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Frontiers in Big Data is a peer-reviewed journal published by Frontiers, covering Complex Network Analysis Techniques, Advanced Graph Neural Networks, Ethics and Social Impacts of AI. Over its lifetime it has published 759 papers, which have received 11,133 citations.
| Publisher | Frontiers |
|---|---|
| Reference style | Author–year (Harvard) Author–year — (Smith, 2023) in the text Smith, A., Jones, B. and Lee, C. (2023) 'A representative article title', Frontiers in Big Data, 12(3), pp. 45–58.
Formats any DOI in Frontiers in Big Data style. No sign-up. |
| Publishes research in | Complex Network Analysis Techniques Advanced Graph Neural Networks Ethics and Social Impacts of AI Misinformation and Its Impacts Machine Learning in Healthcare |
| ISSN | 2624-909X |
| Citation impact (2-yr) | 6.12 |
| h-index | 49 |
| i10-index | 265 |
| Article processing charge | $1,150 |
| Open access | Yes — indexed in DOAJ |
| Top institutions publishing here | Centre National de la Recherche Scientifique |
| Journal website | www.frontiersin.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Social data in digital form-including user-generated content, expressed or implicit relations between people, and behavioral traces-are at the core of popular applications and platforms, driving the research agenda of many researchers. The promises of social data are many, including understanding "what the world thinks" about a social issue, brand, celebrity, or other entity, as well…
Open science will make science more efficient, reliable, and responsive to societal challenges. The European Commission has sought to advance open science policy from its inception in a holistic and integrated way, covering all aspects of the research cycle from scientific discovery and review to sharing knowledge, publishing, and outreach. We present the steps taken…
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Both statistical and neural methods have been proposed in the literature to predict healthcare expenditures. However, less attention has been given to comparing predictions from both these methods as well as ensemble approaches in the healthcare domain. The primary objective of this paper was to evaluate different statistical, neural, and ensemble techniques in their ability…
As of 2020, the Public Employment Service Austria (AMS) makes use of algorithmic profiling of job seekers to increase the efficiency of its counseling process and the effectiveness of active labor market programs. Based on a statistical model of job seekers' prospects on the labor market, the system-that has become known as the AMS algorithm-is…
