Social media big data analytics: A survey. (December 2019)

• Record Type: Journal Article
• Authors: Ghani, Norjihan Abdul; Hamid, Suraya; Targio Hashem, Ibrahim Abaker; Ahmed, Ejaz
• Is Part Of: Computers in human behavior. Volume 101(2019)
• Page Start: 417
• Page End: 428
• Publication Date: 2019-12
• Subjects: Big data -- Social media -- Machine learning -- Analytics; Interactive computer systems -- Periodicals; Man-machine systems -- Periodicals; 004.019
• DOI: 10.1016/j.chb.2018.08.039
• Languages: English
• ISSNs: 0747-5632

Abstract

Abstract: Big data analytics has recently emerged as an important research area due to the popularity of the Internet and the advent of the Web 2.0 technologies. Moreover, the proliferation and adoption of social media applications have provided extensive opportunities and challenges for researchers and practitioners. The massive amount of data generated by users using social media platforms is the result of the integration of their background details and daily activities. This enormous volume of generated data known as "big data" has been intensively researched recently. A review of the recent works is presented to obtain a broad perspective of the social media big data analytics research topic. We classify the literature based on important aspects. This study also compares possible big data analytics techniques and their quality attributes. Moreover, we provide a discussion on the applications of social media big data analytics by highlighting the state-of-the-art techniques, methods, and the quality attributes of various studies. Open research challenges in big data analytics are described as well. Highlights: We review recent work on big social media analytics. We provide classification of big data analytics on social media. Recent advance in machine learning algorithms are discussed. We highlight some of the research challenges.