A Combination of Machine Learning and Lexicon Based Techniques for Sentiment Analysis

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Saadat Neshan Seydeh Akram; AKBARI REZA

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2020 | Issue:6

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Title

A Combination of Machine Learning and Lexicon Based Techniques for Sentiment Analysis

Author(s)

Saadat Neshan Seydeh Akram | AKBARI REZA

Keywords

sentiment analysis

classification

opinion mining

Abstract

Today millions of web users put their opinions on the internet about various topics. Development of methods that automatically categorize these opinions to positive, negative or neutral is important. opinion mining or sentiment analysis is known as mining of behavior, opinions and sentiments of the text, chat, etc. using natural language processing and information retrieval methods. The paper is aimed to study the effect of combining machine learning methods in a meta-classifier for sentiment analysis. The machine learning methods use the output of lexicon-based techniques. In this way, the score of SentiWordNet dictionary, Liu’ s sentiment list, SentiStrength and sentimental words ratios are computed and used as the input of machine learning techniques. Adjectives, adverbs and verbs of an opinion are used for opinion modeling and score of these words are extracted from lexicons. Experimental results show that the meta-classifier improve the accuracy of classification 0. 9% and 1. 09% for Amazon and IMDB reviews in comparison with the four machine learning techniques evaluated here.

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APA: Copy

Saadat Neshan, Seydeh Akram, & AKBARI, REZA. (2020). A Combination of Machine Learning and Lexicon Based Techniques for Sentiment Analysis. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/949205/en

Vancouver: Copy

Saadat Neshan Seydeh Akram, AKBARI REZA. A Combination of Machine Learning and Lexicon Based Techniques for Sentiment Analysis. 2020. Available from: https://sid.ir/paper/949205/en

IEEE: Copy

Seydeh Akram Saadat Neshan, and REZA AKBARI, “A Combination of Machine Learning and Lexicon Based Techniques for Sentiment Analysis,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2020, [Online]. Available: https://sid.ir/paper/949205/en

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