Subdirected acyclic category graphgroup Identification

1. Automatic detection of hate speech in text: an overview of the topic and dataset annotation with hierarchical classes
2. Understanding Abuse:A Typology of Abusive Language Detection Subtasks
3. Predicting the Type and Target of Offensive Posts in Social Media

Number	Data Set	Goal	Method	Conclusion	Remarks
1.	Crawled twitter using hate profiles and enumerated words	Detect hate speech using directed acyclic category graph to aid annotation to further distinguish sub-groups within hate speech, to help annotation
2.	NA	propose a typol-ogy that captures central similarities anddifferences between subtasks and we dis-cuss its implications for data annotationand feature construction			Generalized, directed, implicit and explicit