The exponential growth of social media platforms has led to an unprecedented surge in data generation,
offering vast opportunities for research, analysis, and insight generation. This literature review synthesizes existing
studies on the implementation of big data analytics on social media data. It delves into various aspects including
methodologies, tools, challenges, and emerging trends.
The review begins by exploring the methodologies employed in analyzing social media data, ranging from traditional
statistical methods to advanced computational methods of machine learning. It highlights the importance of selecting
appropriate methodologies based on the research objectives and characteristics of the data.
Furthermore, the review addresses the diverse range of tools and platforms available for big data analysis in social
media data, including open-source frameworks, commercial software, and custom-built solutions. It examines the
functionalities, scalability, and usability of these tools, offering insights into their suitability for different research
contexts.
[1] Bach, M. P.., Krstic, Z.., Seljan, S.., & Turulja, L.. (2019). Text Mining for Big Data Analysis in Financial Sector: A Literature Review.
Sustainability . http://doi.org/10.3390/SU11051277
[2] Sreenu, G.., & Durai, M. A. Saleem. (2019). Intelligent video surveillance: a review through deep learning techniques for crowd analysis. Journal of
Big Data , 6 . http://doi.org/10.1186/s40537-019-0212-5
[3] Zhu, Bangren., Zheng, Xinqi., Liu, Haiyan., Li, Jiayang., & Wang, Peipei. (2020). Analysis of spatiotemporal characteristics of big data on social
media sentiment with COVID-19 epidemic topics. Chaos, Solitons, and Fractals , 140 , 110123 - 110123 . http://doi.org/10.1016/j.chaos.2020.110123
[4] Vargo, Chris J.., Guo, Lei., & Amazeen, Michelle A.. (2018). The agenda-setting power of fake news: A big data analysis of the online media
landscape from 2014 to 2016. New Media & Society , 20 , 2028 - 2049 . http://doi.org/10.1177/1461444817712086
[5] Felt, Mylynn. (2016). Social media and the social sciences: How researchers employ Big Data analytics. Big Data & Society , 3 .
http://doi.org/10.1177/2053951716645828
[6] Xu, Zheng., Liu, Yunhuai., Yen, N.., Mei, Lin., Luo, Xiangfeng., Wei, Xiao., & Hu, Chuanping. (2020). Crowdsourcing Based Description of Urban
Emergency Events Using Social Media Big Data. IEEE Transactions on Cloud Computing , 8 , 387-397 . http://doi.org/10.1109/TCC.2016.2517638
Applications
[7] Luckow, André., Cook, M.., Ashcraft, Nathan., Weill, Edwin., Djerekarov, Emil., & Vorster, Bennie. (2016). Deep learning in the automotive
industry:
and tools. 2016 IEEE International Conference on Big Data (Big Data) , 3759-3768 .
http://doi.org/10.1109/BigData.2016.7841045
[8] Tsou, Ming-Hsiang. (2015). Research challenges and opportunities in mapping social media and Big Data. Cartography and Geographic
Information Science , 42 , 70 - 74 . http://doi.org/10.1080/15230406.2015.1059251.
[9] Hargittai, E.. (2018). Potential Biases in Big Data: Omitted Voices on Social Media. Social Science Computer Review , 38 , 10 - 24 .
http://doi.org/10.1177/0894439318788322
[10] Md. Saifur Rahman, Hassan Reza (2020). Systematic Mapping Study of Non-Functional Requirements in Big Data System.
http://doi.org/10.1109/EIT48999.2020.9208288
[11] Sepideh Bazzaz Abkenar, Mostafa Haghi Kashani, Ebrahim Mahdipour, Seyed Mahdi Jameii (2020). Big data analytics meets social media: A
systematic review of techniques, open issues, and future directions. https://doi.org/10.1016/j.tele.2020.101517
