HUrtful HUmour (HUHU): Detection of humour spreading prejudice in Twitter
Creators
- 1. PRHLT Research Center, Universitat Politècnica de València
Description
In HUHU, our focus is on examining automatically the use of humor to express prejudice towards minorities, specifically analyzing Spanish tweets that are prejudicial towards:
- Women and feminists
- LGBTIQ community
- Immigrants and racially discriminated people
- Overweight people
For this, we propose 3 subtasks :
1-HUrtful HUmour Detection:
The first subtask consists in determining whether a prejudicial tweet is intended to cause humour. Participants will have to distinguish between tweets that using humour express prejudice and tweets that express prejudice without using humour. For this, the systems will be evaluated and ranked employing the F1-measure over the positive class.
2A-Prejudice Target Detection:
Taking into account the minority groups analyzed, i.e, Women and feminists, LGBTIQ community and Immigrants, racially discriminated people, and overweight people, participants are asked to identify the targeted groups on each tweet as a multilabel classification task. The metric employed for the second task will be Weighted-F1.
2B-Degree of Prejudice Prediction:
The third subtask consists of predicting on a continuous scale from 1 to 5 to evaluate how prejudicial the message is on average among minority groups. We will evaluate the submitted predictions employing the Root Mean Squared Error.
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Additional details
References
- Merlo, L.I., Chulvi, B., Ortega-Bueno, R., & Rosso, P. (2022) When Humour Hurts: Linguistic Features to Foster Explainability. In: Procesamiento del Lenguaje Natural (SEPLN), num. 70 (accepted)
- Merlo, L. (2022). When Humour Hurts: A Computational Linguistic Approach. Final degree project, Universitat Politècnica de València.
- Jones, E. (1972). Prejudice and Racism. Addinson-Wesley.
- S. Frenda, A. Cignarella A., V. Basile, C. Bosco, V. Patti, & P. Rosso (2022). The Unbearable Hurtfulness of Sarcasm. Expert Systems with Applications (ESWA), 193.
- Castro, S., Chiruzzo, L., & Rosá, A. (2018). Overview of the HAHA Task: Humor Analysis Based on Human Annotation at IberEval 2018. IberEval@SEPLN.
- Chiruzzo, L., Castro, S., Etcheverry, M., Garat, D., Prada, J.J., & Rosá, A. (2019). Overview of HAHA at IberLEF 2019: Humor Analysis Based on Human Annotation. IberLEF@SEPLN.
- Chiruzzo, L., Castro, S., Góngora, S., Rosá, A., Meaney, J. A., & Mihalcea, R. (2021). Overview of HAHA at Iberlef 2021: Detecting, Rating and Analyzing Humor in spanish. Procesamiento del Lenguaje Natural, 67, 257-268.
- Ortega-Bueno, R., Chulvi, B., Rangel, F., Rosso, P., & Fersini, E. (2022). Profiling Irony and Stereotype Spreaders on Twitter (IROSTEREO) at PAN 2022. CEUR-WS. org.
- Meaney, J., Wilson, S., Chiruzzo, L., Lopez, A., & Magdy, W. (2021). SemEval 2021 Task 7: HaHackathon, Detecting and Rating Humor and Offense. In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021) (pp. 105–119). Association for Computational Linguistics.
- Fersini, E., Gasparini, F., Rizzi, G., Saibene, A., Chulvi, B., Rosso, P., Lees, A., & Sorensen, J. (2022). SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022) (pp. 533–549). Association for Computational Linguistics.
- Sibley, C., & Barlow, F. (Eds.). (2016). The Cambridge Handbook of the Psychology of Prejudice (Cambridge Handbooks in Psychology). Cambridge: Cambridge University Press. doi:10.1017/CBO9781316161579