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Tan, Yuting and Madisetti, Vijay K. (2024) User Profile & Attitude Analysis Based on Unstructured Social Media and Online Activity. Journal of Software Engineering and Applications, 17 (06). pp. 463-473. ISSN 1945-3116

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Abstract

As social media and online activity continue to pervade all age groups, it serves as a crucial platform for sharing personal experiences and opinions as well as information about attitudes and preferences for certain interests or purchases. This generates a wealth of behavioral data, which, while invaluable to businesses, researchers, policymakers, and the cybersecurity sector, presents significant challenges due to its unstructured nature. Existing tools for analyzing this data often lack the capability to effectively retrieve and process it comprehensively. This paper addresses the need for an advanced analytical tool that ethically and legally collects and analyzes social media data and online activity logs, constructing detailed and structured user profiles. It reviews current solutions, highlights their limitations, and introduces a new approach, the Advanced Social Analyzer (ASAN), that bridges these gaps. The proposed solution’s technical aspects, implementation, and evaluation are discussed, with results compared to existing methodologies. The paper concludes by suggesting future research directions to further enhance the utility and effectiveness of social media data analysis.

Item Type: Article
Subjects: GO for ARCHIVE > Engineering
Depositing User: Unnamed user with email support@goforarchive.com
Date Deposited: 08 Jun 2024 10:02
Last Modified: 08 Jun 2024 10:02
URI: http://eprints.go4mailburst.com/id/eprint/2289

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