Author:
Shaila S. G.,Prasanna M. S. M.,Shazia ,Bhavya Shree C.,Arya S.,Deshpande K. P.
Publisher
Springer Nature Singapore
Reference9 articles.
1. Prasanna, MSM, Shaila SG, Vadivel A (2021) Phrase-level sentence patterns for estimating positive and negative emotions using Neuro-fuzzy model for information retrieval applications. Multimed Tools Appl 80:20151–20190
2. Riloff E, Qadir A, Surve P, Silva LD, Gilbert N, Huang R (2013) Sarcasm as contrast between a positive sentiment and negative situation. In: Proceedings of the 2013 conference on empirical methods in natural language processing, pp 704–714
3. Mishra P, Rajnish R, Kumar P (2016) Sentiment analysis of twitter data: case study on digital India, In: International conference on information technology (InCITe‘2016) The next generation it summit on the theme—internet of things: connect your worlds, Noida, pp 148–153. https://doi.org/10.1109/INCITE.2016.7857607
4. Patel A, Patel AA, Butani SG, Sawant PB Literature survey on sentiment analysis of twitter data using machine learning approaches. Int J Innov Res Sci Technol 3(10), ISSN (online): 2349–6010
5. Sonawanea SS, Kolhe SR (2020) TCSD: term cooccurrence based sarcasm detection from twitter trends. Procedia Comput Sci 167:830–839