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

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.

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Publication Details

Journal
International Journal of Grid and Utility Computing
Published
2025-01-01
DOI
https://doi.org/10.1504/ijguc.2025.147675
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Zhenbo Zang, Honglei Zhang, Hongjun Zhu
International Journal of Grid and Utility Computing
Big Data and Business Intelligence
article

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

Zhenbo Zang, Honglei Zhang, Hongjun Zhu
article en

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.

International Journal of Grid and Utility ComputingVol. 16(4)
Chongqing Technology and Business University (CN), Chongqing University of Science and Technology (CN), Yangtze Normal University (CN), Chongqing Academy of Science and Technology (CN), Civil Aviation Flight University of China (CN)
Decent work and economic growth
Openalex Percentile: Top 69%
Big Data and Business Intelligence
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