  Unlike most bibliometric studies focusing on publications, taking Big Data
research as a case study, we introduce a novel bibliometric approach to unfold
the status of a given scientific community from an individual level
perspective. We study the academic age, production, and research focus of the
community of authors active in Big Data research. Artificial Intelligence (AI)
is selected as a reference area for comparative purposes. Results show that the
academic realm of "Big Data" is a growing topic with an expanding community of
authors, particularly of new authors every year. Compared to AI, Big Data
attracts authors with a longer academic age, who can be regarded to have
accumulated some publishing experience before entering the community. Despite
the highly skewed distribution of productivity amongst researchers in both
communities, Big Data authors have higher values of both research focus and
production than those of AI. Considering the community size, overall academic
age, and persistence of publishing on the topic, our results support the idea
of Big Data as a research topic with attractiveness for researchers. We argue
that the community-focused indicators proposed in this study could be
generalized to investigate the development and dynamics of other research
fields and topics.
