Hyperbolic Feature-based Sarcasm Detection in Telugu Conversation Sentences

Issues in Analyzing Telugu Sentences towards Building a Telugu Treebank

This paper describes an effort towards building a Telugu Dependency Treebank. We discuss the basic framework and issues we encountered while annotating. 1487 sentences have been annotated in Paninian framework. We also discuss how some of the annotation decisions would effect the development of a parser for Telugu.

Cataloging Telugu Sentences by Hidden Morkov Techniques

The Role of Conversation Context for Sarcasm Detection in Online Interactions

Computational models for sarcasm detection have often relied on the content of utterances in isolation. However, speaker’s sarcastic intent is not always obvious without additional context. Focusing on social media discussions, we investigate two issues: (1) does modeling of conversation context help in sarcasm detection and (2) can we understand what part of conversation context triggered the ...

Tweet Sarcasm: Mechanism of Sarcasm Detection in Twitter

The www is growing at an alarming rate . Users have started participating actively on Internet by giving their opinions on products, services and blogs. Study and analysis of such opinions is known as Opinion Mining. But sometimes users prefer being sarcastic. Sarcasm is a linguistic phenomenon in which people state the opposite of what they actually mean. Sarcasm Detection is a challenging tas...

Sarcasm Suite: A Browser-Based Engine for Sarcasm Detection and Generation

Sarcasm Suite is a browser-based engine that deploys five of our past papers in sarcasm detection and generation. The sarcasm detection modules use four kinds of incongruity: sentiment incongruity, semantic incongruity, historical context incongruity and conversational context incongruity. The sarcasm generation module is a chatbot that responds sarcastically to user input. With a visually appe...