paper-with-me

홈 › Papers

Developing a Multilingual Annotated Corpus of Misogyny and Aggression

2020-03-16 · LREC 2020 5 · Shiladitya Bhattacharya, Siddharth Singh, Ritesh Kumar, Akanksha Bansal, Akash Bhagat, Yogesh Dawer, Bornini Lahiri, Atul Kr. Ojha

In this paper, we discuss the development of a multilingual annotated corpus of misogyny and aggression in Indian English, Hindi, and Indian Bangla as part of a project on studying and automatically identifying misogyny and communalism on social media (the ComMA Project). The dataset is collected from comments on YouTube videos and currently contains a total of over 20,000 comments. The comments are annotated at two levels - aggression (overtly aggressive, covertly aggressive, and non-aggressive) and misogyny (gendered and non-gendered). We describe the process of data collection, the tagset used for annotation, and issues and challenges faced during the process of annotation. Finally, we discuss the results of the baseline experiments conducted to develop a classifier for misogyny in the three languages.

📄 PDF Abstract BibTeX arXiv:2003.07428

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Aggression and Misogyny Detection using BERT: A Multi-Task Approach

2020-05-01 · LREC 2020 5 · Niloofar Safi Samghabadi, Parth Patwa, Srinivas Pykl, Prerana Mukherjee 외

In recent times, the focus of the NLP community has increased towards offensive language, aggression, and hate-speech detection.This paper presents our system for TRAC-2 shared task on {``}Aggression Identification{''} (…

Abusive LanguageAggression IdentificationHate Speech DetectionMisogynistic Aggression Identification+1

An Efficient BERT Based Approach to Detect Aggression and Misogyny

2021-12-01 · ICON 2021 12 · Sandip Dutta, Utso Majumder, Sudip Naskar

Social media is bustling with ever growing cases of trolling, aggression and hate. A huge amount of social media data is generated each day which is insurmountable for manual inspection. In this work, we propose an effic…

The ComMA Dataset V0.2: Annotating Aggression and Bias in Multilingual Social Media Discourse

2021-11-19 · LREC 2022 6 · Ritesh Kumar, Enakshi Nandi, Laishram Niranjana Devi, Shyam Ratan 외

In this paper, we discuss the development of a multilingual dataset annotated with a hierarchical, fine-grained tagset marking different types of aggression and the "context" in which they occur. The context, here, is de…

Aggression Identification

LaSTUS/TALN at TRAC - 2020 Trolling, Aggression and Cyberbullying

2020-05-01 · LREC 2020 5 · L{\"u}tfiye Seda Mut Alt{\i}n, Alex Bravo, Horacio Saggion

This paper presents the participation of the LaSTUS/TALN team at TRAC-2020 Trolling, Aggression and Cyberbullying shared task. The aim of the task is to determine whether a given text is aggressive and contains misogynis…

Misogyny classification of German newspaper forum comments

2022-11-30 · Johann Petrak, Brigitte Krenn

This paper presents work on detecting misogyny in the comments of a large Austrian German language newspaper forum. We describe the creation of a corpus of 6600 comments which were annotated with 5 levels of misogyny. Th…

Classification