Sentiment Analysis of Facebook Posts using Hybrid Method
Swarnangini Sinha1, Kanak Saxena2, Nisheeth Joshi3 

1Swarnangini Sinha, Department of Computer Science, Banasthali Vidyapith, Rajasthan, India.
2Dr. Kanak Saxena, Department of Computer Application, Samrat Ashok Technological Institute, Vidisha, M.P., India.
3Dr. Nisheeth Joshi, Department of Computer Science, Banasthali Vidyapith, Rajasthan, India.

Manuscript received on 01 March 2019 | Revised Manuscript received on 06 March 2019 | Manuscript published on 30 July 2019 | PP: 2421-2428 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1969078219/19©BEIESP | DOI: 10.35940/ijrte.B1969.078219
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Abstract: Social Media is a popular medium of communication amongst youngsters to remain connected with their friends. Facebook is one of the most preferred Social Media Sites which store the gigantic amount of data which can be explored for Sentiment Analysis. In this study, we have applied hybrid analysis approach which combines the best features of a lexical analysis and SVM machine learning classification algorithm on Facebook Posts. The analysis is further improved by incorporating language discourse features to detect intensity of sentiment and the prominent emotions expressed through these posts.
Index Terms: Emotion Lexicons, Hybrid Analysis, Sentiment Analysis, Social Networking Sites, Support Vector Machine.

Scope of the Article: Social Networks