Aggressiveness analysis in Estonian Tweets: A Benchmark Dataset and Baselines
Organization
TartuNLP
Abstract
The importance of the detection of aggressiveness in social media is due to the real effects of violence provoked by negative behavior online. As a result, research on safety and security in social media has grown substantially in the last decade. A particularly relevant aspect of this work is detecting and preventing the use of various forms of abusive language in blogs, micro-blogs, and social networks.
This proposal involves: i) creating a benchmark dataset by annotating Estonian tweets, ii) proposing neural baselines.
Outcome: a benchmark dataset and baselines for Aggressiveness detection in the context of social media data in Estonian.
This proposal involves: i) creating a benchmark dataset by annotating Estonian tweets, ii) proposing neural baselines.
Outcome: a benchmark dataset and baselines for Aggressiveness detection in the context of social media data in Estonian.
Graduation Theses defence year
2022-2023
Supervisor
Somnath Banerjee, Rajesh Sharma
Spoken language (s)
Requirements for candidates
Level
Bachelor, Masters
Keywords
Application of contact
Name
Somnath Banerjee, Rajesh Sharma
Phone