Title

Machine Learning Approaches to Sentiment Analytics

Abstract

One key aspect of sentiment analytics is emotion classification. This research studies the use of machine learning approaches to classify human emotion. Two different machine learning approaches were compared in an experimental study. In one approach, emotions from both genders were used to train the machine. In another approach, genders were separated and two separate machines were used to learn the emotions of the two genders. We also manipulated the training sample sizes and study the effect of training sample sizes on the two machine learning approaches. Our preliminary results show that the approach where the genders were separated produces a higher accuracy in classifying emotions. We also observe that training sample sizes have different impact on the two approaches.

Meeting Name

12th Midwest Association for Information Systems Conference, MWAIS 2017 (2017: May 18-19, Springfield, IL)

Department(s)

Business and Information Technology

Keywords and Phrases

Sentiment Analytics; Emotion classification; Machine Learning

Document Type

Audio - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2017 Association for Information Systems (AIS), All rights reserved.

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