Sentiment Analysis at the Product Feature Level and Based on Users Gender

Mohammadi, Shahriar; Nazemi, Eslam

doi:10.22054/ims.2021.52110.1723

Document Type : Research Paper

Authors

Shahriar Mohammadi ¹
Eslam Nazemi ²

¹ MSc., Information Technology Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran.

² Assistant Professor, Faculty of Computer Engineering and Science, Shahid Beheshti University, Tehran, Iran Corresponding Author: Nazemi@sbu.ac.irCorresponding Author: Nazemi@sbu.ac.ir

https://doi.org/10.22054/ims.2021.52110.1723

Abstract

Social media data is one of the most effective and accurate indicators of public sentiment, so that analyzing this information can provide researchers with interesting results from users' sentiment about characters, subjects, products, and services. In this study, while reviewing users' opinion on Twitter about the various features of two competing mobile phone products on the market, Apple's Iphone X and Samsung's Galaxy S9, we examine their sentiment based on the gender of consumers of these two products. This study is performed using the relation-based method in the feature extraction step and Lexicon-Based in the polarity of opinions step. The results of this study show that the popularity of different product features varies between male and female users, and based on these results, business owners can produce products that focus on people's gender or design smart advertising plan according to their interests. These measures ultimately lead to increased business profitability and customer satisfaction.

Keywords

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‌ ‌استناد به این مقاله: محمدی، شهریار، ناظمی، اسلام. (1400). تجزیه‌وتحلیل احساسات در سطح ویژگی محصول و مبتنی بر جنسیت کاربران، مطالعات مدیریت کسب وکار هوشمند، 10(37)، 267-296.

DOI: 10.22054/IMS.2021.52110.1723

Journal of Business Intelligence Management Studies is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License..

Sentiment Analysis at the Product Feature Level and Based on Users Gender

References

References

Volume 10, Issue 37September 2021Pages 267-296

Volume 10, Issue 37
September 2021
Pages 267-296