An ensemble approach to stabilize the features for multi-domain sentiment analysis using supervised machine learning-Reference-Cited by-同舟云学术

An ensemble approach to stabilize the features for multi-domain sentiment analysis using supervised machine learning

Published:2018-11-14 Issue:1 Volume:5 Page:
ISSN:2196-1115
Container-title:Journal of Big Data
language:en
Short-container-title:J Big Data

Author:

Ghosh Monalisa^ORCID,Sanyal Goutam

Publisher

Springer Science and Business Media LLC

Subject

Information Systems and Management,Computer Networks and Communications,Hardware and Architecture,Information Systems

Link

http://link.springer.com/content/pdf/10.1186/s40537-018-0152-5.pdf

Reference44 articles.

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3. Liu B. Sentiment analysis and subjectivity. In: Indurkhya N, Damerau FJ, editors. Invited chapter for the handbook of natural language processing. 2nd ed. England: Taylor & Francis; 2010.

4. Dhaoui C, Webster CM, Tan LP. Social media sentiment analysis: lexicon versus machine learning. J Consumer Mark. 2017;34(6):480–8.

5. Samal BR, Behera AK, Panda M. Performance analysis of supervised machine learning techniques for sentiment analysis. In: Proceedings of the 1st ICRIL international conference on sensing, signal processing and security (ICSSS). Piscataway: IEEE; 2017. p. 128–3.

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