@inproceedings{barilan2012beyond,
  abstract = {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.},
  author = {Bar-Ilan, Judit and Haustein, Stefanie and Peters, Isabella and Priem, Jason and Shema, Hadas and Terliesner, Jens},
  booktitle = {Proceedings of 17th International Conference on Science and Technology Indicators, Montréal: Science-Metrix and OST},
  editor = {Archambault, Éric and Gingras, Yves and Larivière, Vincent},
  interhash = {5c386f2bfcd8d2052d455c75efb1c727},
  intrahash = {42585cbc0a99d9e137f2a3d6cb0239e5},
  pages = {98-109},
  title = {Beyond citations: Scholars' visibility on the social Web},
  url = {http://2012.sticonference.org/Proceedings/vol1/Bar-Ilan_Beyond_98.pdf},
  volume = 1,
  year = 2012
}

@article{barilan2012beyond,
  abstract = {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.},
  author = {Bar-Ilan, Judit and Haustein, Stefanie and Peters, Isabella and Priem, Jason and Shema, Hadas and Terliesner, Jens},
  interhash = {5c386f2bfcd8d2052d455c75efb1c727},
  intrahash = {81198ca94374ccd7b0a86b2b53d2ee50},
  title = {Beyond citations: Scholars' visibility on the social Web},
  url = {http://dblp.uni-trier.de/db/journals/corr/corr1205.html#abs-1205-5611},
  year = 2012
}

@inproceedings{peters2011crowdsourcing,
  abstract = {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.},
  author = {Peters, Isabella and Haustein, Stefanie and Terliesner, Jens},
  booktitle = {ACM WebSci'11},
  interhash = {def78a2b12565187bcac0cf08089b7a1},
  intrahash = {8e03cf8d57f903da395c07e9a9125f08},
  month = {June},
  note = {WebSci Conference 2011},
  pages = {1--4},
  title = {Crowdsourcing in Article Evaluation},
  url = {http://journal.webscience.org/487/},
  year = 2011
}