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A novel framework for remote management of social media big data analytics

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Abstract

With the rapid expansion of social media users and the ever-increasing data exchange between them, the era of big data has arrived. Integration of big data generates enormous benefits, making it a hotspot for research. However, big data demonstrates the heterogeneity brought on by multiple data sources. Big data integration is constrained by multi-source heterogeneous data. Moreover, the rise in the volume of social media data is affecting the efficiency of data integration. This study is concerned with developing a novel framework for data integration system that can manage the heterogeneity of massive social media data. The framework is comprised of four layers: data source layer, application layer, resource layer, and visualization layer. The framework establishes correlations between data stored in distributed data sources. We used RESTful APIs to offer end-users with reliable and effective web-based access to data using unique queries. The framework was evaluated based on firsthand impressions of test users, who answered a standardized set of questions after testing real-world inputs.

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Data Availability

The materials used in this study are available at https://github.com/AlShomar/AlShomar-Big-Data-Integration-Framework.

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Authors and Affiliations

  1. University of Hail, Hail, Saudi Arabia

    Ahmad M. Al-Shomar

  2. Research and Innovation Division, Elm Company, Riyadh, Saudi Arabia

    Muhammad Al-Qurish

  3. University of North Texas, Denton, USA

    Wajdi Aljedaani

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  1. Ahmad M. Al-Shomar
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  2. Muhammad Al-Qurish
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  3. Wajdi Aljedaani
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Correspondence to Ahmad M. Al-Shomar.

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Al-Shomar, A.M., Al-Qurish, M. & Aljedaani, W. A novel framework for remote management of social media big data analytics. Soc. Netw. Anal. Min. 12, 172 (2022). https://doi.org/10.1007/s13278-022-00996-4

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