Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.
© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 18. September 2018)
1Zhao, M. ; Yan, E. ; Li, K.: Data set mentions and citations : a content analysis of full-text publications.
In: Journal of the Association for Information Science and Technology. 69(2018) no.1, S.32-46.
Abstract: This study provides evidence of data set mentions and citations in multiple disciplines based on a content analysis of 600 publications in PLoS One. We find that data set mentions and citations varied greatly among disciplines in terms of how data sets were collected, referenced, and curated. While a majority of articles provided free access to data, formal ways of data attribution such as DOIs and data citations were used in a limited number of articles. In addition, data reuse took place in less than 30% of the publications that used data, suggesting that researchers are still inclined to create and use their own data sets, rather than reusing previously curated data. This paper provides a comprehensive understanding of how data sets are used in science and helps institutions and publishers make useful data policies.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23919/full.
Objekt: PLoS One
2Yan, E. ; Li, K.: Which domains do open-access journals do best in? : a 5-year longitudinal study.
In: Journal of the Association for Information Science and Technology. 69(2018) no.6, S.844-856.
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.
Inhalt: Vgl.: https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.24002.
3Zhu, Y. ; Yan, E. ; Song, I.-Y..: ¬The use of a graph-based system to improve bibliographic information retrieval : system design, implementation, and evaluation.
In: Journal of the Association for Information Science and Technology. 68(2017) no.2, S.480-490.
Abstract: In this article, we propose a graph-based interactive bibliographic information retrieval system-GIBIR. GIBIR provides an effective way to retrieve bibliographic information. The system represents bibliographic information as networks and provides a form-based query interface. Users can develop their queries interactively by referencing the system-generated graph queries. Complex queries such as "papers on information retrieval, which were cited by John's papers that had been presented in SIGIR" can be effectively answered by the system. We evaluate the proposed system by developing another relational database-based bibliographic information retrieval system with the same interface and functions. Experiment results show that the proposed system executes the same queries much faster than the relational database-based system, and on average, our system reduced the execution time by 72% (for 3-node query), 89% (for 4-node query), and 99% (for 5-node query).
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23677/full.
4Yan, E. ; Zhu, Y.: Adding the dimension of knowledge trading to source impact assessment : approaches, indicators, and implications.
In: Journal of the Association for Information Science and Technology. 68(2017) no.5, S.1090-1104.
Abstract: The objective of this paper is to systematically assess sources' (e.g., journals and proceedings) impact in knowledge trading. While there have been efforts at evaluating different aspects of journal impact, the dimension of knowledge trading is largely absent. To fill the gap, this study employed a set of trading-based indicators, including weighted degree centrality, Shannon entropy, and weighted betweenness centrality, to assess sources' trading impact. These indicators were applied to several time-sliced source-to-source citation networks that comprise 33,634 sources indexed in the Scopus database. The results show that several interdisciplinary sources, such as Nature, PLoS One, Proceedings of the National Academy of Sciences, and Science, and several specialty sources, such as Lancet, Lecture Notes in Computer Science, Journal of the American Chemical Society, Journal of Biological Chemistry, and New England Journal of Medicine, have demonstrated their marked importance in knowledge trading. Furthermore, this study also reveals that, overall, sources have established more trading partners, increased their trading volumes, broadened their trading areas, and diversified their trading contents over the past 15 years from 1997 to 2011. These results inform the understanding of source-level impact assessment and knowledge diffusion.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23670/full.
5Pan, X. ; Yan, E. ; Hua, W.: Science communication and dissemination in different cultures : an analysis of the audience for TED videos in China and abroad.
In: Journal of the Association for Information Science and Technology. 67(2016) no.6, S.1473-1486.
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.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23461/abstract.
6Yan, E. ; Yu, Q.: Using path-based approaches to examine the dynamic structure of discipline-level citation networks.
In: Journal of the Association for Information Science and Technology. 67(2016) no.8, S.1943-1955.
Abstract: The objective of this paper is to identify the dynamic structure of several time-dependent, discipline-level citation networks through a path-based method. A network data set is prepared that comprises 27 subjects and their citations aggregated from more than 27,000 journals and proceedings indexed in the Scopus database. A maximum spanning tree method is employed to extract paths in the weighted, directed, and cyclic networks. This paper finds that subjects such as Medicine, Biochemistry, Chemistry, Materials Science, Physics, and Social Sciences are the ones with multiple branches in the spanning tree. This paper also finds that most paths connect science, technology, engineering, and mathematics (STEM) fields; 2 critical paths connecting STEM and non-STEM fields are the one from Mathematics to Decision Sciences and the one from Medicine to Social Sciences.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23516/abstract.
7Yan, E.: Disciplinary knowledge production and diffusion in science.
In: Journal of the Association for Information Science and Technology. 67(2016) no.9, S.2223-2245.
Abstract: This study examines patterns of dynamic disciplinary knowledge production and diffusion. It uses a citation data set of Scopus-indexed journals and proceedings. The journal-level citation data set is aggregated into 27 subject areas and these subjects are selected as the unit of analysis. A 3-step approach is employed: the first step examines disciplines' citation characteristics through scientific trading dimensions; the second step analyzes citation flows between pairs of disciplines; and the third step uses egocentric citation networks to assess individual disciplines' citation flow diversity through Shannon entropy. The results show that measured by scientific impact, the subjects of Chemical Engineering, Energy, and Environmental Science have the fastest growth. Furthermore, most subjects are carrying out more diversified knowledge trading practices by importing higher volumes of knowledge from a greater number of subjects. The study also finds that the growth rates of disciplinary citations align with the growth rates of global research and development (R&D) expenditures, thus providing evidence to support the impact of R&D expenditures on knowledge production.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23541/full.
8Yan, E.: Research dynamics, impact, and dissemination : a topic-level analysis.
In: Journal of the Association for Information Science and Technology. 66(2015) no.11, S.2357-2372.
Abstract: In informetrics, journals have been used as a standard unit to analyze research impact, productivity, and scholarship. The increasing practice of interdisciplinary research challenges the effectiveness of journal-based assessments. The aim of this article is to highlight topics as a valuable unit of analysis. A set of topic-based approaches is applied to a data set on library and information science publications. Results show that topic-based approaches are capable of revealing the research dynamics, impact, and dissemination of the selected data set. The article also identifies a nonsignificant relationship between topic popularity and impact and argues for the need to use both variables in describing topic characteristics. Additionally, a flow map illustrates critical topic-level knowledge dissemination channels.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23324/abstract.
9Hu, B. ; Dong, X. ; Zhang, C. ; Bowman, T.D. ; Ding, Y. ; Milojevic, S. ; Ni, C. ; Yan, E. ; Larivière, V.: ¬A lead-lag analysis of the topic evolution patterns for preprints and publications.
In: Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2643-2656.
Abstract: This study applied LDA (latent Dirichlet allocation) and regression analysis to conduct a lead-lag analysis to identify different topic evolution patterns between preprints and papers from arXiv and the Web of Science (WoS) in astrophysics over the last 20 years (1992-2011). Fifty topics in arXiv and WoS were generated using an LDA algorithm and then regression models were used to explain 4 types of topic growth patterns. Based on the slopes of the fitted equation curves, the paper redefines the topic trends and popularity. Results show that arXiv and WoS share similar topics in a given domain, but differ in evolution trends. Topics in WoS lose their popularity much earlier and their durations of popularity are shorter than those in arXiv. This work demonstrates that open access preprints have stronger growth tendency as compared to traditional printed publications.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23347/abstract.
Themenfeld: Elektronisches Publizieren
10Yan, E.: Finding knowledge paths among scientific disciplines.
In: Journal of the Association for Information Science and Technology. 65(2014) no.11, S.2331-2347.
Abstract: This paper uncovers patterns of knowledge dissemination among scientific disciplines. Although the transfer of knowledge is largely unobservable, citations from one discipline to another have been proven to be an effective proxy to study disciplinary knowledge flow. This study constructs a knowledge-flow network in which a node represents a Journal Citation Reports subject category and a link denotes the citations from one subject category to another. Using the concept of shortest path, several quantitative measurements are proposed and applied to a knowledge-flow network. Based on an examination of subject categories in Journal Citation Reports, this study indicates that social science domains tend to be more self-contained, so it is more difficult for knowledge from other domains to flow into them; at the same time, knowledge from science domains, such as biomedicine-, chemistry-, and physics-related domains, can access and be accessed by other domains more easily. This study also shows that social science domains are more disunified than science domains, because three fifths of the knowledge paths from one social science domain to another require at least one science domain to serve as an intermediate. This work contributes to discussions on disciplinarity and interdisciplinarity by providing empirical analysis.
11Ding, 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.
In: Journal of the American Society for Information Science and Technology. 63(2012) no.7, S.1313-1326.
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.
12Yan, E. ; Ding, Y. ; Sugimoto, C.R.: P-Rank: an indicator measuring prestige in heterogeneous scholarly networks.
In: Journal of the American Society for Information Science and Technology. 62(2011) no.3, S.467-477.
Abstract: Ranking scientific productivity and prestige are often limited to homogeneous networks. These networks are unable to account for the multiple factors that constitute the scholarly communication and reward system. This study proposes a new informetric indicator, P-Rank, for measuring prestige in heterogeneous scholarly networks containing articles, authors, and journals. P-Rank differentiates the weight of each citation based on its citing papers, citing journals, and citing authors. Articles from 16 representative library and information science journals are selected as the dataset. Principle Component Analysis is conducted to examine the relationship between P-Rank and other bibliometric indicators. We also compare the correlation and rank variances between citation counts and P-Rank scores. This work provides a new approach to examining prestige in scholarly communication networks in a more comprehensive and nuanced way.
13Milojevic, S. ; Sugimoto, C.R. ; Yan, E. ; Ding, Y.: ¬The cognitive structure of Library and Information Science : analysis of article title words.
In: Journal of the American Society for Information Science and Technology. 62(2011) no.10, S.1933-1953.
Abstract: This study comprises a suite of analyses of words in article titles in order to reveal the cognitive structure of Library and Information Science (LIS). The use of title words to elucidate the cognitive structure of LIS has been relatively neglected. The present study addresses this gap by performing (a) co-word analysis and hierarchical clustering, (b) multidimensional scaling, and (c) determination of trends in usage of terms. The study is based on 10,344 articles published between 1988 and 2007 in 16 LIS journals. Methodologically, novel aspects of this study are: (a) its large scale, (b) removal of non-specific title words based on the "word concentration" measure (c) identification of the most frequent terms that include both single words and phrases, and (d) presentation of the relative frequencies of terms using "heatmaps". Conceptually, our analysis reveals that LIS consists of three main branches: the traditionally recognized library-related and information-related branches, plus an equally distinct bibliometrics/scientometrics branch. The three branches focus on: libraries, information, and science, respectively. In addition, our study identifies substructures within each branch. We also tentatively identify "information seeking behavior" as a branch that is establishing itself separate from the three main branches. Furthermore, we find that cognitive concepts in LIS evolve continuously, with no stasis since 1992. The most rapid development occurred between 1998 and 2001, influenced by the increased focus on the Internet. The change in the cognitive landscape is found to be driven by the emergence of new information technologies, and the retirement of old ones.
Wissenschaftsfach: Bibliothekswesen ; Informationswissenschaft
14Yan, E. ; Sugimoto, C.R.: Institutional interactions : exploring social, cognitive, and geographic relationships between institutions as demonstrated through citation networks.
In: Journal of the American Society for Information Science and Technology. 62(2011) no.8, S.1498-1514.
Abstract: The objective of this research is to examine the interaction of institutions, based on their citation and collaboration networks. The domain of library and information science is examined, using data from 1965-2010. A linear model is formulated to explore the factors that are associated with institutional citation behaviors, using the number of citations as the dependent variable, and the number of collaborations, physical distance, and topical distance as independent variables. It is found that institutional citation behaviors are associated with social, topical, and geographical factors. Dynamically, the number of citations is becoming more associated with collaboration intensity and less dependent on the country boundary and/or physical distance. This research is informative for scientometricians and policy makers.
15Li, D. ; Ding, Y. ; Sugimoto, C. ; He, B. ; Tang, J. ; Yan, E. ; Lin, N. ; Qin, Z. ; Dong, T.: Modeling topic and community structure in social tagging : the TTR-LDA-Community model.
In: Journal of the American Society for Information Science and Technology. 62(2011) no.9, S.1849-1866.
Abstract: The presence of social networks in complex systems has made networks and community structure a focal point of study in many domains. Previous studies have focused on the structural emergence and growth of communities and on the topics displayed within the network. However, few scholars have closely examined the relationship between the thematic and structural properties of networks. Therefore, this article proposes the Tagger Tag Resource-Latent Dirichlet Allocation-Community model (TTR-LDA-Community model), which combines the Latent Dirichlet Allocation (LDA) model with the Girvan-Newman community detection algorithm through an inference mechanism. Using social tagging data from Delicious, this article demonstrates the clustering of active taggers into communities, the topic distributions within communities, and the ranking of taggers, tags, and resources within these communities. The data analysis evaluates patterns in community structure and topical affiliations diachronically. The article evaluates the effectiveness of community detection and the inference mechanism embedded in the model and finds that the TTR-LDA-Community model outperforms other traditional models in tag prediction. This has implications for scholars in domains interested in community detection, profiling, and recommender systems.
Themenfeld: Social tagging
16Yan, E. ; Ding, Y.: Discovering author impact : a PageRank perspective.
In: Information processing and management. 47(2011) no.1, S.125-134.
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.
17Ding, Y. ; Jacob, E.K. ; Fried, M. ; Toma, I. ; Yan, E. ; Foo, S. ; Milojevicacute, S.: Upper tag ontology for integrating social tagging data.
In: Journal of the American Society for Information Science and Technology. 61(2010) no.3, S.505-521.
Abstract: Data integration and mediation have become central concerns of information technology over the past few decades. With the advent of the Web and the rapid increases in the amount of data and the number of Web documents and users, researchers have focused on enhancing the interoperability of data through the development of metadata schemes. Other researchers have looked to the wealth of metadata generated by bookmarking sites on the Social Web. While several existing ontologies have capitalized on the semantics of metadata created by tagging activities, the Upper Tag Ontology (UTO) emphasizes the structure of tagging activities to facilitate modeling of tagging data and the integration of data from different bookmarking sites as well as the alignment of tagging ontologies. UTO is described and its utility in modeling, harvesting, integrating, searching, and analyzing data is demonstrated with metadata harvested from three major social tagging systems (Delicious, Flickr, and YouTube).
Themenfeld: Social tagging
18Yan, E. ; Ding, Y.: Weighted citation : an indicator of an article's prestige.
In: Journal of the American Society for Information Science and Technology. 61(2010) no.8, S.1635-1643.
Abstract: The authors propose using the technique of weighted citation to measure an article's prestige. The technique allocates a different weight to each reference by taking into account the impact of citing journals and citation time intervals. Weightedcitation captures prestige, whereas citation counts capture popularity. They compare the value variances for popularity and prestige for articles published in the Journal of the American Society for Information Science and Technology from 1998 to 2007, and find that the majority have comparable status.
19Yan, E. ; Ding, Y.: Applying centrality measures to impact analysis : a coauthorship network analysis.
In: Journal of the American Society for Information Science and Technology. 60(2009) no.10, S.2107-2118.
Abstract: Many studies on coauthorship networks focus on network topology and network statistical mechanics. This article takes a different approach by studying micro-level network properties with the aim of applying centrality measures to impact analysis. Using coauthorship data from 16 journals in the field of library and information science (LIS) with a time span of 20 years (1988-2007), we construct an evolving coauthorship network and calculate four centrality measures (closeness centrality, betweenness centrality, degree centrality, and PageRank) for authors in this network. We find that the four centrality measures are significantly correlated with citation counts. We also discuss the usability of centrality measures in author ranking and suggest that centrality measures can be useful indicators for impact analysis.
20Ding, Y. ; Yan, E. ; Frazho, A. ; Caverlee, J.: PageRank for ranking authors in co-citation networks.
In: Journal of the American Society for Information Science and Technology. 60(2009) no.11, S.2229-2243.
Abstract: This paper studies how varied damping factors in the PageRank algorithm influence the ranking of authors and proposes weighted PageRank algorithms. We selected the 108 most highly cited authors in the information retrieval (IR) area from the 1970s to 2008 to form the author co-citation network. We calculated the ranks of these 108 authors based on PageRank with the damping factor ranging from 0.05 to 0.95. In order to test the relationship between different measures, we compared PageRank and weighted PageRank results with the citation ranking, h-index, and centrality measures. We found that in our author co-citation network, citation rank is highly correlated with PageRank with different damping factors and also with different weighted PageRank algorithms; citation rank and PageRank are not significantly correlated with centrality measures; and h-index rank does not significantly correlate with centrality measures but does significantly correlate with other measures. The key factors that have impact on the PageRank of authors in the author co-citation network are being co-cited with important authors.
Themenfeld: Suchmaschinen ; Retrievalalgorithmen ; Informetrie