7,157 research outputs found
Tweeting biomedicine: an analysis of tweets and citations in the biomedical literature
Data collected by social media platforms have recently been introduced as a
new source for indicators to help measure the impact of scholarly research in
ways that are complementary to traditional citation-based indicators. Data
generated from social media activities related to scholarly content can be used
to reflect broad types of impact. This paper aims to provide systematic
evidence regarding how often Twitter is used to diffuse journal articles in the
biomedical and life sciences. The analysis is based on a set of 1.4 million
documents covered by both PubMed and Web of Science (WoS) and published between
2010 and 2012. The number of tweets containing links to these documents was
analyzed to evaluate the degree to which certain journals, disciplines, and
specialties were represented on Twitter. It is shown that, with less than 10%
of PubMed articles mentioned on Twitter, its uptake is low in general. The
relationship between tweets and WoS citations was examined for each document at
the level of journals and specialties. The results show that tweeting behavior
varies between journals and specialties and correlations between tweets and
citations are low, implying that impact metrics based on tweets are different
from those based on citations. A framework utilizing the coverage of articles
and the correlation between Twitter mentions and citations is proposed to
facilitate the evaluation of novel social-media based metrics and to shed light
on the question in how far the number of tweets is a valid metric to measure
research impact.Comment: 22 pages, 4 figures, 5 table
Genesis of Altmetrics or Article-level Metrics for Measuring Efficacy of Scholarly Communications: Current Perspectives
The article-level metrics (ALMs) or altmetrics becomes a new trendsetter in
recent times for measuring the impact of scientific publications and their
social outreach to intended audiences. The popular social networks such as
Facebook, Twitter, and Linkedin and social bookmarks such as Mendeley and
CiteULike are nowadays widely used for communicating research to larger
transnational audiences. In 2012, the San Francisco Declaration on Research
Assessment got signed by the scientific and researchers communities across the
world. This declaration has given preference to the ALM or altmetrics over
traditional but faulty journal impact factor (JIF)-based assessment of career
scientists. JIF does not consider impact or influence beyond citations count as
this count reflected only through Thomson Reuters' Web of Science database.
Furthermore, JIF provides indicator related to the journal, but not related to
a published paper. Thus, altmetrics now becomes an alternative metrics for
performance assessment of individual scientists and their contributed scholarly
publications. This paper provides a glimpse of genesis of altmetrics in
measuring efficacy of scholarly communications and highlights available
altmetric tools and social platforms linking altmetric tools, which are widely
used in deriving altmetric scores of scholarly publications. The paper thus
argues for institutions and policy makers to pay more attention to altmetrics
based indicators for evaluation purpose but cautions that proper safeguards and
validations are needed before their adoption
How the Scientific Community Reacts to Newly Submitted Preprints: Article Downloads, Twitter Mentions, and Citations
We analyze the online response to the preprint publication of a cohort of
4,606 scientific articles submitted to the preprint database arXiv.org between
October 2010 and May 2011. We study three forms of responses to these
preprints: downloads on the arXiv.org site, mentions on the social media site
Twitter, and early citations in the scholarly record. We perform two analyses.
First, we analyze the delay and time span of article downloads and Twitter
mentions following submission, to understand the temporal configuration of
these reactions and whether one precedes or follows the other. Second, we run
regression and correlation tests to investigate the relationship between
Twitter mentions, arXiv downloads and article citations. We find that Twitter
mentions and arXiv downloads of scholarly articles follow two distinct temporal
patterns of activity, with Twitter mentions having shorter delays and narrower
time spans than arXiv downloads. We also find that the volume of Twitter
mentions is statistically correlated with arXiv downloads and early citations
just months after the publication of a preprint, with a possible bias that
favors highly mentioned articles.Comment: 15 pages, 7 Figures, 3 Tables. PLoS One, in pres
Does the public discuss other topics on climate change than researchers? A comparison of explorative networks based on author keywords and hashtags
Twitter accounts have already been used in many scientometric studies, but
the meaningfulness of the data for societal impact measurements in research
evaluation has been questioned. Earlier research focused on social media counts
and neglected the interactive nature of the data. We explore a new network
approach based on Twitter data in which we compare author keywords to hashtags
as indicators of topics. We analyze the topics of tweeted publications and
compare them with the topics of all publications (tweeted and not tweeted). Our
exploratory study is based on a comprehensive publication set of climate change
research. We are interested in whether Twitter data are able to reveal topics
of public discussions which can be separated from research-focused topics. We
find that the most tweeted topics regarding climate change research focus on
the consequences of climate change for humans. Twitter users are interested in
climate change publications which forecast effects of a changing climate on the
environment and to adaptation, mitigation and management issues rather than in
the methodology of climate-change research and causes of climate change. Our
results indicate that publications using scientific jargon are less likely to
be tweeted than publications using more general keywords. Twitter networks seem
to be able to visualize public discussions about specific topics.Comment: 31 pages, 1 table, and 7 figure
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