Big data and social media: A scientometrics analysis

• Published in: International journal of data and network science (Print) Vol. 3; no. 3; pp. 145 - 164
• Main Authors: Jelvehgaran Esfahani, Hossein, Tavasoli, Keyvan, Jabbarzadeh, Armin
• Format: Journal Article
• Language: English
• Published: Growing Science 2019
• Subjects: Bibliometric; Bibliometrix R-package; Big data; Big data analytics; Scientometrics; Social media; Social networking
• ISSN: 2561-8148; 2561-8156
• DOI: 10.5267/j.ijdns.2019.2.007

The purpose of this research is to investigate the status and the evolution of the scientific studies for the effect of social networks on big data and usage of big data for modeling the social net-works users’ behavior. This paper presents a comprehensive review of the studies associated with big data in social media. The study uses Scopus database as a primary search engine and covers 2000 of highly cited articles over the period 2012-2019. The records are statistically analyzed and categorized in terms of different criteria. The findings show that researches have grown exponentially since 2014 and the trend has continued at relatively stable rates. Based on the survey, decision support systems is the keyword which has carried the highest densities followed by heuristics methods. Among the most cited articles, papers published by researchers in United States have received the highest citations (7548), followed by United Kingdom (588) and China with 543 citations. Thematic analysis shows that the subject nearly maintained an important and well-developed research field and for better results we can merge our research with “big data analytics” and “twitter” that are important topics in this field but not developed well.