108 citations · 211 across the 12 of their papers we have counts for
5 papers · 2 filters
`Who would have thought of that!': A Hierarchical Topic Model for Extraction of Sarcasm-prevalent Topics and Sarcasm Detection
Aditya Joshi, Prayas Jain, Pushpak Bhattacharyya +1
Topic Models have been reported to be beneficial for aspect-based sentiment analysis. This paper reports a simple topic model for sarcasm detection, a first, to the best of our kno…
Are Word Embedding-based Features Useful for Sarcasm Detection?
Aditya Joshi, Vaibhav Tripathi, Kevin Patel +2
This paper makes a simple increment to state-of-the-art in sarcasm detection research. Existing approaches are unable to capture subtle forms of context incongruity which lies at t…
A Computational Approach to Automatic Prediction of Drunk Texting
Aditya Joshi, Abhijit Mishra, Balamurali AR +2
Alcohol abuse may lead to unsociable behavior such as crime, drunk driving, or privacy leaks. We introduce automatic drunk-texting prediction as the task of identifying whether a t…
Automatic Identification of Sarcasm Target: An Introductory Approach
Aditya Joshi, Pranav Goel, Pushpak Bhattacharyya +1
Past work in computational sarcasm deals primarily with sarcasm detection. In this paper, we introduce a novel, related problem: sarcasm target identification i.e., extracting the…
Automatic Sarcasm Detection: A Survey
Aditya Joshi, Pushpak Bhattacharyya, Mark James Carman
Automatic sarcasm detection is the task of predicting sarcasm in text. This is a crucial step to sentiment analysis, considering prevalence and challenges of sarcasm in sentiment-b…