Published by: SAGE
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Social Sciences and Humanities | 341 | 18 | 21 | 12 |
| Computer Science | 859 | 9 | 9 | 5 |
The aim of the journal is to expand the discussion of research in Big data, Data science, Social media, Internet privacy and Public relations. The Big data works featured in the journal incorporate elements from Media studies, Law, World Wide Web, Epistemology and Social science. The work on Law addressed in the journal expands to the thematically related Corporate governance.
The work tackled in the journal goes beyond the discipline of Data science as it also encompasses Critical data studies.
The journal articles primarily focus on research topics in Big data, Data science, Social media, Public relations and Law. The published articles address concerns in Big data which are intertwined with other disciplines, such as Epistemology, Social science, Analytics and Management science. While Data science is the key highlight in the most cited articles, thet also covered some subjects on Data collection and External validity, Record linkage and Linkage (mechanical).
The main research concerns discussed in the journal are Big data, Social media, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), 2019-20 coronavirus outbreak and Data science. The journal facilitates discussions on Big data that incorporate concepts from other fields like Marketing and Corporate social responsibility. In it, Sentiment analysis, Internet privacy and Media studies are investigated in conjunction with one another to address concerns in Social media research.
Most of the Internet privacy studies addressed also intersect with Datafication. In addition to Media studies research, it aims to explore topics under Public discourse, Context (language use) and Topic model. Big Data & Society tackles research in Computational sociology as part of the general discipline of Data science, however, it also discusses concepts in Digital data.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Big Data & Society (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Big Data & Society (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 7.32% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 28.95% were posted by at least one author from the top 10 institutions publishing in the journal. Another 9.21% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 25.00% of all publications and 36.84% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
While the field of Big Data and Society is primarily research-oriented, it also opens up a plethora of career opportunities. For instance, Licensed Professional Counselors (LPC) who wish to specialize in Big Data can find numerous rewarding roles in this industry. Especially in Delaware, there are specific LPC requirements to transition into this field. To become an LPC specializing in Big Data, individuals must first complete a Master's degree in counseling or a related field. They would also need to complete a 3,200-hour supervised internship, pass the National Counselor Examination (NCE), the National Clinical Mental Health Counseling Examination (NCMHCE), and complete a two-year post-Master's supervised experience. After fulfilling these requirements, they can advance their careers in areas like data counseling or as data privacy consultants. To further clarify and analyze the role of LPC in Big Data, potential candidates can refer to the article on "LPC requirements in Delaware". This important source goes into detail about the requirements, opportunities, and challenges facing LPCs in Big Data. The Big Data field is constantly evolving, allowing professionals with a passion for data and societal impact to make a meaningful difference. By pursuing a career as an LPC in Big Data, one can contribute to this developing field while assisting others in navigating the complex world of data privacy and security.
Kai-Cheng Yang;Francesco Pierri;Francesco Pierri;Pik-Mai Hui;David Axelrod
(2021)Age Poom;Age Poom;Olle Järv;Matthew Zook;Tuuli Toivonen
(2020)Paola Pascual-Ferrá;Neil Alperstein;Daniel J. Barnett;Rajiv N. Rimal
(2021)Sabina Leonelli;Rebecca Lovell;Benedict W Wheeler;Lora Fleming
(2021)Michael Robert Haupt;Jiawei Li;Tim K Mackey
(2021)Katie Shilton;Emanuel Moss;Sarah A. Gilbert;Matthew J. Bietz
(2021)For those interested in studying Computer Science in the USA, exploring related online degrees can offer flexible and affordable alternatives. Many students benefit from enrolling in best self paced online college programs, which allow learners to manage their study schedules around personal commitments.
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