The Hate Speech Detection (HaSpeeDe 2) task is the second edition of a shared task on the detection of hateful content in Italian Twitter messages. HaSpeeDe 2 is composed of a Main task (hate speech detection) and two Pilot tasks,(stereotype and nominal utterance detection). Systems were challenged along two dimensions:(i) time, with test data coming from a different time period than the training data, and (ii) domain, with test data coming from the news domain (ie, news headlines). Overall, 14 teams participated in the Main task, the best systems achieved a macro F1-score of 0.8088 and 0.7744 on the indomain in the out-of-domain test sets, respectively; 6 teams submitted their results for Pilot task 1 (stereotype detection), the best systems achieved a macro F1-score of 0.7719 and 0.7203 on in-domain and outof-domain test sets. We did not receive any submission for Pilot task 2.

Haspeede 2@ evalita2020: Overview of the evalita 2020 hate speech detection task

Irene Russo
2020

Abstract

The Hate Speech Detection (HaSpeeDe 2) task is the second edition of a shared task on the detection of hateful content in Italian Twitter messages. HaSpeeDe 2 is composed of a Main task (hate speech detection) and two Pilot tasks,(stereotype and nominal utterance detection). Systems were challenged along two dimensions:(i) time, with test data coming from a different time period than the training data, and (ii) domain, with test data coming from the news domain (ie, news headlines). Overall, 14 teams participated in the Main task, the best systems achieved a macro F1-score of 0.8088 and 0.7744 on the indomain in the out-of-domain test sets, respectively; 6 teams submitted their results for Pilot task 1 (stereotype detection), the best systems achieved a macro F1-score of 0.7719 and 0.7203 on in-domain and outof-domain test sets. We did not receive any submission for Pilot task 2.
2020
Istituto di linguistica computazionale "Antonio Zampolli" - ILC
hate speech
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/506041
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