
A Research on Detection of Sarcasm using Machine Learning Techniques
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1160.0982s1119
Subject(s) - sarcasm , computer science , artificial intelligence , social media , chatbot , sentiment analysis , machine learning , natural language processing , world wide web , irony , linguistics , philosophy
Today in the era of flooding information on online forums, social media where decision making of customer(user) is assisted in all possible ways. Almost all types of applications have their own assistant or chatbots to guide user for his/her query. Use of assistants and chatbots gives real experience and at the same time for admin it is performing the role of customer care executive. To make it more realistic most of assistants and chatbots are built in conversational format which guide user to get correct information. It is necessary to have knowledge of user sentiments while assistance is provided. Sarcasm is one of complex human sentiment which is used to convey disagreement using positive words. This paper provides review on various approaches used to detect sarcasm present in textual data using supervised and unsupervised approaches of machine learning. It is observed many authors used neural networks algorithms to detect sarcasm. Efficiency and accuracy of detection can be increased with combination of different approaches.