The reliable assessment of individual faculty members’ contributions is a key challenge in the governance of research institutions. Traditionally, scientific impact is estimated based on bibliographic analyses. With online platforms, particularly social media, gaining popularity among academics, new opportunities for the analysis of scientific impact arise. Proponents of the “altmetrics” approach hold that both general purpose social media and services tailored to the scientific community allow for a range of usage metrics that may inform scientific impact assessment. We propose that relational analyses of social media platforms may shed new light on these understudied dimensions of scientific impact and may enrich assessment efforts. Based on a sample of Swiss management scholars’ active on ResearchGate, we conduct a social network analysis, derive relational metrics, and correlate these metrics with bibliometrics, webometrics, and altmetrics to gauge their potential to inform scientific impact assessment, specifically in business and management research.
%0 Journal Article
%1 lutz2017making
%A Lutz, Christoph
%A Hoffmann, Christian Pieter
%D 2017
%J Social Science Computer Review
%K altmetrics bwl netzwerke
%R 10.1177/0894439317721181
%T Making Academic Social Capital Visible
%U http://dx.doi.org/10.1177/0894439317721181
%X The reliable assessment of individual faculty members’ contributions is a key challenge in the governance of research institutions. Traditionally, scientific impact is estimated based on bibliographic analyses. With online platforms, particularly social media, gaining popularity among academics, new opportunities for the analysis of scientific impact arise. Proponents of the “altmetrics” approach hold that both general purpose social media and services tailored to the scientific community allow for a range of usage metrics that may inform scientific impact assessment. We propose that relational analyses of social media platforms may shed new light on these understudied dimensions of scientific impact and may enrich assessment efforts. Based on a sample of Swiss management scholars’ active on ResearchGate, we conduct a social network analysis, derive relational metrics, and correlate these metrics with bibliometrics, webometrics, and altmetrics to gauge their potential to inform scientific impact assessment, specifically in business and management research.
@article{lutz2017making,
abstract = { The reliable assessment of individual faculty members’ contributions is a key challenge in the governance of research institutions. Traditionally, scientific impact is estimated based on bibliographic analyses. With online platforms, particularly social media, gaining popularity among academics, new opportunities for the analysis of scientific impact arise. Proponents of the “altmetrics” approach hold that both general purpose social media and services tailored to the scientific community allow for a range of usage metrics that may inform scientific impact assessment. We propose that relational analyses of social media platforms may shed new light on these understudied dimensions of scientific impact and may enrich assessment efforts. Based on a sample of Swiss management scholars’ active on ResearchGate, we conduct a social network analysis, derive relational metrics, and correlate these metrics with bibliometrics, webometrics, and altmetrics to gauge their potential to inform scientific impact assessment, specifically in business and management research. },
added-at = {2017-07-25T09:36:24.000+0200},
author = {Lutz, Christoph and Hoffmann, Christian Pieter},
biburl = {https://www.bibsonomy.org/bibtex/28ed0cf22c6da21c07512546219378e01/wdees},
doi = {10.1177/0894439317721181},
eprint = {http://dx.doi.org/10.1177/0894439317721181},
interhash = {d2e927ebf7b9e8578de2303a6b393f66},
intrahash = {8ed0cf22c6da21c07512546219378e01},
journal = {Social Science Computer Review},
keywords = {altmetrics bwl netzwerke},
timestamp = {2017-07-25T09:36:24.000+0200},
title = {Making Academic Social Capital Visible},
url = {http://dx.doi.org/10.1177/0894439317721181 },
year = 2017
}