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Sentimental Analysis on Twitter:Approaches and Techniques


Affiliations
1 Department of Computer Science & IT, Central University, Jammu, India
 

Sentiment is a terminology which define an attitude, opinion, thought, or perception that indicates ones feeling. Sentiment analysis correspondingly called as opinion mining, facilitates the extraction of individual’s sentiment towards certain elements. Now a days, social media applications like Twitter, Facebook etc. has an immense effect on individual lives as people post their thinking in form of posts on these applications. Researchers find Twitter to be the most commonly used social media application to post their opinions. Twitter is a microblogging sites in which a user send messages and those ongoing messages are called Tweets. But these sites carries various technical threats like noise, sparsity, non-standard vocabulary, multilingual content that is posted online. For tackling these challenges, the N-gram technique has been discussed which is used for feature extraction and Support Vector Machine (SVM) approach for classification for sentiment analysis. In this paper a brief introduction on Sentiment Analysis is given along with approaches and techniques. And a workflow on sentiment analysis technique also discussed.

Keywords

Sentiment Analysis, Opinion Mining, Social Media, N-Gram Technique, Support Vector Machine (SVM).
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  • Sentimental Analysis on Twitter:Approaches and Techniques

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Authors

Akankasha
Department of Computer Science & IT, Central University, Jammu, India
Bhavna Arora
Department of Computer Science & IT, Central University, Jammu, India

Abstract


Sentiment is a terminology which define an attitude, opinion, thought, or perception that indicates ones feeling. Sentiment analysis correspondingly called as opinion mining, facilitates the extraction of individual’s sentiment towards certain elements. Now a days, social media applications like Twitter, Facebook etc. has an immense effect on individual lives as people post their thinking in form of posts on these applications. Researchers find Twitter to be the most commonly used social media application to post their opinions. Twitter is a microblogging sites in which a user send messages and those ongoing messages are called Tweets. But these sites carries various technical threats like noise, sparsity, non-standard vocabulary, multilingual content that is posted online. For tackling these challenges, the N-gram technique has been discussed which is used for feature extraction and Support Vector Machine (SVM) approach for classification for sentiment analysis. In this paper a brief introduction on Sentiment Analysis is given along with approaches and techniques. And a workflow on sentiment analysis technique also discussed.

Keywords


Sentiment Analysis, Opinion Mining, Social Media, N-Gram Technique, Support Vector Machine (SVM).

References