Published by: Springer
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Engineering and Technology | 786 | 17 | 30 | 11 |
The main research concerns discussed in the journal are Data science, Social media, Artificial intelligence, Mobile phone and Big data. It focuses on Data science but the discussions also offer insight into other areas such as Context (language use), Popularity, Data mining and Complex network. The journal explores issues in Social media which can be linked to other research areas like Simulation and Social network.
The study on Artificial intelligence presented in the journal intersects with subjects under the field of Machine learning.
The most cited publications cover a variety of subjects, including Social media, Data science, Artificial intelligence, Big data and Social network. The works on Social media tackled in the journal publications bring together disciplines like Data mining, Computational sociology, Internet privacy, Information cascade and Grassroots. The most cited papers focus on Data science but the discussions also offer insight into other areas such as Mobile phone, Learning classifier system, Key (cryptography), Scientific publishing and Complex network.
The journal mostly deals with topics like Pandemic, Social media, Cluster analysis, Artificial intelligence and Politics. In addition to Social media research, it aims to explore topics under Advertising, Shock (economics) and Personal mobility. While the primary focus in EPJ Data Science is Cluster analysis, it also dissects topics surrounding Mobile phone and Environmental resource management and Public transport as a whole.
The studies in Artificial intelligence featured incorporate elements of Machine learning and Markov process. Semantic network research in EPJ Data Science involves the investigation of Presidential system studies, all of which are linked to disciplines such as Data science. EPJ Data Science addresses concerns in Data science which are intertwined with other disciplines, such as Structure (mathematical logic), Survey data collection and Metric (mathematics).
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 EPJ Data 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 EPJ Data 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, 1.92% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 43.14% were posted by at least one author from the top 10 institutions publishing in the journal. Another 11.76% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 11.76% of all publications and 33.33% 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.
Guido Caldarelli;Guido Caldarelli;Rocco De Nicola;Marinella Petrocchi;Marinella Petrocchi;Manuel Pratelli
(2021)Takahiro Yabe;Yunchang Zhang;Satish V. Ukkusuri
(2020)Hao Cui;János Kertész
(2021)Javier Ureña-Carrion;Jari Saramäki;Mikko Kivelä
(2020)Mattia Mattei;Guido Caldarelli;Tiziano Squartini;Fabio Saracco
(2021)Sara Daraei;Konstantinos Pelechrinis;Daniele Quercia
(2021)Marta Tuninetti;Alberto Aleta;Daniela Paolotti;Yamir Moreno;Yamir Moreno
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