108 citations · 707 across the 92 of their papers we have counts for
10 papers · 1 filter
`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…
Faster decoding for subword level Phrase-based SMT between related languages
Anoop Kunchukuttan, Pushpak Bhattacharyya
A common and effective way to train translation systems between related languages is to consider sub-word level basic units. However, this increases the length of the sentences res…
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…
Orthographic Syllable as basic unit for SMT between Related Languages
Anoop Kunchukuttan, Pushpak Bhattacharyya
We explore the use of the orthographic syllable, a variable-length consonant-vowel sequence, as a basic unit of translation between related languages which use abugida or alphabeti…
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…