Employee Sentiment Analysis Using Naive Bayes Classifier
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

Research Paper | Information Technology | Indonesia | Volume 7 Issue 5, May 2018

Employee Sentiment Analysis Using Naive Bayes Classifier

Dessy Monica Ginting, Andry Alamsyah

People today tend to use social media as their platform to share reviews or opinions, including about their work. Therefore, public opinion and sentiments are some of the most important factors for a company to take advantage of. It can be used as a source to be analyzed and extracted to valuable insights. When used appropriately, employee sentiment analysis can provide more effective tools for determining key factors such as job satisfaction than internal surveys or other conventional methods. By getting a clearer picture of employee sentiment, companies can identify areas where employees are dissatisfied and devise strategies to increase engagement and, in turn, improve employee productivity and retention.

Keywords: Text Mining, Sentiment Analysis, Data Classification, Naive Bayes Classifier

Edition: Volume 7 Issue 5, May 2018

Pages: 1676 - 1679

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How to Cite this Article?

Dessy Monica Ginting, Andry Alamsyah, "Employee Sentiment Analysis Using Naive Bayes Classifier", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=ART20182855, Volume 7 Issue 5, May 2018, 1676 - 1679

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