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: 23. Dezember 2017)
1Zhang, C. ; Bu, Y. ; Ding, Y. ; Xu, J.: Understanding scientific collaboration : homophily, transitivity, and preferential attachment.
In: Journal of the Association for Information Science and Technology. 69(2018) no.1, S.72-86.
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.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23916/full.
2Hu, 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.
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3Wang, X. ; Hong, Z. ; Xu, Y.(C.) ; Zhang, C. ; Ling, H.: Relevance judgments of mobile commercial information.
In: Journal of the Association for Information Science and Technology. 65(2014) no.7, S.1335-1348.
Abstract: In the age of mobile commerce, users receive floods of commercial messages. How do users judge the relevance of such information? Is their relevance judgment affected by contextual factors, such as location and time? How do message content and contextual factors affect users' privacy concerns? With a focus on mobile ads, we propose a research model based on theories of relevance judgment and mobile marketing research. We suggest topicality, reliability, and economic value as key content factors and location and time as key contextual factors. We found mobile relevance judgment is affected mainly by content factors, whereas privacy concerns are affected by both content and contextual factors. Moreover, topicality and economic value have a synergetic effect that makes a message more relevant. Higher topicality and location precision exacerbate privacy concerns, whereas message reliability alleviates privacy concerns caused by location precision. These findings reveal an interesting intricacy in user relevance judgment and privacy concerns and provide nuanced guidance for the design and delivery of mobile commercial information.
4Zhang, C. ; Liu, X. ; Xu, Y.(C.) ; Wang, Y.: Quality-structure index : a new metric to measure scientific journal influence.
In: Journal of the American Society for Information Science and Technology. 62(2011) no.4, S.643-653.
Abstract: An innovative model to measure the influence among scientific journals is developed in this study. This model is based on the path analysis of a journal citation network, and its output is a journal influence matrix that describes the directed influence among all journals. Based on this model, an index of journals' overall influence, the quality-structure index (QSI), is derived. Journal ranking based on QSI has the advantage of accounting for both intrinsic journal quality and the structural position of a journal in a citation network. The QSI also integrates the characteristics of two prevailing streams of journal-assessment measures: those based on bibliometric statistics to approximate intrinsic journal quality, such as the Journal Impact Factor, and those using a journal's structural position based on the PageRank-type of algorithm, such as the Eigenfactor score. Empirical results support our finding that the new index is significantly closer to scholars' subjective perception of journal influence than are the two aforementioned measures. In addition, the journal influence matrix offers a new way to measure two-way influences between any two academic journals, hence establishing a theoretical basis for future scientometrics studies to investigate the knowledge flow within and across research disciplines.
5Zhang, C.-T.: Relationship of the h-index, g-index, and e-index.
In: Journal of the American Society for Information Science and Technology. 61(2010) no.3, S.625-628.
Abstract: Of h-type indices available now, the g-index is an important one in that it not only keeps some advantages of the h-index but also counts citations from highly cited articles. However, the g-index has a drawback that one has to add fictitious articles with zero citation to calculate this index in some important cases. Based on an alternative definition without introducing fictitious articles, an analytical method has been proposed to calculate the g-index based approximately on the h-index and the e-index. If citations for a scientist are ranked by a power law, it is shown that the g-index can be calculated accurately by the h-index, the e-index, and the power parameter. The relationship of the h-, g-, and e-indices presented here shows that the g-index contains the citation information from the h-index, the e-index, and some papers beyond the h-core.
Objekt: h-index ; g-index ; e-index
6Zhang, C. ; Zeng, D. ; Li, J. ; Wang, F.-Y. ; Zuo, W.: Sentiment analysis of Chinese documents : from sentence to document level.
In: Journal of the American Society for Information Science and Technology. 60(2009) no.12, S.2474-2487.
Abstract: User-generated content on the Web has become an extremely valuable source for mining and analyzing user opinions on any topic. Recent years have seen an increasing body of work investigating methods to recognize favorable and unfavorable sentiments toward specific subjects from online text. However, most of these efforts focus on English and there have been very few studies on sentiment analysis of Chinese content. This paper aims to address the unique challenges posed by Chinese sentiment analysis. We propose a rule-based approach including two phases: (1) determining each sentence's sentiment based on word dependency, and (2) aggregating sentences to predict the document sentiment. We report the results of an experimental study comparing our approach with three machine learning-based approaches using two sets of Chinese articles. These results illustrate the effectiveness of our proposed method and its advantages against learning-based approaches.