Aggression-annotated Corpus of Hindi-English Code-mixed Data
This addresses the need for preventive measures against online aggression like cyberbullying for users in India, but it is incremental as it focuses on creating a dataset rather than a novel detection method.
The authors tackled the problem of detecting aggression in online Hindi-English code-mixed data by developing an annotated corpus from Twitter and Facebook, resulting in a dataset of approximately 18,000 tweets and 21,000 Facebook comments with a hierarchical tagset.
As the interaction over the web has increased, incidents of aggression and related events like trolling, cyberbullying, flaming, hate speech, etc. too have increased manifold across the globe. While most of these behaviour like bullying or hate speech have predated the Internet, the reach and extent of the Internet has given these an unprecedented power and influence to affect the lives of billions of people. So it is of utmost significance and importance that some preventive measures be taken to provide safeguard to the people using the web such that the web remains a viable medium of communication and connection, in general. In this paper, we discuss the development of an aggression tagset and an annotated corpus of Hindi-English code-mixed data from two of the most popular social networking and social media platforms in India, Twitter and Facebook. The corpus is annotated using a hierarchical tagset of 3 top-level tags and 10 level 2 tags. The final dataset contains approximately 18k tweets and 21k facebook comments and is being released for further research in the field.