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SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter
The paper describes the organization of the SemEval 2019 Task 5 about the detection of hate speech against immigrants and women in Spanish and English messages extracted from Twitter, and provides an analysis and discussion about the participant systems and the results they achieved in both subtasks.
Hurtlex: A Multilingual Lexicon of Words to Hurt
A twofold evaluation of HurtLex are provided: a qualitative evaluation against an Italian annotated Twitter corpus of hate against immigrants, and an extrinsic evaluation in the context of the AMI@Ibereval2018 shared task, where the resource was exploited for extracting domain-specific lexicon-based features for the supervised classification of misogyny in English and Spanish tweets.
Resources and benchmark corpora for hate speech detection: a systematic review
- Fabio Poletto, Valerio Basile, M. Sanguinetti, C. Bosco, V. Patti
- Computer ScienceLang. Resour. Evaluation
- 30 September 2020
This review systematically analyze the resources made available by the community at large, including their development methodology, topical focus, language coverage, and other factors, to highlight a heterogeneous, growing landscape.
An Italian Twitter Corpus of Hate Speech against Immigrants
An Impossible Dialogue! Nominal Utterances and Populist Rhetoric in an Italian Twitter Corpus of Hate Speech against Immigrants
An investigation on the role of populist themes and rhetoric in an Italian Twitter corpus of hate speech against immigrants, annotated with four new layers of analysis is proposed.
Overview of the Evalita 2016 SENTIment POLarity Classification Task
- Francesco Barbieri, Valerio Basile, D. Croce, M. Nissim, Nicole Novielli, V. Patti
- Computer ScienceCLiC-it/EVALITA
- 11 December 2014
The SENTIPOLC was the most participated Evalita task with a total of 35 submitted runs from 11 different teams, and the datasets and the evaluation methodology are presented, and results and participating systems are discussed.
SemEval 2018 Task 2: Multilingual Emoji Prediction
This paper describes the results of the first Shared Task on Multilingual Emoji Prediction, organized as part of SemEval 2018, which consists of predicting the most likely emoji to be used along such tweet.
Developing Corpora for Sentiment Analysis: The Case of Irony and Senti-TUT
Senti-TUT-an ongoing Italian project that investigates sentiment and irony in online political discussions-illustrates how to develop corpora for mining and analyzing opinion and sentiment in social…
Misogyny Detection in Twitter: a Multilingual and Cross-Domain Study
Overview of the Task on Stance and Gender Detection in Tweets on Catalan Independence
- M. Taulé, M. A. Martí, F. M. R. Pardo, Paolo Rosso, C. Bosco, V. Patti
- Computer ScienceIberEval@SEPLN
The datasets are presented, which include annotations for dealing with stance and gender, the evaluation methodology, and discuss results and participating systems.