Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations.

@inproceedings{zoller2015publication, author = {Zoller, Daniel and Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd and Hotho, Andreas}, title = {On Publication Usage in a Social Bookmarking System}, booktitle = {Proceedings of the 2015 ACM Conference on Web Science}, year = {2015}, keywords = {2015, altmetrics, bookmarking, impact, myown, publication, social, usage}, abstract = {Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations.} }

%0 = inproceedings %A = Zoller, Daniel and Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd and Hotho, Andreas %B = Proceedings of the 2015 ACM Conference on Web Science %D = 2015 %T = On Publication Usage in a Social Bookmarking System

Academics can now use the web and the social websites to disseminate scholarly information in a variety of different ways. Although some scholars have taken advantage of these new online opportunities, it is not clear how widespread their uptake is or how much impact they can have. This study assesses the extent to which successful scientists have social web presences, focusing on one influential group: highly cited researchers working at European institutions. It also assesses the impact of these presences. We manually and systematically identified if the European highly cited researchers had profiles in Google Scholar, Microsoft Academic Search, Mendeley, Academia and LinkedIn or any content in SlideShare. We then used URL mentions and altmetric indicators to assess the impact of the web presences found. Although most of the scientists had an institutional website of some kind, few had created a profile in any social website investigated, and LinkedIn—the only non-academic site in the list—was the most popular. Scientists having one kind of social web profile were more likely to have another in many cases, especially in the life sciences and engineering. In most cases it was possible to estimate the relative impact of the profiles using a readily available statistic and there were disciplinary differences in the impact of the different kinds of profiles. Most social web profiles had some evidence of uptake, if not impact; nevertheless, the value of the indicators used is unclear.

@article{masbleda2014highly, author = {Mas-Bleda, Amalia and Thelwall, Mike and Kousha, Kayvan and Aguillo, IsidroF.}, title = {Do highly cited researchers successfully use the social web?}, journal = {Scientometrics}, publisher = {Springer Netherlands}, year = {2014}, volume = {101}, number = {1}, pages = {337-356}, url = {http://dx.doi.org/10.1007/s11192-014-1345-0}, doi = {10.1007/s11192-014-1345-0}, issn = {0138-9130}, keywords = {altmetrics, scientometrics, social, web}, abstract = {Academics can now use the web and the social websites to disseminate scholarly information in a variety of different ways. Although some scholars have taken advantage of these new online opportunities, it is not clear how widespread their uptake is or how much impact they can have. This study assesses the extent to which successful scientists have social web presences, focusing on one influential group: highly cited researchers working at European institutions. It also assesses the impact of these presences. We manually and systematically identified if the European highly cited researchers had profiles in Google Scholar, Microsoft Academic Search, Mendeley, Academia and LinkedIn or any content in SlideShare. We then used URL mentions and altmetric indicators to assess the impact of the web presences found. Although most of the scientists had an institutional website of some kind, few had created a profile in any social website investigated, and LinkedIn—the only non-academic site in the list—was the most popular. Scientists having one kind of social web profile were more likely to have another in many cases, especially in the life sciences and engineering. In most cases it was possible to estimate the relative impact of the profiles using a readily available statistic and there were disciplinary differences in the impact of the different kinds of profiles. Most social web profiles had some evidence of uptake, if not impact; nevertheless, the value of the indicators used is unclear.} }

%0 = article %A = Mas-Bleda, Amalia and Thelwall, Mike and Kousha, Kayvan and Aguillo, IsidroF. %D = 2014 %I = Springer Netherlands %T = Do highly cited researchers successfully use the social web? %U = http://dx.doi.org/10.1007/s11192-014-1345-0

<p>Altmetric measurements derived from the social web are increasingly advocated and used as early indicators of article impact and usefulness. Nevertheless, there is a lack of systematic scientific evidence that altmetrics are valid proxies of either impact or utility although a few case studies have reported medium correlations between specific altmetrics and citation rates for individual journals or fields. To fill this gap, this study compares 11 altmetrics with Web of Science citations for 76 to 208,739 PubMed articles with at least one altmetric mention in each case and up to 1,891 journals per metric. It also introduces a simple sign test to overcome biases caused by different citation and usage windows. Statistically significant associations were found between higher metric scores and higher citations for articles with positive altmetric scores in all cases with sufficient evidence (Twitter, Facebook wall posts, research highlights, blogs, mainstream media and forums) except perhaps for Google+ posts. Evidence was insufficient for LinkedIn, Pinterest, question and answer sites, and Reddit, and no conclusions should be drawn about articles with zero altmetric scores or the strength of any correlation between altmetrics and citations. Nevertheless, comparisons between citations and metric values for articles published at different times, even within the same year, can remove or reverse this association and so publishers and scientometricians should consider the effect of time when using altmetrics to rank articles. Finally, the coverage of all the altmetrics except for Twitter seems to be low and so it is not clear if they are prevalent enough to be useful in practice.</p>

@article{thelwall2013altmetrics, author = {Thelwall, Mike and Haustein, Stefanie and Larivière, Vincent and Sugimoto, Cassidy R.}, title = {Do Altmetrics Work? Twitter and Ten Other Social Web Services}, journal = {PLoS ONE}, publisher = {Public Library of Science}, year = {2013}, volume = {8}, number = {5}, pages = {e64841}, url = {http://dx.doi.org/10.1371%2Fjournal.pone.0064841}, doi = {10.1371/journal.pone.0064841}, keywords = {altmetrics, citations, facebook, scientometrics, twitter}, abstract = {<p>Altmetric measurements derived from the social web are increasingly advocated and used as early indicators of article impact and usefulness. Nevertheless, there is a lack of systematic scientific evidence that altmetrics are valid proxies of either impact or utility although a few case studies have reported medium correlations between specific altmetrics and citation rates for individual journals or fields. To fill this gap, this study compares 11 altmetrics with Web of Science citations for 76 to 208,739 PubMed articles with at least one altmetric mention in each case and up to 1,891 journals per metric. It also introduces a simple sign test to overcome biases caused by different citation and usage windows. Statistically significant associations were found between higher metric scores and higher citations for articles with positive altmetric scores in all cases with sufficient evidence (Twitter, Facebook wall posts, research highlights, blogs, mainstream media and forums) except perhaps for Google+ posts. Evidence was insufficient for LinkedIn, Pinterest, question and answer sites, and Reddit, and no conclusions should be drawn about articles with zero altmetric scores or the strength of any correlation between altmetrics and citations. Nevertheless, comparisons between citations and metric values for articles published at different times, even within the same year, can remove or reverse this association and so publishers and scientometricians should consider the effect of time when using altmetrics to rank articles. Finally, the coverage of all the altmetrics except for Twitter seems to be low and so it is not clear if they are prevalent enough to be useful in practice.</p>} }

%0 = article %A = Thelwall, Mike and Haustein, Stefanie and Larivière, Vincent and Sugimoto, Cassidy R. %D = 2013 %I = Public Library of Science %T = Do Altmetrics Work? Twitter and Ten Other Social Web Services %U = http://dx.doi.org/10.1371%2Fjournal.pone.0064841

In growing numbers, scholars are integrating social media tools like blogs,
itter, and Mendeley into their professional communications. The online,
blic nature of these tools exposes and reifies scholarly processes once
dden and ephemeral. Metrics based on this activities could inform broader,
ster measures of impact, complementing traditional citation metrics. This
udy explores the properties of these social media-based metrics or
ltmetrics", sampling 24,331 articles published by the Public Library of
ience.
We find that that different indicators vary greatly in activity. Around 5% of
mpled articles are cited in Wikipedia, while close to 80% have been included
at least one Mendeley library. There is, however, an encouraging diversity;
quarter of articles have nonzero data from five or more different sources.
rrelation and factor analysis suggest citation and altmetrics indicators
ack related but distinct impacts, with neither able to describe the complete
cture of scholarly use alone. There are moderate correlations between
ndeley and Web of Science citation, but many altmetric indicators seem to
asure impact mostly orthogonal to citation. Articles cluster in ways that
ggest five different impact "flavors", capturing impacts of different types
different audiences; for instance, some articles may be heavily read and
ved by scholars but seldom cited. Together, these findings encourage more
search into altmetrics as complements to traditional citation measures.

@misc{priem2012altmetrics, author = {Priem, Jason and Piwowar, Heather A. and Hemminger, Bradley M.}, title = {Altmetrics in the wild: Using social media to explore scholarly impact}, year = {2012}, note = {cite arxiv:1203.4745v1Comment: 5 tables, 13 figures}, url = {http://arxiv.org/abs/1203.4745}, keywords = {altmetrics, bookmarking, citations, correlation, coverage, impact, wild}, abstract = {In growing numbers, scholars are integrating social media tools like blogs,Twitter, and Mendeley into their professional communications. The online,public nature of these tools exposes and reifies scholarly processes oncehidden and ephemeral. Metrics based on this activities could inform broader,faster measures of impact, complementing traditional citation metrics. Thisstudy explores the properties of these social media-based metrics or"altmetrics", sampling 24,331 articles published by the Public Library ofScience. We find that that different indicators vary greatly in activity. Around 5% ofsampled articles are cited in Wikipedia, while close to 80% have been includedin at least one Mendeley library. There is, however, an encouraging diversity;a quarter of articles have nonzero data from five or more different sources.Correlation and factor analysis suggest citation and altmetrics indicatorstrack related but distinct impacts, with neither able to describe the completepicture of scholarly use alone. There are moderate correlations betweenMendeley and Web of Science citation, but many altmetric indicators seem tomeasure impact mostly orthogonal to citation. Articles cluster in ways thatsuggest five different impact "flavors", capturing impacts of different typeson different audiences; for instance, some articles may be heavily read andsaved by scholars but seldom cited. Together, these findings encourage moreresearch into altmetrics as complements to traditional citation measures.} }

%0 = misc %A = Priem, Jason and Piwowar, Heather A. and Hemminger, Bradley M. %B = } %C = %D = 2012 %I = %T = Altmetrics in the wild: Using social media to explore scholarly impact} %U = http://arxiv.org/abs/1203.4745

@electronic{priem2011altmetrics, author = {Priem, Jason and Taraborelli, Dario and Groth, Paul and Neylon, Cameron}, title = {Altmetrics: a Manifesto}, year = {2011}, url = {http://altmetrics.org/manifesto/}, keywords = {altmetrics, citation, manifesto} }

%0 = electronic %A = Priem, Jason and Taraborelli, Dario and Groth, Paul and Neylon, Cameron %B = } %C = %D = 2011 %I = %T = Altmetrics: a Manifesto} %U = http://altmetrics.org/manifesto/