Measuring Social Media Activity of Scientific Literature: An Exhaustive Comparison of Scopus and Novel Altmetrics Big Data
This paper measures social media activity of 15 broad scientific disciplines indexed in Scopus database using Altmetric.com data. First, the presence of Altmetric.com data in Scopus database is investigated, overall and across disciplines. Second, the correlation between the bibliometric and altmetr...
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creator | Hassan, Saeed-Ul Imran, Mubashir Gillani, Uzair Aljohani, Naif Radi Bowman, Timothy D Didegah, Fereshteh |
description | This paper measures social media activity of 15 broad scientific disciplines
indexed in Scopus database using Altmetric.com data. First, the presence of
Altmetric.com data in Scopus database is investigated, overall and across
disciplines. Second, the correlation between the bibliometric and altmetric
indices is examined using Spearman correlation. Third, a zero-truncated
negative binomial model is used to determine the association of various factors
with increasing or decreasing citations. Lastly, the effectiveness of altmetric
indices to identify publications with high citation impact is comprehensively
evaluated by deploying Area Under the Curve (AUC) - an application of receiver
operating characteristic. Results indicate a rapid increase in the presence of
Altmetric.com data in Scopus database from 10.19% in 2011 to 20.46% in 2015. A
zero-truncated negative binomial model is implemented to measure the extent to
which different bibliometric and altmetric factors contribute to citation
counts. Blog count appears to be the most important factor increasing the
number of citations by 38.6% in the field of Health Professions and Nursing,
followed by Twitter count increasing the number of citations by 8% in the field
of Physics and Astronomy. Interestingly, both Blog count and Twitter count
always show positive increase in the number of citations across all fields.
While there was a positive weak correlation between bibliometric and altmetric
indices, the results show that altmetric indices can be a good indicator to
discriminate highly cited publications, with an encouragingly AUC= 0.725
between highly cited publications and total altmetric count. Overall, findings
suggest that altmetrics could better distinguish highly cited publications. |
doi_str_mv | 10.48550/arxiv.1705.03258 |
format | Article |
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indexed in Scopus database using Altmetric.com data. First, the presence of
Altmetric.com data in Scopus database is investigated, overall and across
disciplines. Second, the correlation between the bibliometric and altmetric
indices is examined using Spearman correlation. Third, a zero-truncated
negative binomial model is used to determine the association of various factors
with increasing or decreasing citations. Lastly, the effectiveness of altmetric
indices to identify publications with high citation impact is comprehensively
evaluated by deploying Area Under the Curve (AUC) - an application of receiver
operating characteristic. Results indicate a rapid increase in the presence of
Altmetric.com data in Scopus database from 10.19% in 2011 to 20.46% in 2015. A
zero-truncated negative binomial model is implemented to measure the extent to
which different bibliometric and altmetric factors contribute to citation
counts. Blog count appears to be the most important factor increasing the
number of citations by 38.6% in the field of Health Professions and Nursing,
followed by Twitter count increasing the number of citations by 8% in the field
of Physics and Astronomy. Interestingly, both Blog count and Twitter count
always show positive increase in the number of citations across all fields.
While there was a positive weak correlation between bibliometric and altmetric
indices, the results show that altmetric indices can be a good indicator to
discriminate highly cited publications, with an encouragingly AUC= 0.725
between highly cited publications and total altmetric count. Overall, findings
suggest that altmetrics could better distinguish highly cited publications.</description><identifier>DOI: 10.48550/arxiv.1705.03258</identifier><language>eng</language><subject>Computer Science - Digital Libraries</subject><creationdate>2017-05</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,777,882</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/1705.03258$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.1705.03258$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Hassan, Saeed-Ul</creatorcontrib><creatorcontrib>Imran, Mubashir</creatorcontrib><creatorcontrib>Gillani, Uzair</creatorcontrib><creatorcontrib>Aljohani, Naif Radi</creatorcontrib><creatorcontrib>Bowman, Timothy D</creatorcontrib><creatorcontrib>Didegah, Fereshteh</creatorcontrib><title>Measuring Social Media Activity of Scientific Literature: An Exhaustive Comparison of Scopus and Novel Altmetrics Big Data</title><description>This paper measures social media activity of 15 broad scientific disciplines
indexed in Scopus database using Altmetric.com data. First, the presence of
Altmetric.com data in Scopus database is investigated, overall and across
disciplines. Second, the correlation between the bibliometric and altmetric
indices is examined using Spearman correlation. Third, a zero-truncated
negative binomial model is used to determine the association of various factors
with increasing or decreasing citations. Lastly, the effectiveness of altmetric
indices to identify publications with high citation impact is comprehensively
evaluated by deploying Area Under the Curve (AUC) - an application of receiver
operating characteristic. Results indicate a rapid increase in the presence of
Altmetric.com data in Scopus database from 10.19% in 2011 to 20.46% in 2015. A
zero-truncated negative binomial model is implemented to measure the extent to
which different bibliometric and altmetric factors contribute to citation
counts. Blog count appears to be the most important factor increasing the
number of citations by 38.6% in the field of Health Professions and Nursing,
followed by Twitter count increasing the number of citations by 8% in the field
of Physics and Astronomy. Interestingly, both Blog count and Twitter count
always show positive increase in the number of citations across all fields.
While there was a positive weak correlation between bibliometric and altmetric
indices, the results show that altmetric indices can be a good indicator to
discriminate highly cited publications, with an encouragingly AUC= 0.725
between highly cited publications and total altmetric count. Overall, findings
suggest that altmetrics could better distinguish highly cited publications.</description><subject>Computer Science - Digital Libraries</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotkMtOwzAQRbNhgQofwIr5gQQncRqXXQjlIbWwaPfRxB6XkfKS40QtXw-0rO7m3iPdEwR3sYikyjLxgO7IcxTnIotEmmTqOvjeEo6T4-4Au14zNrAlwwiF9jyzP0FvYaeZOs-WNWzYk0M_OXqEooP18Qun8bdJUPbtgI7HvrtM-mEaATsDH_1MDRSNb8k71iM88QGe0eNNcGWxGen2PxfB_mW9L9_Czefre1lsQlzmKlTpipSyiRWpxETVCk1tqEZjFAmlhUwt5jlZE8tY1KRrma-klKpeWpPlwqSL4P6CPZ-vBsctulP1J6E6S0h_AMVIWX8</recordid><startdate>20170509</startdate><enddate>20170509</enddate><creator>Hassan, Saeed-Ul</creator><creator>Imran, Mubashir</creator><creator>Gillani, Uzair</creator><creator>Aljohani, Naif Radi</creator><creator>Bowman, Timothy D</creator><creator>Didegah, Fereshteh</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20170509</creationdate><title>Measuring Social Media Activity of Scientific Literature: An Exhaustive Comparison of Scopus and Novel Altmetrics Big Data</title><author>Hassan, Saeed-Ul ; Imran, Mubashir ; Gillani, Uzair ; Aljohani, Naif Radi ; Bowman, Timothy D ; Didegah, Fereshteh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a678-839e88f2f034a28b8adbdebadd8e08c043fa77efd1410becb4794448b6fd570d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Computer Science - Digital Libraries</topic><toplevel>online_resources</toplevel><creatorcontrib>Hassan, Saeed-Ul</creatorcontrib><creatorcontrib>Imran, Mubashir</creatorcontrib><creatorcontrib>Gillani, Uzair</creatorcontrib><creatorcontrib>Aljohani, Naif Radi</creatorcontrib><creatorcontrib>Bowman, Timothy D</creatorcontrib><creatorcontrib>Didegah, Fereshteh</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hassan, Saeed-Ul</au><au>Imran, Mubashir</au><au>Gillani, Uzair</au><au>Aljohani, Naif Radi</au><au>Bowman, Timothy D</au><au>Didegah, Fereshteh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Measuring Social Media Activity of Scientific Literature: An Exhaustive Comparison of Scopus and Novel Altmetrics Big Data</atitle><date>2017-05-09</date><risdate>2017</risdate><abstract>This paper measures social media activity of 15 broad scientific disciplines
indexed in Scopus database using Altmetric.com data. First, the presence of
Altmetric.com data in Scopus database is investigated, overall and across
disciplines. Second, the correlation between the bibliometric and altmetric
indices is examined using Spearman correlation. Third, a zero-truncated
negative binomial model is used to determine the association of various factors
with increasing or decreasing citations. Lastly, the effectiveness of altmetric
indices to identify publications with high citation impact is comprehensively
evaluated by deploying Area Under the Curve (AUC) - an application of receiver
operating characteristic. Results indicate a rapid increase in the presence of
Altmetric.com data in Scopus database from 10.19% in 2011 to 20.46% in 2015. A
zero-truncated negative binomial model is implemented to measure the extent to
which different bibliometric and altmetric factors contribute to citation
counts. Blog count appears to be the most important factor increasing the
number of citations by 38.6% in the field of Health Professions and Nursing,
followed by Twitter count increasing the number of citations by 8% in the field
of Physics and Astronomy. Interestingly, both Blog count and Twitter count
always show positive increase in the number of citations across all fields.
While there was a positive weak correlation between bibliometric and altmetric
indices, the results show that altmetric indices can be a good indicator to
discriminate highly cited publications, with an encouragingly AUC= 0.725
between highly cited publications and total altmetric count. Overall, findings
suggest that altmetrics could better distinguish highly cited publications.</abstract><doi>10.48550/arxiv.1705.03258</doi><oa>free_for_read</oa></addata></record> |
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source | arXiv.org |
subjects | Computer Science - Digital Libraries |
title | Measuring Social Media Activity of Scientific Literature: An Exhaustive Comparison of Scopus and Novel Altmetrics Big Data |
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