A Hybrid Method for Aspect-based Sentiment Analysis in Social Networks

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SALEHI ALI; Rezvanian Alireza

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2023 | Issue:9

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Title

A Hybrid Method for Aspect-based Sentiment Analysis in Social Networks

Author(s)

SALEHI ALI | Rezvanian Alireza

Keywords

Social Networks

Sentiment Analysis

Machine Learning

Clustering

Ensemble Classification

Abstract

In this paper, due to the importance of analyzing users' sentiments in Social Networks, a hybrid method is proposed in 5 steps. In this regard, after pre-processing the text, the VADER dictionary is used to determine the polarity, then BoW and TF-IDF are used for feature extraction. Also, an ensemble classifier based on logistic regression, decision tree, and Naï, ve Bayes is designed, and finally, several Clustering methods are used for aspect-based Sentiment Analysis. For evaluation, the proposed algorithm is conducted on the Amazon, Twitter, and Reddit datasets the results are reported in terms of run-time and precision.

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APA: Copy

SALEHI, ALI, & Rezvanian, Alireza. (). . . SID. https://sid.ir/paper/1046845/en

Vancouver: Copy

SALEHI ALI, Rezvanian Alireza. . . Available from: https://sid.ir/paper/1046845/en

IEEE: Copy

ALI SALEHI, and Alireza Rezvanian, “,” presented at the . , [Online]. Available: https://sid.ir/paper/1046845/en

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