Conceptual usage model of big data generated by social media

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Jolanta SabaitytÄ—
Roberta Karpovičiūtė


The digital revolution and the communication platforms provided by the Web 2.0 virtual space era, such as social media, social networks, other tools and channels, create new opportunities for better marketing decisions based on user-generated data analysis. Every day customers of social media and other virtual tools are creating huge amounts of their actions-caused data, and businesses lack management tools supporting this process, which could create knowledge in the areas of deeper cognitive customer profiles and preferences. The growing number of social media users indicates the popularity of these communication tools among the information society, but science today lacks a deeper knowledge of social media-generated data and other algorithms for this kind of data usage. Therefore, the purpose of the article can be defined as the development of a conceptual model of big data generated by social media usage in business. The formation of the conceptual model is based on the analysis of big data assumptions and application possibilities, social media classification peculiarities and different channel specifics, identification of big data analysis methods and analysis of big data applications generated by social media. The conceptual model creates preconditions for deeper knowledge of user-generated big data in nowadays’ widely used communication platforms, as well as creation of the decision support tool for marketing specialists in order to use big data from social media in deeper cognitive customer profiles and preferences. The methods employed in this research are literature and other references analysis, synthesis and logical analysis of information, comparison of information, systemisation and visualisation.


Keywords: Big data, data mining, social media, social networks, internet marketing.


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Sabaitytė, J., & Karpovičiūtė, R. (2020). Conceptual usage model of big data generated by social media. Global Journal of Information Technology: Emerging Technologies, 10(2), 128–145.