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  1. Chang, Y.-W.; Huang, M.-H.: ¬A study of the evolution of interdisciplinarity in library and information science : using three bibliometric methods (2012) 0.13 
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    Abstract
    This study uses three bibliometric methods: direct citation, bibliographic coupling, and co-authorship analysis, to investigate interdisciplinary changes in library and information science (LIS) from 1978 to 2007. The results reveal that LIS researchers most frequently cite publications in their own discipline. In addition, half of all co-authors of LIS articles are affiliated with LIS-related institutes. The results confirm that the degree of interdisciplinarity within LIS has increased, particularly co-authorship. However, the study found sources of direct citations in LIS articles are widely distributed across 30 disciplines, but co-authors of LIS articles are distributed across only 25 disciplines. The degree of interdisciplinarity was found ranging from 0.61 to 0.82 with citation to references in all articles being the highest and that of co-authorship being the lowest. Percentages of contribution attributable to LIS show a decreasing tendency based on the results of direct citation and co-authorship analysis, but an increasing tendency based on those of bibliographic coupling analysis. Such differences indicate each of the three bibliometric methods has its strength and provides insights respectively for viewing various aspects of interdisciplinarity, suggesting the use of no single bibliometric method can reveal all aspects of interdisciplinarity due to its multifaceted nature.
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.1, S.22-33
  2. Wu, K.-C.; Hsieh, T.-Y.: Affective choosing of clustering and categorization representations in e-book interfaces (2016) 0.12 
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    Abstract
    Purpose - The purpose of this paper is to investigate user experiences with a touch-wall interface featuring both clustering and categorization representations of available e-books in a public library to understand human information interactions under work-focused and recreational contexts. Design/methodology/approach - Researchers collected questionnaires from 251 New Taipei City Library visitors who used the touch-wall interface to search for new titles. The authors applied structural equation modelling to examine relationships among hedonic/utilitarian needs, clustering and categorization representations, perceived ease of use (EU) and the extent to which users experienced anxiety and uncertainty (AU) while interacting with the interface. Findings - Utilitarian users who have an explicit idea of what they intend to find tend to prefer the categorization interface. A hedonic-oriented user tends to prefer clustering interfaces. Users reported EU regardless of which interface they engaged with. Results revealed that use of the clustering interface had a negative correlation with AU. Users that seek to satisfy utilitarian needs tended to emphasize the importance of perceived EU, whilst pleasure-seeking users were a little more tolerant of anxiety or uncertainty. Originality/value - The Online Public Access Catalogue (OPAC) encourages library visitors to borrow digital books through the implementation of an information visualization system. This situation poses an opportunity to validate uses and gratification theory. People with hedonic/utilitarian needs displayed different risk-control attitudes and affected uncertainty using the interface. Knowledge about user interaction with such interfaces is vital when launching the development of a new OPAC.
    Date
    20. 1.2015 18:30:22
  3. Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019) 0.10 
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    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  4. HaCohen-Kerner, Y. et al.: Classification using various machine learning methods and combinations of key-phrases and visual features (2016) 0.10 
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    Date
    1. 2.2016 18:25:22
  5. Zhou, Y. et al.: Analysing entity context in multilingual Wikipedia to support entity-centric retrieval applications (2016) 0.10 
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    Date
    1. 2.2016 18:25:22
  6. Zhang, C.; Bu, Y.; Ding, Y.; Xu, J.: Understanding scientific collaboration : homophily, transitivity, and preferential attachment (2018) 0.08 
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    Abstract
    Scientific collaboration is essential in solving problems and breeding innovation. Coauthor network analysis has been utilized to study scholars' collaborations for a long time, but these studies have not simultaneously taken different collaboration features into consideration. In this paper, we present a systematic approach to analyze the differences in possibilities that two authors will cooperate as seen from the effects of homophily, transitivity, and preferential attachment. Exponential random graph models (ERGMs) are applied in this research. We find that different types of publications one author has written play diverse roles in his/her collaborations. An author's tendency to form new collaborations with her/his coauthors' collaborators is strong, where the more coauthors one author had before, the more new collaborators he/she will attract. We demonstrate that considering the authors' attributes and homophily effects as well as the transitivity and preferential attachment effects of the coauthorship network in which they are embedded helps us gain a comprehensive understanding of scientific collaboration.
  7. Plochberger, F.: Neues Paradigma in der Informationswissenschaft : wissenschaftlicher Ansatz, um die Informationstechnologie für den Menschen erfreulicher zu gestalten (2011) 0.08 
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    Source
    http://www.plbg.at/Werke/deutsch/Neues%20Paradigma%20in%20der%20IW%20(Ausgabe2).pdf
  8. Bu, Y.; Ding, Y.; Xu, J.; Liang, X.; Gao, G.; Zhao, Y.: Understanding success through the diversity of collaborators and the milestone of career (2018) 0.08 
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    Abstract
    Scientific collaboration is vital to many fields, and it is common to see scholars seek out experienced researchers or experts in a domain with whom they can share knowledge, experience, and resources. To explore the diversity of research collaborations, this article performs a temporal analysis on the scientific careers of researchers in the field of computer science. Specifically, we analyze collaborators using 2 indicators: the research topic diversity, measured by the Author-Conference-Topic model and cosine, and the impact diversity, measured by the normalized standard deviation of h-indices. We find that the collaborators of high-impact researchers tend to study diverse research topics and have diverse h-indices. Moreover, by setting PhD graduation as an important milestone in researchers' careers, we examine several indicators related to scientific collaboration and their effects on a career. The results show that collaborating with authoritative authors plays an important role prior to a researcher's PhD graduation, but working with non-authoritative authors carries more weight after PhD graduation.
  9. Yan, E.; Ding, Y.: Weighted citation : an indicator of an article's prestige (2010) 0.08 
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    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.
  10. Onodera, N.; Iwasawa, M.; Midorikawa, N.; Yoshikane, F.; Amano, K.; Ootani, Y.; Kodama, T.; Kiyama, Y.; Tsunoda, H.; Yamazaki, S.: ¬A method for eliminating articles by homonymous authors from the large number of articles retrieved by author search (2011) 0.08 
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    Abstract
    This paper proposes a methodology which discriminates the articles by the target authors ("true" articles) from those by other homonymous authors ("false" articles). Author name searches for 2,595 "source" authors in six subject fields retrieved about 629,000 articles. In order to extract true articles from the large amount of the retrieved articles, including many false ones, two filtering stages were applied. At the first stage any retrieved article was eliminated as false if either its affiliation addresses had little similarity to those of its source article or there was no citation relationship between the journal of the retrieved article and that of its source article. At the second stage, a sample of retrieved articles was subjected to manual judgment, and utilizing the judgment results, discrimination functions based on logistic regression were defined. These discrimination functions demonstrated both the recall ratio and the precision of about 95% and the accuracy (correct answer ratio) of 90-95%. Existence of common coauthor(s), address similarity, title words similarity, and interjournal citation relationships between the retrieved and source articles were found to be the effective discrimination predictors. Whether or not the source author was from a specific country was also one of the important predictors. Furthermore, it was shown that a retrieved article is almost certainly true if it was cited by, or cocited with, its source article. The method proposed in this study would be effective when dealing with a large number of articles whose subject fields and affiliation addresses vary widely.
  11. Lu, C.; Bu, Y.; Wang, J.; Ding, Y.; Torvik, V.; Schnaars, M.; Zhang, C.: Examining scientific writing styles from the perspective of linguistic complexity : a cross-level moderation model (2019) 0.08 
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    Abstract
    Publishing articles in high-impact English journals is difficult for scholars around the world, especially for non-native English-speaking scholars (NNESs), most of whom struggle with proficiency in English. To uncover the differences in English scientific writing between native English-speaking scholars (NESs) and NNESs, we collected a large-scale data set containing more than 150,000 full-text articles published in PLoS between 2006 and 2015. We divided these articles into three groups according to the ethnic backgrounds of the first and corresponding authors, obtained by Ethnea, and examined the scientific writing styles in English from a two-fold perspective of linguistic complexity: (a) syntactic complexity, including measurements of sentence length and sentence complexity; and (b) lexical complexity, including measurements of lexical diversity, lexical density, and lexical sophistication. The observations suggest marginal differences between groups in syntactical and lexical complexity.
  12. Ding, Y.: Applying weighted PageRank to author citation networks (2011) 0.07 
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    Date
    22. 1.2011 13:02:21
  13. Ding, Y.: Topic-based PageRank on author cocitation networks (2011) 0.07 
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    Abstract
    Ranking authors is vital for identifying a researcher's impact and standing within a scientific field. There are many different ranking methods (e.g., citations, publications, h-index, PageRank, and weighted PageRank), but most of them are topic-independent. This paper proposes topic-dependent ranks based on the combination of a topic model and a weighted PageRank algorithm. The author-conference-topic (ACT) model was used to extract topic distribution of individual authors. Two ways for combining the ACT model with the PageRank algorithm are proposed: simple combination (I_PR) or using a topic distribution as a weighted vector for PageRank (PR_t). Information retrieval was chosen as the test field and representative authors for different topics at different time phases were identified. Principal component analysis (PCA) was applied to analyze the ranking difference between I_PR and PR_t.
  14. Stover, J.A.; Winter, Y.; Koppel, M.; Kestemont, M.: Computational authorship verification method attributes a new work to a major 2nd century African author (2016) 0.07 
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    Abstract
    We discuss a real-world application of a recently proposed machine learning method for authorship verification. Authorship verification is considered an extremely difficult task in computational text classification, because it does not assume that the correct author of an anonymous text is included in the candidate authors available. To determine whether 2 documents have been written by the same author, the verification method discussed uses repeated feature subsampling and a pool of impostor authors. We use this technique to attribute a newly discovered Latin text from antiquity (the Compendiosa expositio) to Apuleius. This North African writer was one of the most important authors of the Roman Empire in the 2nd century and authored one of the world's first novels. This attribution has profound and wide-reaching cultural value, because it has been over a century since a new text by a major author from antiquity was discovered. This research therefore illustrates the rapidly growing potential of computational methods for studying the global textual heritage.
  15. An, J.; Kim, N.; Kan, M.-Y.; Kumar Chandrasekaran, M.; Song, M.: Exploring characteristics of highly cited authors according to citation location and content (2017) 0.07 
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    Abstract
    Big Science and cross-disciplinary collaborations have reshaped the intellectual structure of research areas. A number of works have tried to uncover this hidden intellectual structure by analyzing citation contexts. However, none of them analyzed by document logical structures such as sections. The two major goals of this study are to find characteristics of authors who are highly cited section-wise and to identify the differences in section-wise author networks. This study uses 29,158 of research articles culled from the ACL Anthology, which hosts articles on computational linguistics and natural language processing. We find that the distribution of citations across sections is skewed and that a different set of highly cited authors share distinct academic characteristics, according to their citation locations. Furthermore, the author networks based on citation context similarity reveal that the intellectual structure of a domain differs across different sections.
  16. Wu, H.; He, J.; Pei, Y.: Scientific impact at the topic level : a case study in computational linguistics (2010) 0.07 
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    Abstract
    In this article, we propose to apply the topic model and topic-level eigenfactor (TEF) algorithm to assess the relative importance of academic entities including articles, authors, journals, and conferences. Scientific impact is measured by the biased PageRank score toward topics created by the latent topic model. The TEF metric considers the impact of an academic entity in multiple granular views as well as in a global view. Experiments on a computational linguistics corpus show that the method is a useful and promising measure to assess scientific impact.
  17. Yan, E.; Ding, Y.; Sugimoto, C.R.: P-Rank: an indicator measuring prestige in heterogeneous scholarly networks (2011) 0.07 
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    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.
  18. 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) 0.07 
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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.
  19. Song, M.; Kim, S.Y.; Zhang, G.; Ding, Y.; Chambers, T.: Productivity and influence in bioinformatics : a bibliometric analysis using PubMed central (2014) 0.07 
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    Abstract
    Bioinformatics is a fast-growing field based on the optimal use of "big data" gathered in genomic, proteomics, and functional genomics research. In this paper, we conduct a comprehensive and in-depth bibliometric analysis of the field of bioinformatics by extracting citation data from PubMed Central full-text. Citation data for the period 2000 to 2011, comprising 20,869 papers with 546,245 citations, was used to evaluate the productivity and influence of this emerging field. Four measures were used to identify productivity; most productive authors, most productive countries, most productive organizations, and most popular subject terms. Research impact was analyzed based on the measures of most cited papers, most cited authors, emerging stars, and leading organizations. Results show the overall trends between the periods 2000 to 2003 and 2004 to 2007 were dissimilar, while trends between the periods 2004 to 2007 and 2008 to 2011 were similar. In addition, the field of bioinformatics has undergone a significant shift, co-evolving with other biomedical disciplines.
  20. Liu, Y.; Rousseau, R.: Interestingness and the essence of citation : Thomas Reid and bibliographic description (2013) 0.07 
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    Abstract
    Purpose - This paper aims to provide a new insight into the reasons why authors cite. Design/methodology/approach The authors argue that, based on philosophical ideas about the essence of things, pure rational thinking about the role of citations leads to the answer. Findings - Citations originate from the interestingness of the investigated phenomenon. The essence of citation lies in the interaction between different ideas or perspectives on a phenomenon addressed in the citing as well as in the cited articles. Research limitations/implications - The findings only apply to ethical (not whimsical or self-serving) citations. As such citations reflect interactions of scientific ideas, they can reveal the evolution of science, revive the cognitive process of an investigated scientific phenomenon and reveal political and economic factors influencing the development of science. Originality/value - This article is the first to propose interestingness and the interaction of ideas as the basic reason for citing. This view on citations allows reverse engineering from citations to ideas and hence becomes useful for science policy.

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