2050-1242
Published by: Cambridge University Press
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Social Sciences and Humanities | 522 | 16 | 18 | 9 |
| Computer Science | 781 | 16 | 17 | 6 |
The main research concerns discussed in Network Science are Social psychology, Social network, Theoretical computer science, Artificial intelligence and Network science. As a part of the journal, discussions in Social psychology involve topics like Friendship, Interpersonal ties and Social influence. Studies on Social network discussed in it link to the field of Homophily.
The research on Theoretical computer science discussed in the journal draws on the closely related field of Cluster analysis. The studies tackled, which mainly focus on Artificial intelligence, apply to Machine learning as well. The Network science study featured falls within the larger field of Complex network.
Many of the studies tackled connect Complex network with a similar field of study like Centrality.
The most cited articles facilitate discussions on Social psychology, Network science, Theoretical computer science, Cluster analysis and Complex network. The journal papers address concerns in Network science which are intertwined with other disciplines, such as Graph (abstract data type), Field (geography) and Applied mathematics. The published articles facilitate discussions on Complex network that incorporate concepts from other fields like Betweenness centrality, Epidemic spread and Vaccination.
The foci of the journal are Theoretical computer science, Complex network, Artificial intelligence, Degree (graph theory) and Graph (abstract data type). The study of Theoretical computer science encompasses disciplines such as Random graph, as well as fields such as Structure (mathematical logic), Metric (mathematics), Social media and Preprocessor, all of which overlap with one another. It addresses concerns in Complex network which are intertwined with other disciplines, such as Distributed computing, Curvature, Ricci curvature, Metric space and Differential geometry.
Many of the research works in Artificial intelligence, specifically Adversarial system, closely connected to disciplines like Network analysis. While Identification (information) is the key highlight in it, it also covered some subjects on Coding (social sciences) and Cluster analysis. The work on Cluster analysis tackled in it brings together disciplines like Sorting and Node (networking).
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 Network Science (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 Network Science (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, 44.44% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 13.33% were posted by at least one author from the top 10 institutions publishing in the journal. Another 20.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 26.67% of all publications and 40.00% 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.
With the diverse range of research topics and areas of study within network science, multiple career opportunities arise for those who choose to specialize in this field. Opportunities include working as a network analyst, data scientist, or theoretical computer scientist. Moreover, for those interested in the psychological aspects of network science, becoming a licensed professional counselor is another viable option.
For example, a career as a licensed professional counselor, particularly in the state of Michigan, involves specific steps for licensure. To enhance their understanding and embark on such a career journey, interested individuals might find our guide on How to become an LPC in Michigan beneficial. This guide provides a step-by-step approach to becoming a licensed professional counselor, illustrating the intersection between network science and psychology.
Overall, pursuing a career in network science opens up a world of opportunities in various industries. Whether your interests lie in artificial intelligence, social networks, or the intricacies of theoretical computer science, each pathway offers immense potential for personal and professional growth.
Beate Volker
(2020)Jan Treur
(2020)Bernie Hogan;Patrick Janulis;Gregory Lee Phillips;Joshua R. Melville
(2020)Barry Wellman;Anabel Quan-Haase;Molly-Gloria R. Harper
(2020)Byungkyu Lee;Peter Bearman
(2020)Marianne Hooijsma;Gijs Huitsing;Dorottya Kisfalusi;Jan Kornelis Dijkstra
(2020)Ran Xu;Kenneth A. Frank
(2021)Exploring the field of Computer Science opens doors to various interdisciplinary career options and advanced study paths. For students interested in blending technology with physical sciences, online mechanical engineering degrees offer affordable opportunities to develop skills in designing machines and systems critical to today’s innovations. Similarly, those drawn to the fundamental laws of nature may consider online theoretical physics degree programs, which provide a strong foundation in analytical thinking and problem-solving.
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