ISSN 2394-5125
 

Review Article 


Sentiment Analysis of Social and Topic Context Using Machine Learning Techniques

Ratna Patil, Ms. Sonia Arora.

Abstract
Sentiment Analysis could be a new area in research and is beneficial in many other fields. In the
present time, a large amount of textual data is collected using surveys, comments, and reviews online. All
the collected data are employed to enhance the items and services provided by both public and private
organizations around the world. This Paper introduces a sentiment analysis of social and context reviews using
feature-based opinion mining and supervised machine learning. The Sentiment Analysis techniques are to function
on a series of expressions for a given item that supported the product quality, and item features. Sentiment analysis
is additionally called Opinion mining because of the significant volume of opinion. Analyzing customer opinion
is extremely important to rate the items. To automate rate the opinions within the type of unstructured data is been
a challenging problem today. Social context and topic context are combined by the Laplacian matrix of the graph
built by these contexts and Laplacian regularization is added into the microblog sentiment analysis model.
Experimental results on two real Twitter data sets demonstrate that our proposed model can outperform baseline
methods consistently and significantly. Various topics beyond item reviews like online shopping, stock markets,
elections, disasters, medicine, software engineering, and Cyberbullying extend the utilization of sentiment
analysis.

Key words: Sentiment Analysis, Data Mining, Text Mining, Opinion Mining, Natural Language Processing.


 
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Pubmed Style

Ratna Patil, Ms. Sonia Arora. Sentiment Analysis of Social and Topic Context Using Machine Learning Techniques. JCR. 2020; 7(10): 1255-1260. doi:10.31838/jcr.07.10.247


Web Style

Ratna Patil, Ms. Sonia Arora. Sentiment Analysis of Social and Topic Context Using Machine Learning Techniques. http://www.jcreview.com/?mno=12205 [Access: August 18, 2021]. doi:10.31838/jcr.07.10.247


AMA (American Medical Association) Style

Ratna Patil, Ms. Sonia Arora. Sentiment Analysis of Social and Topic Context Using Machine Learning Techniques. JCR. 2020; 7(10): 1255-1260. doi:10.31838/jcr.07.10.247



Vancouver/ICMJE Style

Ratna Patil, Ms. Sonia Arora. Sentiment Analysis of Social and Topic Context Using Machine Learning Techniques. JCR. (2020), [cited August 18, 2021]; 7(10): 1255-1260. doi:10.31838/jcr.07.10.247



Harvard Style

Ratna Patil, Ms. Sonia Arora (2020) Sentiment Analysis of Social and Topic Context Using Machine Learning Techniques. JCR, 7 (10), 1255-1260. doi:10.31838/jcr.07.10.247



Turabian Style

Ratna Patil, Ms. Sonia Arora. 2020. Sentiment Analysis of Social and Topic Context Using Machine Learning Techniques. Journal of Critical Reviews, 7 (10), 1255-1260. doi:10.31838/jcr.07.10.247



Chicago Style

Ratna Patil, Ms. Sonia Arora. "Sentiment Analysis of Social and Topic Context Using Machine Learning Techniques." Journal of Critical Reviews 7 (2020), 1255-1260. doi:10.31838/jcr.07.10.247



MLA (The Modern Language Association) Style

Ratna Patil, Ms. Sonia Arora. "Sentiment Analysis of Social and Topic Context Using Machine Learning Techniques." Journal of Critical Reviews 7.10 (2020), 1255-1260. Print. doi:10.31838/jcr.07.10.247



APA (American Psychological Association) Style

Ratna Patil, Ms. Sonia Arora (2020) Sentiment Analysis of Social and Topic Context Using Machine Learning Techniques. Journal of Critical Reviews, 7 (10), 1255-1260. doi:10.31838/jcr.07.10.247