A taxonomy and survey of big data in social media

Author:

Hemmati Atefeh1ORCID,Arzanagh Hanieh Mohammadi2ORCID,Rahmani Amir Masoud3ORCID

Affiliation:

1. Department of Computer Engineering, Science and Research Branch Islamic Azad University Tehran Iran

2. Department of Computer Science and Engineering Shahid Beheshti University Tehran Iran

3. Future Technology Research Center National Yunlin University of Science and Technology Douliou Yunlin Taiwan

Abstract

SummaryExamining the particular value of each platform for big data would be difficult because of the variety of social media forms and sizes. Using social media to objectively and subjectively analyze large groups of individuals makes it the most effective tool for this task. There are numerous sources of big data within the organization. Social media can be identified by the interaction and communication it facilitates. Utilizing social media has become a daily occurrence in modern society. In addition, this frequent use generates data demonstrating the importance of researching the relationship between big data and social media. It is because so many internet users are also active on social media. We conducted a systematic literature review (SLR) to identify 42 articles published between 2018 and 2022 that examined the significance of big data in social media and upcoming issues in this field. We also discuss the potential benefits of utilizing big data in social media. Our analysis discovered open problems and future challenges, such as high‐quality data, information accessibility, speed, natural language processing (NLP), and enhancing prediction approaches. As proven by our investigations of evaluation metrics for big data in social media, the distribution reveals that 24% is related to data‐trace, 12% is related to execution time, 21% to accuracy, 6% to cost, 10% to recall, 11% to precision, 11% to F1‐score, and 5% run time complexity.

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

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