Page 162 - JOURNAL OF LIBRARY SCIENCE IN CHINA 2018 Vol. 42

YU Houqiang，Bradley M. Hemminger，XIAO Tingting & QIU Junping / Features of Sina Weibo altmetrics indicator 161

scientific big data.
Altmetrics is transforming from the idea (Priem, 2013) and theoretical (Qiu & Yu, 2015; Yu
& Qiu, 2014) discussion to more empirical (Y. Wang, S. Guo, & Zhang, 2015), experimental
(Friedrich, Bowman, Stock, & Haustein, 2015) and application (Das, 2015) oriented researches.
Related researches can be reviewed in four categories. The first is further investigation into single
altmetrics data source. These researches can provide reference for studying other novel data
sources. The prevailing explored data sources are Twitter (Haustein, Peters, Sugimoto, Thelwall,
& Larivière , 2014), Mendeley (Thelwall & Wilson, 2015; Song, J. F. Wang, & S. Y. Wang, 2014),
ResearchBlogging (Shema, Bar-ilan, & Thelwall, 2014), F1000 (Mohammadi & Thelwall, 2012),
ResearchGate (Thelwall & Kousha, 2014) and Youtube (Kousha, Thelwall, & Abdoli, 2012) etc.
The second is researches on novel types of scholarly products. These scholarly products include
blog (Shema, Bar-Ilan, & Thelwall, 2012), software (ImpactStory, 2016), slides (Kraker, Lex，
Gorraiz, Gumpenberger, Peters, 2015), dataset (Peters, Kraker, Lex, Gumpenberger, Gorraiz,
2015) and video (Kousha, Thelwall, & Abdoli, 2012) etc. The third is scientific evaluation
based on comprehensive altmetrics indicators. The major data providers are Altmetric.com and
ImpactStory. Evaluated objects can be journal (Loach & Evans, 2015), institution (Rehemtula,
Avilés, Rosa, Leitão, 2015), discipline (Holmberg & Thelwall, 2014) and scientists (Kolahi, 2015)
etc. The fourth is to adopt altmetrics indicators for literature retrieval. The retrieval entry can be
comprehensive score or single indicator (Dawson, 2016).
In China, researches of altmetrics have achieved some progress as well. Empirical studies
focused on the correlation between altmetrics indicators and citations (Liu, Zhou, & You, 2015),
and evaluation based on altmetrics indicators (R. Wang, Hu, & W. Guo, 2014), with few tapping
into the meaning of altmetrics indicators and none investigating Chinese altmetrics source. The
research analyzed Sina Weibo altmetrics, and aimed at providing reference for studying and
developing domestic altmetrics indicators. Research questions are: 1) Does Sina Weibo discuss
scholarly articles? And to what extent? 2) What kind of scholarly articles does Sina Weibo discuss?
3) What’s the overall performance of scholarly articles with Sina Weibo attention in Altmetric
attention score compared with the others?

1 Data and processing

1.1 Terms used in the article

Sina Weibo altmetrics indicator, in the following content, refers to Sina Weibo Mention. If a
scholarly product is mentioned in a Sina Weibo via trackable form, the scholarly product is said to
receive a Sina Weibo Mention, or the scholarly product is discussed by Sina Weibo. Currently, the
academia labels altmetrics indicators from two perspectives. The first perspective is information
behavior, for example, mention altmetrics indicator, readership altmetrics indicator and rating