IIIT Hyderabad Publications |
|||||||||
|
Aggression Detection on Social Media Text Using Deep Neural NetworksAuthors: Vinay Singh,Aman Varshney,Syed S. Akhtar,Deepanshu Vijay,Manish Shrivastava Conference: 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP-2018 2018) Location Brussels, Belgium Date: 2018-10-31 Report no: IIIT/TR/2018/99 AbstractIn the past few years, bully and aggressive posts on social media have grown significantly, causing serious consequences for victims/users of all demographics. Majority of the work in this field has been done for English only. In this paper, we introduce a deep learning based classification system for Facebook posts and comments of Hindi-English Code-Mixed text to detect the aggressive behaviour of/towards users. Our work focuses on text from users majorly in the Indian Subcontinent. The dataset that we used for our models is provided by TRAC-1 1 in their shared task. Our classification model assigns each Facebook post/comment to one of the three predefined categories: “Overtly Aggressive”, “Covertly Aggressive” and “Non-Aggressive”. We experimented with 6 classification models and our CNN model on a 10 K-fold cross-validation gave the best result with the prediction accuracy of 73.2%. Full paper: pdf Centre for Language Technologies Research Centre |
||||||||
Copyright © 2009 - IIIT Hyderabad. All Rights Reserved. |