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.
%0 Journal Article
%1 Shuai2012How
%A Shuai, Xin
%A Pepe, Alberto
%A Bollen, Johan
%D 2012
%I Public Library of Science
%J PLoS ONE
%K twitter citations social
%N 11
%P e47523+
%R 10.1371/journal.pone.0047523
%T How the Scientific Community Reacts to Newly Submitted Preprints: Article Downloads, Twitter Mentions, and Citations
%U http://dx.doi.org/10.1371/journal.pone.0047523
%V 7
%X 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.
@article{Shuai2012How,
abstract = {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.},
added-at = {2018-06-18T21:23:34.000+0200},
archiveprefix = {arXiv},
author = {Shuai, Xin and Pepe, Alberto and Bollen, Johan},
biburl = {https://www.bibsonomy.org/bibtex/2974589a5034abcaa9c7a2b3ab5da4406/pbett},
citeulike-article-id = {11602969},
citeulike-linkout-0 = {http://arxiv.org/abs/1202.2461},
citeulike-linkout-1 = {http://arxiv.org/pdf/1202.2461},
citeulike-linkout-2 = {http://dx.doi.org/10.1371/journal.pone.0047523},
day = 17,
doi = {10.1371/journal.pone.0047523},
eprint = {1202.2461},
interhash = {8331e7736f3cc8296cafd7e6397dc010},
intrahash = {974589a5034abcaa9c7a2b3ab5da4406},
issn = {1932-6203},
journal = {PLoS ONE},
keywords = {twitter citations social},
month = sep,
number = 11,
pages = {e47523+},
posted-at = {2013-03-07 19:43:29},
priority = {2},
publisher = {Public Library of Science},
timestamp = {2018-06-22T18:32:57.000+0200},
title = {How the Scientific Community Reacts to Newly Submitted Preprints: Article Downloads, Twitter Mentions, and Citations},
url = {http://dx.doi.org/10.1371/journal.pone.0047523},
volume = 7,
year = 2012
}