17 citations · 48 across the 7 of their papers we have counts for
8 papers
Figurative Usage Detection of Symptom Words to Improve Personal Health Mention Detection
Adith Iyer, Aditya Joshi, Sarvnaz Karimi +2
Personal health mention detection deals with predicting whether or not a given sentence is a report of a health condition. Past work mentions errors in this prediction when symptom…
A Comparison of Word-based and Context-based Representations for Classification Problems in Health Informatics
Aditya Joshi, Sarvnaz Karimi, Ross Sparks +2
Distributed representations of text can be used as features when training a statistical classifier. These representations may be created as a composition of word vectors or as cont…
Survey of Text-based Epidemic Intelligence: A Computational Linguistic Perspective
Aditya Joshi, Sarvnaz Karimi, Ross Sparks +2
Epidemic intelligence deals with the detection of disease outbreaks using formal (such as hospital records) and informal sources (such as user-generated text on the web) of informa…
`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…
Towards Sub-Word Level Compositions for Sentiment Analysis of Hindi-English Code Mixed Text
Ameya Prabhu, Aditya Joshi, Manish Shrivastava +1
Sentiment analysis (SA) using code-mixed data from social media has several applications in opinion mining ranging from customer satisfaction to social campaign analysis in multili…
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…