Publications (10)
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…
CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities
Ye Zhu, Kai Ming Ting, Mark Carman +1
The problem of inhomogeneous cluster densities has been a long-standing issue for distance-based and density-based algorithms in clustering and anomaly detection. These algorithms…
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…
Expect the unexpected: Harnessing Sentence Completion for Sarcasm Detection
Aditya Joshi, Samarth Agrawal, Pushpak Bhattacharyya +1
The trigram `I love being' is expected to be followed by positive words such as `happy'. In a sarcastic sentence, however, the word `ignored' may be observed. The expected and the…
SIR-Hawkes: Linking Epidemic Models and Hawkes Processes to Model Diffusions in Finite Populations
Marian-Andrei Rizoiu, Swapnil Mishra, Quyu Kong +2
Among the statistical tools for online information diffusion modeling, both epidemic models and Hawkes point processes are popular choices. The former originate from epidemiology,…