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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 6, ISSUE 12, DECEMBER 2017

Machine Learning Impact on Sentiment Analysis of Tweets: A Review

Punita Bhardwaj, Aman Kumar, Astha Gautam

DOI: 10.17148/IJARCCE.2017.61236

Abstract: Tweet sentiment analysis is an effective and valuable technique in the sentiment analysis domain. It is the most extensively used approach for tweet sentiment analysis. Machine learning algorithms and Sentiment analysis of tweets are an application of mining Twitter and it is growing in popularity as a means of determining public opinion. Machine learning algorithms are used to perform sentiment analysis; however, data quality issues such as high dimensionality, class imbalance or noise may negatively impact on classifier performance. Machine learning techniques are for targeting these problems but it has not been applied to this domain or studied in detail.



Keywords: Machine learning, sentiment,optimization,tweets

How to Cite:

[1] Punita Bhardwaj, Aman Kumar, Astha Gautam, “Machine Learning Impact on Sentiment Analysis of Tweets: A Review,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2017.61236