THREAT: A Large Annotated Corpus for Detection of Violent Threats
| Autor: | Erik Velldal, Hugo Lewi Hammer, Lilja Øvrelid, Michael Riegler |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Radicalization
National security Publicly available datasets business.industry Computer science 05 social sciences Perspective (graphical) Internet privacy 02 engineering and technology 0506 political science Annotation 050602 political science & public administration 0202 electrical engineering electronic engineering information engineering Task analysis 020201 artificial intelligence & image processing The Internet Social media Social medias Threat detections Violent threats business Sentence |
| Zdroj: | CBMI |
| Popis: | Understanding, detecting, moderating and in extreme cases deleting hateful comments in online discussions and social media are well-known challenges. In this paper we present a dataset consisting of a total of around 30 000 sentences from around 10 000 YouTube comments. Each sentence is manually annotated as either being a violent threat or not. Violent threats is the most extreme form of hateful communication and is of particular importance from an online radicalization and national security perspective. This is the first publicly available dataset with such an annotation. The dataset can further be useful to develop automatic moderation tools or may even be useful from a social science perspective for analyzing the characteristics of online threats and how hateful discussions evolve. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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