Sentiment Analysis of Face Book Statuses
K. Srividya1, A. Mary Sowjanya2
1K. Srividya, Assistant Professor, Department of CSE, Gmrit, Rajam (Andhra Pradesh), India.
2A. Mary Sowjanya, Assistant Professor, Department of CS&SE, Andhra University College of Engineering (A), Visakhapatnam (Andhra Pradesh), India.
Manuscript received on 05 May 2019 | Revised Manuscript received on 17 May 2019 | Manuscript Published on 23 May 2019 | PP: 636-641 | Volume-7 Issue-6S5 April 2019 | Retrieval Number: F11110476S519/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Individuals share their encounters, suppositions or essentially talk pretty much whatever worries them on the web. The extensive measure of accessible information pulls in framework engineers, considering of mining and investigation. Sentiment analysis has popularized due to the availability of abundant opinions that recides in social networks such as Facebook, Twitter, etc. Sentiments are published on these media inform of texts for expressing social support, happiness, anger, friendship etc. A Sentiment is frequently expressed in subtle and complex ways. In addition, data collected from World Wide Web often contains high noise. Sentiment Analysis is treated as a characterization undertaking as it groups the introduction of a content into either positive or negative. In this paper we present sentiment analysis of Facebook statuses using Naive Bayes Classifier and Support Vector Machine (SVM).The essential and basic thought of the paper is that, realizing how individuals feel certain Facebook statuses can be utilized for classification.
Keywords: Analysis Sentiment Machine Facebook Information.
Scope of the Article: Predictive Analysis