3 citations · 8 across the 3 of their papers we have counts for
5 papers
IISERB Brains at SemEval 2022 Task 6: A Deep-learning Framework to Identify Intended Sarcasm in English
Tanuj Singh Shekhawat, Manoj Kumar, Udaybhan Rathore +2
This paper describes the system architectures and the models submitted by our team "IISERBBrains" to SemEval 2022 Task 6 competition. We contested for all three sub-tasks floated f…
Code-switching patterns can be an effective route to improve performance of downstream NLP applications: A case study of humour, sarcasm and hate speech detection
Srijan Bansal, Vishal Garimella, Ayush Suhane +2
In this paper we demonstrate how code-switching patterns can be utilised to improve various downstream NLP applications. In particular, we encode different switching features to im…
What Propels Celebrity Follower Counts? Language Use or Social Connectivity
Jasabanta Patro, Rameshwar Bhaskaran, Animesh Mukherjee
Follower count is a factor that quantifies the popularity of celebrities. It is a reflection of their power, prestige and overall social reach. In this paper we investigate whether…
Characterizing the spread of exaggerated news content over social media
Jasabanta Patro, Sabyasachee Baruah, Vivek Gupta +3
In this paper, we consider a dataset comprising press releases about health research from different universities in the UK along with a corresponding set of news articles. First, w…
Is this word borrowed? An automatic approach to quantify the likeliness of borrowing in social media
Jasabanta Patro, Bidisha Samanta, Saurabh Singh +3
Code-mixing or code-switching are the effortless phenomena of natural switching between two or more languages in a single conversation. Use of a foreign word in a language; however…