A RECOMMENDER SYSTEM FOR FINANCIAL MOBILE APPS BASED ON SENTIMENT ANALYSIS OF CROWD SOURCED FEEDBACK

Authors

  • Saptaparna Ghosh, Dr Mitali Sengupta, Dr Satyajit Chakrabarti Author

Abstract

This article presents a recommender system for financial mobile apps based on the sentiment analysis of crowd sourced feedback along with country wise comparison. The article explains the benefits and challenges of using crowdsourcing platforms and web search tools to collect and analyze user feedback and ratings of financial mobile apps from different sources, languages, and markets. The article also provides some design and evaluation guidelines for such a system, as well as some ethical and legal considerations. The article aims to help users find the best app for their needs and preferences, as well as to help developers and providers of financial mobile apps to understand and improve their products and services.

Keywords: recommender system, financial mobile apps, sentiment analysis, crowdsourcing, web search, country wise comparison.

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Published

2023-12-21

Issue

Vol. 5 No. 2 (2023)

Section

Articles

How to Cite

A RECOMMENDER SYSTEM FOR FINANCIAL MOBILE APPS BASED ON SENTIMENT ANALYSIS OF CROWD SOURCED FEEDBACK. (2023). Journal of Research Administration, 5(2), 9631-9637. https://journalra.org/index.php/jra/article/view/1058