To get cited or get tweeted: a study of psychological academic articles
| DOI | https://doi.org/10.1108/OIR-08-2017-0235 |
| Published date | 12 November 2018 |
| Pages | 1065-1081 |
| Date | 12 November 2018 |
| Author | Yingxin Estella Ye,Jin-Cheon Na |
| Subject Matter | Library & information science,Information behaviour & retrieval,Collection building & management,Bibliometrics,Databases,Information & knowledge management,Information & communications technology,Internet,Records management & preservation,Document management |
To get cited or get tweeted:
a study of psychological
academic articles
Yingxin Estella Ye
NUS Libraries, National University of Singapore, Singapore, and
Jin-Cheon Na
Wee Kim Wee School of Communication and Information,
Nanyang Technological University, Singapore
Abstract
Purpose –By analyzing journal articles with high citation counts but low Twitter mentions and vice versa,
the purpose of this paper is to provide an overall picture of differences between citation counts and Twitter
mentions of academic articles.
Design/methodology/approach –Citation counts from the Web of Science and Twitter mentions of
psychological articles under the Social Science Citation Index collection were collected for data analysis.
An approach combining both statistical and simple content analysis was adopted to examine important
factors contributing to citation counts and Twitter mentions, as well as the patterns of tweets
mentioning academic articles.
Findings –Compared to citation counts, Twitter mentions have stronger affiliations with readability and
accessibility of academic papers. Readability here was defined as the content size of articles and the usage of
jargon and scientific expressions. In addition, Twitter activities, such as the use of hashtags and user
mentions, could better facilitate the sharing of articles. Even though discussions of articles or related social
phenomena were spotted in the contents of tweets, simple counts of Twitter mentions may not be reliable
enough for research evaluations due to issues such as Twitter bots and a deficient understanding of Twitter
users’motivations for mentioning academic articles on Twitter.
Originality/value –This study has elaborated on the differences between Twitter mentions and citation
counts by comparing the characteristics of Twitter-inclined and citation-inclined articles. It provides useful
information for interested parties who would like to adopt social web metrics such as Twitter mentions as
traces of broader engagement with academic literature and potential suggestions to increase the reliability of
Twitter metrics. In addition, it gives specific tips for researchers to increase research visibility and get
attention from the general public on Twitter.
Keywords Twitter, Altmetrics, Citation, Social web, Scholarly communication
Paper type Research paper
Introduction
Assessing and evaluating the impacts of scholarly outputs is an essential process in
scientific progress and the knowledge advancement of society. Derived from peer-review
publishing, citation analysis is the dominant form of scholarly communication and was
developed as the primary mechanism for evaluating research (Haustein, Sugimoto and
Larivière, 2015).
The development of the internet has ca st new light on traditional scholarly
communication. (Gu and Widén‐Wulff, 2011). Web 2.0 tools, such as reference managing
websites (e.g. Mendeley and CiteULike), wikis, blogs, and social networking sites
(e.g. Twitter and Facebook), have sparked faster and less formal methods for scholarly
communication and have opened up the boundaries across academia and non-academic
communities (Shema, Bar-Ilan and Thelwall, 2012). An increasing number of researchers
would like to use the social web to maintain awareness about latest research news and
information, disseminate information, interact with diverse audiences, connect with peers in
professional networks (Manca and Ranieri, 2016; Veletsianos and Kimmons, 2016;
Van Noorden, 2014). Correspondingly, these tools and platforms have yielded broader and
Online Information Review
Vol. 42 No. 7, 2018
pp. 1065-1081
© Emerald PublishingLimited
1468-4527
DOI 10.1108/OIR-08-2017-0235
Received 13 August 2017
Revised 19 December 2017
22 April 2018
Accepted 24 April 2018
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1468-4527.htm
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Psychological
academic
articles
timelier impact assessments of scholarly outputs using altmetrics based on social web
activities, such as readership, discussions, sharing, and recommendations for a variety of
audiences (Fenner, 2014; Das and Mishra, 2014).
Utilizing psychological academic articles as a case study, we examine the differences
between citation counts and Twitter mentions in research evaluations. We studied the
Twitter mentions of academic articles for the following reasons: Twitter is a primary social
media platform used by scientists and researchers (Peoples et al., 2016); and the diversity of
the Twitter community allows us to draw a comprehensive picture of scholarly
communication on the social web, and also the meaning of social web metrics (Barthel et al.,
2015). The field of psychology was selected because it is one of the most popular subjects on
social media platforms (Mohammadi and Thelwall, 2014).
The main goal of thisstudy is to better comprehend the role that Twitterplays in scholarly
communication,and the value of Twitter mentions in researchassessment. It aims to provide
useful information to parties including funding agencies, university administrators, and
policymakers whowould like to adopt social web metrics such as Twittermentions as traces
of broader engagement with academic literature. These traces may be of interest to these
parties asthe use of academic literatureextends beyond the academiccommunity. We also try
to encourage and offer tips for researchers to share their research outputs with a larger
audience on the social web for higher research visibility and impact.
In this study, starting with a review of existing scholarship examining citation counts,
altmetrics, and their determinants, we compared highly cited and highly tweeted articles to
identify distinct differences between citation counts and Twitter mentions. We first
explored how selected attributes including document characteristics, sources, accessibility,
wording and research topics influence differences between citation counts and Twitter
mentions. We then investigated the patterns of Tweets citing these academic articles with a
simple content analysis approach in which we covered various variables including
hashtags, user mentions, and retweets.
Literature review
Citation counts and altmetrics
The emergence of altmetrics has attracted wide attention from scholars. Altmetrics are
regarded as alternative metrics of research evaluations because they make up for the
deficiencies of traditional impact assessments; for example, they can handle the most recent
publications (Brigham, 2014), they expandthe targets of measurements to scholarly works in
various formats not limited to written works (Piwowar, 2013), and aggregated altmetrics are
able to reflect the achievements of researchers (Mounce, 2013). However, there are some
debates regarding the validity of altmetrics. For example, due to the lack of rigorous
regulations, cyber-based metrics may not be as reliable as peer-reviewed citations. They can
be easily manipulated: for example, “buying”or “selling”posts engagements such as “like”
and “share”can leadto a dramatic increase of socialweb mentions. Moreover, withoutrobust
filtering mechanisms or standards,the results of research assessment can be exaggerated due
to “spam”posts (Barthel et al., 2015). Altmetrics, in use as a type of social web metrics, may
also be influenced by heuristics such as authority and bandwagons cues through which the
contents postedby authorities and users with many followersare more easily mentioned and
disseminated. It is also more likely for social media users to cite their peers’posts (Lee and
Sundar, 2013;Lin et al., 2016). Stemming froma deficient understanding ofthe actual meaning
of altmetrics, traditional bibliometrics are still the only assessment mechanism of research
impacts used by majority of academic institutions (Peoples et al., 2016).
Considerable research has been undertaken regarding correlations between citation
counts and social web mentions. A majority of these studies have concentrated on the
following questions: whether altmetrics can predict traditional bibliometrics, whether
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