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. The task is organized in two related classification subtasks: a main binary subtask for detecting the presence of hate speech, and a finer-grained one devoted to identifying further features in hateful contents such as the aggressive attitude and the target harassed, to distinguish if the incitement is against an individual rather than a group. HatEval has been one of the most popular tasks in SemEval-2019 with a total of 108 submitted runs for Subtask A and 70 runs for Subtask B, from a total of 74 different teams. Data provided for the task are described by showing how they have been collected and annotated. Moreover, the paper provides an analysis and discussion about the participant systems and the results they achieved in both subtasks.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
STUFIIT at SemEval-2019 Task 5: Multilingual Hate Speech Detection on Twitter with MUSE and ELMo Embeddings
We present a number of models used for hate speech detection for Semeval 2019 Task-5: Hateval. We evaluate the viability of multilingual learning for this task. We also experiment with adversarial learning as a means of …
Hate Speech DetectionWord EmbeddingsVista.ue at SemEval-2019 Task 5: Single Multilingual Hate Speech Detection Model
This paper shares insight from participating in SemEval-2019 Task 5. The main propose of this system-description paper is to facilitate the reader with replicability and to provide insightful analysis of the developed sy…
Hate Speech DetectionLT3 at SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter (hatEval)
This paper describes our contribution to the SemEval-2019 Task 5 on the detection of hate speech against immigrants and women in Twitter (hatEval). We considered a supervised classification-based approach to detect hate …
ClassificationGeneral ClassificationHATEMINER at SemEval-2019 Task 5: Hate speech detection against Immigrants and Women in Twitter using a Multinomial Naive Bayes Classifier
This paper describes our participation in the SemEval 2019 Task 5 - Multilingual Detection of Hate. This task aims to identify hate speech against two specific targets, immigrants and women. We compare and contrast the p…
General ClassificationHate Speech DetectionSentenceMITRE at SemEval-2019 Task 5: Transfer Learning for Multilingual Hate Speech Detection
This paper describes MITRE{'}s participation in SemEval-2019 Task 5, HatEval: Multilingual detection of hate speech against immigrants and women in Twitter. The techniques explored range from simple bag-of-ngrams classif…
AllHate Speech DetectionregressionTransfer Learning