2015/07/02 by Tamar Loach, Tim Evans, Loach, Tamar V. +1
Computer Science · Physics and Astronomy · Social Sciences · #Complex Network Analysis Techniques #Computers and Society (cs.CY) #Digital Libraries (cs.DL) #FOS: Computer and information sciences #Social and Information Networks (cs.SI) #Web visibility and informetrics #Wikis in Education and Collaboration
paper · pdf · doi:10.48550/arxiv.1507.00451
openalex publication_date 2015/07/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The rank of a journal based on simple citation information is a popular measure. The simplicity and availability of rankings such as Impact Factor, Eigenfactor and SciMago Journal Rank based on trusted commercial sources ensures their widespread use for many important tasks despite the well-known limitations of such rankings. In this paper we look at an alternative approach based on information on papers from social and mainstream media sources. Our data comes from altmetric.com who identify mentions of individual academic papers in sources such as Twitter, Facebook, blogs and news outlets. We consider several different methods to produce a ranking of journals from such data. We show that most (but not all) schemes produce results, which are roughly similar, suggesting that there is a basic consistency between social media based approaches and traditional citation based methods. Most ranking schemes applied to one data set produce relatively little variation and we suggest this provides a measure of the uncertainty in any journal rating. The differences we find between data sources also shows they are capturing different aspects of journal impact. We conclude a small number of such ratings will provide the best information on journal impact.