-
Milojevic, S.; Sugimoto, C.R.; Yan, E.; Ding, Y.: ¬The cognitive structure of Library and Information Science : analysis of article title words (2011)
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- Field
- Bibliothekswesen
Informationswissenschaft
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Yan, E.; Ding, Y.: Discovering author impact : a PageRank perspective (2011)
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- Abstract
- This article provides an alternative perspective for measuring author impact by applying PageRank algorithm to a coauthorship network. A weighted PageRank algorithm considering citation and coauthorship network topology is proposed. We test this algorithm under different damping factors by evaluating author impact in the informetrics research community. In addition, we also compare this weighted PageRank with the h-index, citation, and program committee (PC) membership of the International Society for Scientometrics and Informetrics (ISSI) conferences. Findings show that this weighted PageRank algorithm provides reliable results in measuring author impact.
- Source
- Information processing and management. 47(2011) no.1, S.125-134
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Zhao, M.; Yan, E.; Li, K.: Data set mentions and citations : a content analysis of full-text publications (2018)
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- Date
- 18.12.2017 16:29:01
- Source
- Journal of the Association for Information Science and Technology. 69(2018) no.1, S.32-46
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Yan, E.: Finding knowledge paths among scientific disciplines (2014)
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- Date
- 26.10.2014 20:22:22
-
Ding, Y.; Yan, E.: Scholarly network similarities : how bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other (2012)
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- Abstract
- This study explores the similarity among six types of scholarly networks aggregated at the institution level, including bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks. Cosine distance is chosen to measure the similarities among the six networks. The authors found that topical networks and coauthorship networks have the lowest similarity; cocitation networks and citation networks have high similarity; bibliographic coupling networks and cocitation networks have high similarity; and coword networks and topical networks have high similarity. In addition, through multidimensional scaling, two dimensions can be identified among the six networks: Dimension 1 can be interpreted as citation-based versus noncitation-based, and Dimension 2 can be interpreted as social versus cognitive. The authors recommend the use of hybrid or heterogeneous networks to study research interaction and scholarly communications.
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Pan, X.; Yan, E.; Hua, W.: Science communication and dissemination in different cultures : an analysis of the audience for TED videos in China and abroad (2016)
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- Abstract
- Disseminated across the world in more than 100 languages and viewed over 1 billion times, TED Talks is a successful example of web-based science communication. This study investigates the impact of TED Talks videos on YouKu, a Chinese video portal, and YouTube using 6 measures of impact: number of views; likes; dislikes; comments; bookmarks; and shares. In particular, we study the relationship between the topicality and impact of these videos. Findings demonstrate that topics vary greatly in terms of their impact: Topics on entertainment and psychology/philosophy receive more views and likes, whereas design/art and astronomy/biology/oceanography attract fewer comments and bookmarks. Moreover, we identify several topical differences between YouKu and YouTube users. Topics on global issues and technology are more popular on YouKu, whereas topics on entertainment and psychology/philosophy are more popular on YouTube. By analyzing the popularity distribution of videos and the audience characteristics of YouKu, we find that women are more interested in topics on education and psychology/philosophy, whereas men favor topics on technology and astronomy/biology/oceanography.
-
Yan, E.; Li, K.: Which domains do open-access journals do best in? : a 5-year longitudinal study (2018)
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- Abstract
- Although researchers have begun to investigate the difference in scientific impact between closed-access and open-access journals, studies that focus specifically on dynamic and disciplinary differences remain scarce. This study serves to fill this gap by using a large longitudinal dataset to examine these differences. Using CiteScore as a proxy for journal scientific impact, we employ a series of statistical tests to identify the quartile categories and disciplinary areas in which impact trends differ notably between closed- and open-access journals. We find that closed-access journals have a noticeable advantage in social sciences (for example, business and economics), whereas open-access journals perform well in medical and healthcare domains (for example, health profession and nursing). Moreover, we find that after controlling for a journal's rank and disciplinary differences, there are statistically more closed-access journals in the top 10%, Quartile 1, and Quartile 2 categories as measured by CiteScore; in contrast, more open-access journals in Quartile 4 gained scientific impact from 2011 to 2015. Considering dynamic and disciplinary trends in tandem, we find that more closed-access journals in Social Sciences gained in impact, whereas in biochemistry and medicine, more open-access journals experienced such gains.
