Global Research on Big Data in Relation with Artificial Intelligence (A Bibliometric Study: 20082019) The purpose of this paper is to analyze and explore the research studies on Big Data in relation with Artificial Intelligence domain, which published in Peer Review Journals and indexed in Web of Science Core Collection for the period of 20082019 years.     The publication data for our research analysis xe2x80x9cBig Data in relation with Artificial Intelligencexe2x80x9d has been derived from the Web of Science (WoS) Core Collection database (Indexes included SCI Expanded and SSCI).xc2xa0   The Bibliometric Analysis Methods is applied for the study in order to find out the relations between two domains and to investigate the status of scientific development level in the research era. Therefore, our research concentrates and highlights the current issues discussed and studied by the scholars around the globe. This paper would useful for researchers to show the publication trends on big data in relation with artificial intelligence research outcomes in highly reputable SCIExp and SSCI journal (ranked by WoS).

Theme Mapping and Bibliometrics Analysis of One Decade of Big Data Research in the Scopus Database Recently, the popularity of big data as a research field has shown continuous and widescale growth. This study aims to capture the scientific structure and topic evolution of big data research using bibliometrics and text miningbased analysis methods. Bibliographic data of journal articles regarding big data published between 2009 to 2018 were collected from the Scopus database and analyzed. The results show a significant growth of publications since 2014. Furthermore, the findings of this study highlight the core journals, most cited articles, top productive authors, countries, and institutions. Secondly, a unique approach to identifying and analyzing major research themes in big data publications was proposed. Keywords were clustered, and each cluster was labeled as a theme. Moreover, the papers were divided into four subperiods to observe the thematic evolution. The theme mapping reveals that research on big data is dominated by big data analytics, which covers methods, tools, supporting infrastructure, and applications. Other critical aspects of big data research are security and privacy. Social networks and the Internet of things are significant sources of big data, and the resources and services offered by cloud computing strongly support the management and processing of big data.