language.

Important Dates and Phases of the Task

Data

Available on https://github.com/emotion-analysis-project/SemEval2025-Task11

Useful Links for the participants

Twitter/X  @EmoSemEval2025

FAQs and Terms and Conditions 

Competition webpage https://www.codabench.org/competitions/3863/