A Smart Sentimentality Analysis on Twitter
 
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Publication date: 2019-11-25
 
Eurasian J Anal Chem 2018;13(3):em2018155
 
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ABSTRACT
Depression is a global health concern. Social networks allow the affected population to share their experiences. Social media provides limitless opportunities to share experiences with their best suggestion. In current scenarios and with available new technologies, twitter can be used effectively for gathering information rather than gathering information in traditional method. Twitter is a most popular online social networking service that enable user to share and gain knowledge. This enabled us to accurately represent user interactions by relying on the data’s semantic content. Preprocessed tweets are stored in database and those tweets are identified and classified whether it is user keywords related post using Support Vector Machine classification. The user keywords can be predicted whether it is a best suggestion using polarity. To provide an interactive automatic system which predicts the sentiment of the review/tweets of the people posted in social media. This system deals with the challenges that appear in the process of Sentiment Analysis, real time tweets are considered as they are rich sources of data for opinion mining and sentiment analysis. The main objective of this system is to perform real time sentimental analysis on the tweets that are extracted from the twitter and provide time based analytics to the user.
eISSN:1306-3057