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Chen, X.: Indexing consistency between online catalogues (2008) 0.01
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Abstract

In der globalen Online-Umgebung stellen viele bibliographische Dienstleistungen integrierten Zugang zu unterschiedlichen internetbasierten OPACs zur Verfügung. In solch einer Umgebung erwarten Benutzer mehr Übereinstimmungen innerhalb und zwischen den Systemen zu sehen. Zweck dieser Studie ist, die Indexierungskonsistenz zwischen Systemen zu untersuchen. Währenddessen werden einige Faktoren, die die Indexierungskonsistenz beeinflussen können, untersucht. Wichtigstes Ziel dieser Studie ist, die Gründe für die Inkonsistenzen herauszufinden, damit sinnvolle Vorschläge gemacht werden können, um die Indexierungskonsistenz zu verbessern. Eine Auswahl von 3307 Monographien wurde aus zwei chinesischen bibliographischen Katalogen gewählt. Nach Hooper's Formel war die durchschnittliche Indexierungskonsistenz für Indexterme 64,2% und für Klassennummern 61,6%. Nach Rolling's Formel war sie für Indexterme 70,7% und für Klassennummern 63,4%. Mehrere Faktoren, die die Indexierungskonsistenz beeinflussen, wurden untersucht: (1) Indexierungsbereite; (2) Indexierungsspezifizität; (3) Länge der Monographien; (4) Kategorie der Indexierungssprache; (5) Sachgebiet der Monographien; (6) Entwicklung von Disziplinen; (7) Struktur des Thesaurus oder der Klassifikation; (8) Erscheinungsjahr. Gründe für die Inkonsistenzen wurden ebenfalls analysiert. Die Analyse ergab: (1) den Indexieren mangelt es an Fachwissen, Vertrautheit mit den Indexierungssprachen und den Indexierungsregeln, so dass viele Inkonsistenzen verursacht wurden; (2) der Mangel an vereinheitlichten oder präzisen Regeln brachte ebenfalls Inkonsistenzen hervor; (3) verzögerte Überarbeitungen der Indexierungssprachen, Mangel an terminologischer Kontrolle, zu wenige Erläuterungen und "siehe auch" Referenzen, sowie die hohe semantische Freiheit bei der Auswahl von Deskriptoren oder Klassen, verursachten Inkonsistenzen.

Imprint

Berlin : Humboldt-Universität / Institut für Bibliotheks- und Informationswissenschaft

Wu, Y.-f.B.; Li, Q.; Bot, R.S.; Chen, X.: Finding nuggets in documents : a machine learning approach (2006) 0.00

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Date: 22. 7.2006 17:25:48
Source: Journal of the American Society for Information Science and Technology. 57(2006) no.6, S.740-752

Zhou, H.; Xiao, L.; Liu, Y.; Chen, X.: ¬The effect of prediscussion note-taking in hidden profile tasks (2018) 0.00
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Abstract

Prior research has discovered that groups tend to discuss shared information while failing to discuss unique information in decision-making processes. In our study, we conducted a lab experiment to examine the effect of prediscussion note-taking on this phenomenon. The experiment used a murder-mystery hidden profile task. In all, 192 undergraduate students were recruited and randomly assigned into 48 four-person groups with gender being the matching variable (i.e., each group consisted of four same-gender participants). During the decision-making processes, some groups were asked to take notes while reading task materials and had their notes available in the following group discussion, while the other groups were not given this opportunity. Our analysis results suggest that (a) the presence of an information piece in group members' notes positively correlates with its appearance in the subsequent discussion and note-taking positively affects the group's information repetition rate; (b) group decision quality positively correlates with the group's information sampling rate and negatively correlates with the group's information sampling/repetition bias; and (c) gender has no statistically significant moderating effect on the relationship between note-taking and information sharing. These results imply that prediscussion note-taking could facilitate information sharing but could not alleviate the biased information pooling in hidden profile tasks.

Source

Journal of the Association for Information Science and Technology. 69(2018) no.4, S.566-577

Chen, X.: Fair use of electronic sources in libraries (1996) 0.00

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Imprint: Medford, NJ : Information Today

Xu, C.; Ma, B.; Chen, X.; Ma, F.: Social tagging in the scholarly world (2013) 0.00
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Abstract

The number of research studies on social tagging has increased rapidly in the past years, but few of them highlight the characteristics and research trends in social tagging. A set of 862 academic documents relating to social tagging and published from 2005 to 2011 was thus examined using bibliometric analysis as well as the social network analysis technique. The results show that social tagging, as a research area, develops rapidly and attracts an increasing number of new entrants. There are no key authors, publication sources, or research groups that dominate the research domain of social tagging. Research on social tagging appears to focus mainly on the following three aspects: (a) components and functions of social tagging (e.g., tags, tagging objects, and tagging network), (b) taggers' behaviors and interface design, and (c) tags' organization and usage in social tagging. The trend suggest that more researchers turn to the latter two integrated with human computer interface and information retrieval, although the first aspect is the fundamental one in social tagging. Also, more studies relating to social tagging pay attention to multimedia tagging objects and not only text tagging. Previous research on social tagging was limited to a few subject domains such as information science and computer science. As an interdisciplinary research area, social tagging is anticipated to attract more researchers from different disciplines. More practical applications, especially in high-tech companies, is an encouraging research trend in social tagging.

Source

Journal of the American Society for Information Science and Technology. 64(2013) no.10, S.2045-2057

Liu, X.; Chen, X.: Authors' noninstitutional emails and their correlation with retraction (2021) 0.00

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Source: Journal of the Association for Information Science and Technology. 72(2021) no.4, S.449-4473-477

Bose, I.; Chen, X.: ¬A method for extension of generative topographic mapping for fuzzy clustering (2009) 0.00

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Source: Journal of the American Society for Information Science and Technology. 60(2009) no.2, S.363-371

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