Online Social Networks and Media Template
Write in a clean editor, then format for Online Social Networks and Media in one click — DocuGuru applies the official Elsevier template with numbered references and exports a submission-ready PDF plus the editable LaTeX source. Free to start.
About the Online Social Networks and Media format
Online Social Networks and Media is a peer-reviewed journal published by Elsevier, covering Misinformation and Its Impacts, Complex Network Analysis Techniques, Social Media and Politics.
| Publisher | Elsevier |
|---|---|
| Reference style | Numbered (Elsevier) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, C. Lee, A representative article title, Online Social Networks and Media 12 (2023) 45–58.
Formats any DOI in Online Social Networks and Media style. No sign-up. |
| Publishes research in | Misinformation and Its Impacts Complex Network Analysis Techniques Social Media and Politics Opinion Dynamics and Social Influence Spam and Phishing Detection |
| ISSN | 2468-6964 |
| Citation impact (2-yr) | 3.7 |
| h-index | 38 |
| i10-index | 107 |
| Total citations | 4,431 |
| Article processing charge | $2,070 |
| Top institutions publishing here | Institute of Informatics and Telematics |
| Journal website | www.journals.elsevier.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Papers published in Online Social Networks and Media per year
Citation impact of Online Social Networks and Media by publication year
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Most-cited papers in Online Social Networks and Media
The World Wide Web, and online social networks in particular, have increased connectivity between people such that information can spread to millions of people in a matter of minutes. This form of online collective contagion has provided many benefits to society, such as providing reassurance and emergency management in the immediate aftermath of natural disasters.…
A segment of the political discussions on Online Social Networks (OSNs) is shaped by hyperactive users. These are users that are over-proportionally active in relation to the mean. By applying a geometric topic modeling algorithm (GTM) on German users’ political comments and parties’ posts and by analyzing commenting and liking activities, we quantitatively demonstrate that…