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  • × author_ss:"Zhang, J."
  1. Zhang, J.; Wolfram, D.; Wang, P.; Hong, Y.; Gillis, R.: Visualization of health-subject analysis based on query term co-occurrences (2008) 0.00 
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    Abstract
    A multidimensional-scaling approach is used to analyze frequently used medical-topic terms in queries submitted to a Web-based consumer health information system. Based on a year-long transaction log file, five medical focus keywords (stomach, hip, stroke, depression, and cholesterol) and their co-occurring query terms are analyzed. An overlap-coefficient similarity measure and a conversion measure are used to calculate the proximity of terms to one another based on their co-occurrences in queries. The impact of the dimensionality of the visual configuration, the cutoff point of term co-occurrence for inclusion in the analysis, and the Minkowski metric power k on the stress value are discussed. A visual clustering of groups of terms based on the proximity within each focus-keyword group is also conducted. Term distributions within each visual configuration are characterized and are compared with formal medical vocabulary. This investigation reveals that there are significant differences between consumer health query-term usage and more formal medical terminology used by medical professionals when describing the same medical subject. Future directions are discussed.
    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.12, S.1933-1947
  2. Zhang, J.: Archival context, digital content, and the ethics of digital archival representation : the ethics of identification in digital library metadata (2012) 0.00 
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    Content
    Beitrag aus einem Themenheft zu den Proceedings of the 2nd Milwaukee Conference on Ethics in Information Organization, June 15-16, 2012, School of Information Studies, University of Wisconsin-Milwaukee. Hope A. Olson, Conference Chair. Vgl.: http://www.ergon-verlag.de/isko_ko/downloads/ko_39_2012_5_d.pdf.
  3. Liu, X.; Zhang, J.; Guo, C.: Full-text citation analysis : a new method to enhance scholarly networks (2013) 0.00 
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    Abstract
    In this article, we use innovative full-text citation analysis along with supervised topic modeling and network-analysis algorithms to enhance classical bibliometric analysis and publication/author/venue ranking. By utilizing citation contexts extracted from a large number of full-text publications, each citation or publication is represented by a probability distribution over a set of predefined topics, where each topic is labeled by an author-contributed keyword. We then used publication/citation topic distribution to generate a citation graph with vertex prior and edge transitioning probability distributions. The publication importance score for each given topic is calculated by PageRank with edge and vertex prior distributions. To evaluate this work, we sampled 104 topics (labeled with keywords) in review papers. The cited publications of each review paper are assumed to be "important publications" for the target topic (keyword), and we use these cited publications to validate our topic-ranking result and to compare different publication-ranking lists. Evaluation results show that full-text citation and publication content prior topic distribution, along with the classical PageRank algorithm can significantly enhance bibliometric analysis and scientific publication ranking performance, comparing with term frequency-inverted document frequency (tf-idf), language model, BM25, PageRank, and PageRank + language model (p < .001), for academic information retrieval (IR) systems.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.9, S.1852-1863
  4. Li, D.; Tang, J.; Ding, Y.; Shuai, X.; Chambers, T.; Sun, G.; Luo, Z.; Zhang, J.: Topic-level opinion influence model (TOIM) : an investigation using tencent microblogging (2015) 0.00 
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    Abstract
    Text mining has been widely used in multiple types of user-generated data to infer user opinion, but its application to microblogging is difficult because text messages are short and noisy, providing limited information about user opinion. Given that microblogging users communicate with each other to form a social network, we hypothesize that user opinion is influenced by its neighbors in the network. In this paper, we infer user opinion on a topic by combining two factors: the user's historical opinion about relevant topics and opinion influence from his/her neighbors. We thus build a topic-level opinion influence model (TOIM) by integrating both topic factor and opinion influence factor into a unified probabilistic model. We evaluate our model in one of the largest microblogging sites in China, Tencent Weibo, and the experiments show that TOIM outperforms baseline methods in opinion inference accuracy. Moreover, incorporating indirect influence further improves inference recall and f1-measure. Finally, we demonstrate some useful applications of TOIM in analyzing users' behaviors in Tencent Weibo.
    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2657-2673
  5. Zhang, J.; Zhao, Y.: ¬A user term visualization analysis based on a social question and answer log (2013) 0.00 
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    Abstract
    The authors of this paper investigate terms of consumers' diabetes based on a log from the Yahoo!Answers social question and answers (Q&A) forum, ascertain characteristics and relationships among terms related to diabetes from the consumers' perspective, and reveal users' diabetes information seeking patterns. In this study, the log analysis method, data coding method, and visualization multiple-dimensional scaling analysis method were used for analysis. The visual analyses were conducted at two levels: terms analysis within a category and category analysis among the categories in the schema. The findings show that the average number of words per question was 128.63, the average number of sentences per question was 8.23, the average number of words per response was 254.83, and the average number of sentences per response was 16.01. There were 12 categories (Cause & Pathophysiology, Sign & Symptom, Diagnosis & Test, Organ & Body Part, Complication & Related Disease, Medication, Treatment, Education & Info Resource, Affect, Social & Culture, Lifestyle, and Nutrient) in the diabetes related schema which emerged from the data coding analysis. The analyses at the two levels show that terms and categories were clustered and patterns were revealed. Future research directions are also included.
    Source
    Information processing and management. 49(2013) no.5, S.1019-1048
  6. Zhang, J.; Chen, Y.; Zhao, Y.; Wolfram, D.; Ma, F.: Public health and social media : a study of Zika virus-related posts on Yahoo! Answers (2020) 0.00 
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    Abstract
    This study investigates the content of questions and responses about the Zika virus on Yahoo! Answers as a recent example of how public concerns regarding an international health issue are reflected in social media. We investigate the contents of posts about the Zika virus on Yahoo! Answers, identify and reveal subject patterns about the Zika virus, and analyze the temporal changes of the revealed subject topics over 4 defined periods of the Zika virus outbreak. Multidimensional scaling analysis, temporal analysis, and inferential statistical analysis approaches were used in the study. A resulting 2-layer Zika virus schema, and term connections and relationships are presented. The results indicate that consumers' concerns changed over the 4 defined periods. Consumers paid more attention to the basic information about the Zika virus, and the prevention and protection from the Zika virus at the beginning of the outbreak of the Zika virus. During the later periods, consumers became more interested in the role that the government and health organizations played in the public health emergency.
    Source
    Journal of the Association for Information Science and Technology. 71(2020) no.3, S.282-299
  7. Geng, Q.; Townley, C.; Huang, K.; Zhang, J.: Comparative knowledge management : a pilot study of Chinese and American universities (2005) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.10, S.1031-1044
  8. Zhang, J.; Dimitroff, A.: ¬The impact of metadata implementation on webpage visibility in search engine results : part II (2005) 0.00 
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    Source
    Information processing and management. 41(2005) no.3, S.691-716
  9. Zhang, J.; Dimitroff, A.: ¬The impact of metadata implementation on webpage visibility in search engine results : part II (2005) 0.00 
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    Source
    Information processing and management. 41(2005) no.3, S.691-715
  10. Hansen, D.L.; Khopkar, T.; Zhang, J.: Recommender systems and expert locators (2009) 0.00 
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    Source
    Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates
  11. Zhang, J.; Yu, Q.; Zheng, F.; Long, C.; Lu, Z.; Duan, Z.: Comparing keywords plus of WOS and author keywords : a case study of patient adherence research (2016) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.4, S.967-972
  12. Zhang, J.; Wolfram, D.: Visualization of term discrimination analysis (2001) 0.00 
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    Source
    Journal of the American Society for Information Science and technology. 52(2001) no.8, S.615-627
  13. Wolfram, D.; Zhang, J.: ¬An investigation of the influence of indexing exhaustivity and term distributions on a document space (2002) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 53(2002) no.11, S.944-952
  14. Zhang, J.; Zhai, S.; Stevenson, J.A.; Xia, L.: Optimization of the subject directory in a government agriculture department web portal (2016) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.9, S.2166-2180

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