Design of a Banking Personalized Recommender System using Sentiment Analysis in Social Media

Ghobakhloo, Mehregan; Rajabzadeh Ghatari, Ali; Toloie Eshlaghy, Abbas; Alborzi, Mahmood

doi:10.22054/IMS.2021.59775.1932

Document Type : Research Paper

Authors

¹ PhD Candidate of Information Technology Management (BI), Department of Management and Economics, Science and Research Branch, Islamic Azad university, Tehran, Iran .Address: Science and Research Branch, Islamic Azad university, Tehran, Iran

² PhD in Production Management, Faculty Member (Full Professor), Department of Management and Economics, Tarbiat Modares University, Tehran, Iran. Address: Tarbiat Modares University, Tehran, Iran

³ PhD in Industrial Management, Faculty Member (Full Professor), Department of Management and Economics, Science and Research Branch, Islamic Azad university, Tehran, Iran

⁴ PhD in Neural Networks, Faculty Member (Associate Professor), Department of Management and Economics, Science and Research Branch, Islamic Azad university, Tehran, Iran.

https://doi.org/10.22054/IMS.2021.59775.1932

Abstract

Customer retention is an important issue for any organization, so finding a way to retain the customer is one of the critical needs of any organization. In this regard, the goal in the field of machine learning is focusing on the problem of accurate customer needs with a method based on extracting opinion and sentiment analysis and quantifying customers' emotional orientation.
In the other words, the issue is designing a recommender system to provide appropriate services to customers, using their opinions and experiences. The proposed solution, by receiving and reviewing customers' opinions and experiences in the form of extracting variables such as user sentiment score for tweets, relation score, cosine similarity, and confidence factor, and considering groups of relevant features and registration ideas in the process of training and testing, the result is presented in the form of a banking service suitable offer. In order to provide a recommending solution, appropriate classification methods are used along with opinion mining methods and an appropriate validation approach, and the final designed system with a small error, in order to provide personalized services, will step in to help bank managers.
Since currently there is no complete provision of banking services tailored to the situation of customers, so in this regard, this mentioned system will be very helpful.

Keywords

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‌ ‌استناد به این مقاله: قباخلو، مهرگان.، رجب‌زاده قطری، علی.، طلوعی اشلقی، عباس.، البرزی، محمود. (1401). طراحی سیستم پیشنهاد بانکی فردی با استفاده از تجزیه و تحلیل احساسات در رسانه‌های اجتماعی ، مطالعات مدیریت کسب وکار هوشمند، 10(39)، 257-289.

DOI: 10.22054/IMS.2021.59775.1932

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Design of a Banking Personalized Recommender System using Sentiment Analysis in Social Media

References

References

Volume 10, Issue 39October 2022Pages 257-289

Volume 10, Issue 39
October 2022
Pages 257-289