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http://dx.doi.org/10.1633/JISTaP.2022.10.1.6

Utilization of Log Data Reflecting User Information-Seeking Behavior in the Digital Library  

Lee, Seonhee (Korea Institute of Science and Technology Information)
Lee, Jee Yeon (Department of Library and Information Science, Yonsei University)
Publication Information
Journal of Information Science Theory and Practice / v.10, no.1, 2022 , pp. 73-88 More about this Journal
Abstract
This exploratory study aims to understand the potential of log data analysis and expand its utilization in user research methods. Transaction log data are records of electronic interactions that have occurred between users and web services, reflecting information-seeking behavior in the context of digital libraries where users interact with the service system during the search for information. Two ways were used to analyze South Korea's National Digital Science Library (NDSL) log data for three days, including 150,000 data: a log pattern analysis, and log context analysis using statistics. First, a pattern-based analysis examined the general paths of usage by logged and unlogged users. The correlation between paths was analyzed through a χ2 analysis. The subsequent log context analysis assessed 30 identified users' data using basic statistics and visualized the individual user information-seeking behavior while accessing NDSL. The visualization shows included 30 diverse paths for 30 cases. Log analysis provided insight into general and individual user information-seeking behavior. The results of log analysis can enhance the understanding of user actions. Therefore, it can be utilized as the basic data to improve the design of services and systems in the digital library to meet users' needs.
Keywords
log data; information-seeking behavior; log pattern analysis; log context analysis; digital library; South Korea;
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Times Cited By KSCI : 6  (Citation Analysis)
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1 Penniman, W. D., & Dominick, W. D. (1980). Monitoring and evaluation of on-line information system usage. Information Processing & Management, 16(1), 17-35. https://doi.org/10.1016/0306-4573(80)90003-5.   DOI
2 Koch, T., Ardo, A., & Golub, K. (2004, June 7-11). Browsing and searching behavior in the Renardus web service: A study based on log analysis. Paper presented at the 4th ACM/IEEE-CS Joint Conference on Digital Libraries, Tuscon, AZ, USA.
3 Kim, G. Y., Kwon, N. H., Yu, S. Y., & Choi, Y. (2013). An analysis of NDSL use statistics and its application for developing virtuous circle of NDSL information services. https://scienceon.kisti.re.kr/commons/util/originalView.do?cn=TRKO201500002288&dbt=TRKO&rn=.
4 Jansen, B. J. (2006). Search log analysis: What it is, what's been done, how to do it. Library & Information Science Research, 28(3), 407-432. https://doi.org/10.1016/j.lisr.2006.06.005.   DOI
5 Agosti, M., Crivellari, F., & Di Nunzio, G. M. (2012). Web log analysis: A review of a decade of studies about information acquisition, inspection and interpretation of user interaction. Data Mining and Knowledge Discovery, 24(3), 663-696. https://doi.org/10.1007/s10618-011-0228-8.   DOI
6 Bates, M. J. (1989). The design of browsing and berrypicking techniques for the online search interface. Online Review, 13(5), 407-424. https://doi.org/10.1108/eb024320.   DOI
7 Bollen, J., & Luce, R. (2002). Evaluation of digital library impact and user communities by analysis of usage patterns. http://www.dlib.org/dlib/june02/bollen/06bollen.html.
8 Borgman, C. L., Hirsh, S. G., & Hiller, J. (1996). Rethinking online monitoring methods for information retrieval systems: From search product to search process. Journal of the American Society for Information Science, 47(7), 568-583. https://www.proquest.com/openview/20c67ac9d22a200ad3f6af80a29769c6/1?pq-origsite=gscholar&cbl=41136.   DOI
9 Choo, C. W., Detlor, B., & Turnbull, D. (2000). Information seeking on the web: An integrated model of browsing and searching. First Monday, 5(2). https://doi.org/10.5210/fm.v5i2.729.   DOI
10 Jin, J. Y., & Rieh, H. (2018). Analysis of users' inflow route and search terms of the Korea National Archives' web site. Journal of the Korean Society for information Management, 35(1), 183-203. https://doi.org/10.3743/KOSIM.2018.35.1.183.   DOI
11 Park, M., & Lee, T.-S. (2016). A longitudinal study of information needs and search behaviors in science and technology: A query analysis. Electronic Library, 34(1), 83-98. https://doi.org/10.1108/EL-04-2014-0058.   DOI
12 Lee, T. S., Jeong, D. H., Moon Y. S., Park, M. S., & Hyun, M. H. (2012). An analytic study on the categorization of query through automatic term classification. The KIPS Transactions: Part D, 19D(2), 133-138. https://doi.org/10.3745/KIPSTD.2012.19D.2.133.   DOI
13 Park, M., & Lee, T.-S. (2013). Understanding science and technology information users through transaction log analysis. Library Hi Tech, 31(1), 123-140. https://doi.org/10.1108/07378831311303976.   DOI
14 Park, S. Y. (2011). Trends and changes of web searching behavior. Journal of the Korean Society for Library and Information Science, 45(1), 377-393. https://doi.org/10.4275/KSLIS.2011.45.1.377.   DOI
15 Park, S. Y., & Lee, J. H. (2007). Applications of transaction log analysis for the web searching field. Journal of the Korean Society for Library and Information Science, 41(1), 231-242. https://doi.org/10.4275/KSLIS.2007.41.1.231.   DOI
16 Peters, T. A. (1993). The history and development of transaction log analysis. Library Hi Tech, 11(2), 41-66. https://doi.org/10.1108/eb047884.   DOI
17 Rice, R. E., & Borgman, C. L. (1983). The use of computer-monitored data in information science and communication research. Journal of the American Society for Information Science, 34(4), 247-256. https://www.dhi.ac.uk/san/waysofbeing/data/health-jones-rice-1983c.pdf.   DOI
18 Borgman, C. L. (1986). The user's mental model of an information retrieval system: An experiment on a prototype online catalog. International Journal of Man-Machine Studies, 24(1), 47-64. https://doi.org/10.1016/S0020-7373(86)80039-6.   DOI
19 Choi, D. W., Gang, J. Y., Yang, D., Lee, H., & Oh, H. J. (2018). An analysis of library culture program management based on users' participation logs: A case study of National Library of Korea, Sejong. Journal of Korean Library and Information Science Society, 49(1), 293-320. https://doi.org/10.16981/kliss.49.201803.293.   DOI
20 Lee, H., & Yim, J. H. (2015). A case study analysing the users of archives through web analytics. Korean Journal of Archival Studies, 45, 83-120. https://doi.org/10.20923/kjas.2015.45.083.   DOI
21 Yoo, S.-R. (2002). User-oriented evaluation of NDSL information service. Journal of the Korean Society for Library and Information Science, 36(1), 25-40. https://doi.org/10.4275/KSLIS.2002.36.1.025.   DOI
22 Jansen, B. J., Spink, A., & Taksa, I. (2009). Handbook of research on web log analysis. IGI Global.