Impact Factor 2.0: Applying Social Network Analysis to Scientific Impact Assessment

Applying centrality measures to impact analysis: A coauthorship network analysis

Many studies on coauthorship networks focus on network topology and network statistical mechanics. This article takes a different approach by studying micro-level network properties, with the aim to apply centrality measures to impact analysis. Using coauthorship data from 16 journals in the field of library and information science (LIS) with a time span of twenty years (1988-2007), we construc...

Applying social network analysis to security

In this paper, we set out to explore some of the many ways in which Social Network Analysis (SNA) can be applied to the field of security. In particular, we investigate what information someone (e.g., an attacker) could infer if they were able to gather data on a person’s friend-groups or device communications (e.g., email interactions) and whether this could be used to predict the “hierarchica...

Author Impact Factor: tracking the dynamics of individual scientific impact

The impact factor (IF) of scientific journals has acquired a major role in the evaluations of the output of scholars, departments and whole institutions. Typically papers appearing in journals with large values of the IF receive a high weight in such evaluations. However, at the end of the day one is interested in assessing the impact of individuals, rather than papers. Here we introduce Author...

Scientific competition, impact factor, and Altmetrics

The Impact Factor and Scientific Journals

Thanks to you, our readership, our combined Global Spine Journal/Evidence-Based Spine-Care Journal has enjoyed substantial popularity in terms of submissions. In response to this demand, the AOSpine International Board has given us permission to increase our number of annual issues from 6 to 8. This increase in annual issues has come with a number of stipulations, of which one of the leading on...