Title: Importance of big data for analysing models in social networks and improving business

Authors: Zhenbo Zang; Honglei Zhang; Hongjun Zhu

Addresses: School of Economics and Management, Chongqing Metropolitan College of Science and Technology, Chongqing, China ' Research Centre of Wuling Mountain Area Characteristic Resources Development and Utilisation, Yangtze Normal University, Chongqing, China ' Graduate Admissions Office, Civil Aviation Flight University of China, Sichuan, China

Abstract: The digital revolution fuels business growth through participatory websites and active user involvement. However, literature lacks emphasis on profitable business-to-business transactions. User knowledge and big data search are valuable. Social media data analysis offers promising research. Technological advances enable commercial storage and analysis of large data volumes. Big data represents real-time, organised, and unstructured data sources. Managing vast networks poses challenges and advantages. Social network data grows daily, providing a rich data pool. This article demonstrates a data framework using text mining and natural language processing for social network big data analysis, achieving 98.30% successful in-time access and simultaneous applications.

Keywords: big data; business-to-business; data analytics; text mining; social networks.

DOI: 10.1504/IJGUC.2025.147675

International Journal of Grid and Utility Computing, 2025 Vol.16 No.4, pp.310 - 324

Received: 15 Aug 2022
Received in revised form: 20 Jan 2023
Accepted: 28 Jan 2023
Published online: 25 Jul 2025 *

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