PUMA publications for /author/Jens%20Terliesnerhttps://puma.uni-kassel.de/author/Jens%20TerliesnerPUMA RSS feed for /author/Jens%20Terliesner2024-03-28T19:57:19+01:00Beyond citations: Scholars' visibility on the social Webhttps://puma.uni-kassel.de/bibtex/242585cbc0a99d9e137f2a3d6cb0239e5/stephandoerfelstephandoerfel2015-03-15T16:17:07+01:00visibility social correlation citations authors web <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Judit Bar-Ilan" itemprop="url" href="/author/Judit%20Bar-Ilan"><span itemprop="name">J. Bar-Ilan</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Stefanie Haustein" itemprop="url" href="/author/Stefanie%20Haustein"><span itemprop="name">S. Haustein</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Isabella Peters" itemprop="url" href="/author/Isabella%20Peters"><span itemprop="name">I. Peters</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jason Priem" itemprop="url" href="/author/Jason%20Priem"><span itemprop="name">J. Priem</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hadas Shema" itemprop="url" href="/author/Hadas%20Shema"><span itemprop="name">H. Shema</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jens Terliesner" itemprop="url" href="/author/Jens%20Terliesner"><span itemprop="name">J. Terliesner</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of 17th International Conference on Science and Technology Indicators, Montréal: Science-Metrix and OST</span>, </em></span><em> 1, </em><em>Seite <span itemprop="pagination">98-109</span>. </em>(<em><span>2012<meta content="2012" itemprop="datePublished"/></span></em>)Sun Mar 15 16:17:07 CET 2015Proceedings of 17th International Conference on Science and Technology Indicators, Montréal: Science-Metrix and OST98-109Beyond citations: Scholars' visibility on the social Web12012visibility social correlation citations authors web Traditionally, scholarly impact and visibility have been measured by counting
publications and citations in the scholarly literature. However, increasingly
scholars are also visible on the Web, establishing presences in a growing
variety of social ecosystems. But how wide and established is this presence,
and how do measures of social Web impact relate to their more traditional
counterparts? To answer this, we sampled 57 presenters from the 2010 Leiden STI
Conference, gathering publication and citations counts as well as data from the
presenters' Web "footprints." We found Web presence widespread and diverse: 84%
of scholars had homepages, 70% were on LinkedIn, 23% had public Google Scholar
profiles, and 16% were on Twitter. For sampled scholars' publications, social
reference manager bookmarks were compared to Scopus and Web of Science
citations; we found that Mendeley covers more than 80% of sampled articles, and
that Mendeley bookmarks are significantly correlated (r=.45) to Scopus citation
counts.Beyond citations: Scholars' visibility on the social WebBeyond citations: Scholars' visibility on the social Webhttps://puma.uni-kassel.de/bibtex/281198ca94374ccd7b0a86b2b53d2ee50/stephandoerfelstephandoerfel2013-01-09T13:14:06+01:00scholars visibility social citations web <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Judit Bar-Ilan" itemprop="url" href="/author/Judit%20Bar-Ilan"><span itemprop="name">J. Bar-Ilan</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Stefanie Haustein" itemprop="url" href="/author/Stefanie%20Haustein"><span itemprop="name">S. Haustein</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Isabella Peters" itemprop="url" href="/author/Isabella%20Peters"><span itemprop="name">I. Peters</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jason Priem" itemprop="url" href="/author/Jason%20Priem"><span itemprop="name">J. Priem</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hadas Shema" itemprop="url" href="/author/Hadas%20Shema"><span itemprop="name">H. Shema</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jens Terliesner" itemprop="url" href="/author/Jens%20Terliesner"><span itemprop="name">J. Terliesner</span></a></span>. </span><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"> </span>(<em><span>2012<meta content="2012" itemprop="datePublished"/></span></em>)Wed Jan 09 13:14:06 CET 2013Beyond citations: Scholars' visibility on the social Web2012scholars visibility social citations web Traditionally, scholarly impact and visibility have been measured by counting
publications and citations in the scholarly literature. However, increasingly
scholars are also visible on the Web, establishing presences in a growing
variety of social ecosystems. But how wide and established is this presence,
and how do measures of social Web impact relate to their more traditional
counterparts? To answer this, we sampled 57 presenters from the 2010 Leiden STI
Conference, gathering publication and citations counts as well as data from the
presenters' Web "footprints." We found Web presence widespread and diverse: 84%
of scholars had homepages, 70% were on LinkedIn, 23% had public Google Scholar
profiles, and 16% were on Twitter. For sampled scholars' publications, social
reference manager bookmarks were compared to Scopus and Web of Science
citations; we found that Mendeley covers more than 80% of sampled articles, and
that Mendeley bookmarks are significantly correlated (r=.45) to Scopus citation
counts.Crowdsourcing in Article Evaluationhttps://puma.uni-kassel.de/bibtex/28e03cf8d57f903da395c07e9a9125f08/stephandoerfelstephandoerfel2015-03-16T23:34:55+01:00tags keywords crowd citation <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Isabella Peters" itemprop="url" href="/author/Isabella%20Peters"><span itemprop="name">I. Peters</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Stefanie Haustein" itemprop="url" href="/author/Stefanie%20Haustein"><span itemprop="name">S. Haustein</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jens Terliesner" itemprop="url" href="/author/Jens%20Terliesner"><span itemprop="name">J. Terliesner</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">ACM WebSci'11</span>, </em></span><em>Seite <span itemprop="pagination">1--4</span>. </em>(<em><span>Juni 2011<meta content="Juni 2011" itemprop="datePublished"/></span></em>)<em>WebSci Conference 2011.</em>Mon Mar 16 23:34:55 CET 2015ACM WebSci'11JuneWebSci Conference 20111--4Crowdsourcing in Article Evaluation2011tags keywords crowd citation Qualitative journal evaluation makes use of cumulated content
descriptions of single articles. These can either be represented by
author-generated keywords, professionally indexed subject
headings, automatically extracted terms or by reader-generated
tags as used in social bookmarking systems. It is assumed that
particularly the users? view on article content differs significantly
from the authors? or indexers? perspectives. To verify this
assumption, title and abstract terms, author keywords, Inspec
subject headings, KeyWords PlusTM and tags are compared by
calculating the overlap between the respective datasets. Our
approach includes extensive term preprocessing (i.e. stemming,
spelling unifications) to gain a homogeneous term collection.
When term overlap is calculated for every single document of the
dataset, similarity values are low. Thus, the presented study
confirms the assumption, that the different types of keywords
each reflect a different perspective of the articles? contents and
that tags (cumulated across articles) can be used in journal
evaluation to represent a reader-specific view on published
content.Crowdsourcing in Article Evaluation - Web Science Repository