Page 100 - Journal of Library Science in China, Vol.45, 2019

CHEN Bikun, ZHOU Huixian, ZHONG Zhouyan & WANG Yuefen / Exploring the user platform preference and 099
user interest preference of Chinese scholarly articles: A comparison based on usage metrics

users’ subscription, reading, retrieval and citation has always been attracting researchers’ interests.
In the dominated era of physical scientific literature, scholars carried out their research by tracing
usage data of physical publications, for example, librarians constructing, evaluating collections
(Coombs, 2005; Kraemer, 2006) and exploring user preferences (Pesch, 2006) by analyzing usage
data of subscribed physical publications. As academic exchange platforms continuously improve
their functions of recording user usage data, usage data is treated as an independent and unique
data, different from citation and altmetrics data (Glänzel & Gorraiz, 2015; X.W. Wang, 2016). After
literature investigation, it is found that “Usage Metrics” mainly cover five topics in “Library and
Information Science”. 1) User behavior patterns were studied, such as scientists’ working timetable
(X.W. Wang et al., 2012; X.W. Wang et al., 2013), user preferences (Chen, 2018; Davis & Price,
2006; Davis & Solla, 2003; X.W. Wang, Fang, & Sun, 2016; X.W. Wang, Xu, & Fang, 2016) and
user temporal usage patterns (Chen, Zhong, & Zhan, 2017; Khan &Younas, 2017). 2) Obsolescence
of articles from diachronic or synchronic perspective was analyzed. For example, Moed and Halevi
(Moed, 2005; Moed & Halevi, 2016) studied diachronic and synchronic obsolescence of usage data
from perspective of journals and countries. Gorraiz, Gumpenberger, and Schloegl (2014) did the
similar research from the perspective of disciplines. 3) Latest research trends of disciplines were
identified (Bollen, Luce, Vemulapalli, & Xu, 2003; X.W. Wang, Z.Wang, & Xu, 2013). 4) Usage
data were used as indicators to evaluate performance of journals, authors, groups and countries
(Chi & Glänzel, 2018; De Sordi, Conejero, & Meireles, 2016; Wan, Hua, Rousseau, & Sun, 2010)
or supplementary metrics jointly with altmetrics measures (Bollen, Sompel, Smith, & Luce, 2005;
Kurtz & Henneken, 2016). 5) Correlation between specific usage types was explored, including
downloads and citations (Cao, Y.F. Wang, & Ding, 2012; Kurtz & Bollen, 2010; O’Leary, 2008;
Schloegl, Gorraiz, Gumpenberger, Jack, & Kraker, 2014; Subotic & Mukherjee, 2014; Zhao, 2017),
usage data among different platforms (Chen, 2017; Chen et al., 2017), usage data and author counts
(Chi & Glänzel, 2017), or funding data (Zhao, Lou, Tan, & Yu, 2018).
All the researches above mostly referred to usage data from English publishers or English
citation index databases (such as Web of Science, Elseiver and Springer-Nature). Although some
research focused on Chinese usage data, it was limited to CNKI platform and thus sample data
were single and small. Up to now, an increasing number of Chinese journal official websites have
begun to provide HTML browsing data or PDF downloading data of academic papers, which offers
a new opportunity for Chinese usage metrics research. For this reason, this study comparatively
analyzes usage data from both Chinese journal official websites and information integration
platform (such as CNKI, usually pay-for-access) to explore their user platform preferences and
user interest preferences, promoting user pattern research and decision-making.
Academic papers from 61 Chinese open-access journals in the fields of “Library, Information
and Archival Science”, “Management Science”, “Economics”, “Pedagogy”, “Computer Science”,
“Earth Science”, “Math” and “Biology”, published during 2014-2015 and indexed by CSSCI
(Chinese Social Sciences Citation Index) and CSCD (Chinese Science Citation Database), are