[Analyzing user behavior in virtue of clickstream data analysis]
Another research interest of mine is to explore different methods or frameworks that can be applied to the analysis of human's interaction with websites. It is common to study user behavior based on log analysis. Most previous studies, however, heavily rely on search logs. The problem is that search log analysis, consisting of the analysis of users’ terms, queries, and sessions, is only applicable to examine the usage of web search engines. Clickstream data offers an unobtrusive data source for understanding web users’ information behavior beyond searching. However, it remains underutilized due to the lack of structured analysis procedures. Based on our experience from two case studies with clickstream data analysis, we integrated and proposed an analysis framework. Overall, the integrated analysis framework is designed to be independent of any specific research settings so that it can be easily adopted for different clickstream datasets and research questions.
Chi, Y., Jiang, T., He, D., & Meng, R. (2017). Towards an integrated clickstream data analysis framework for understanding web users’ information behavior. (iConference’17, 34% acceptance rate, Oral) [PDF]
Jiang, T., Chi, Y. & Gao, H. (2017). A clickstream data analysis of Chinese academic library OPAC users’ information behavior. Library & Information Science Research, 39(3), 213-223. [PDF]
[Exploring and designing teens' data worlds in the public library]
As the research assistant of the Youth Data Literacy project , I assisted and led workshops, interviews and observations with teens and staffs at seven branches of the Carnegie Library of Pittsburgh to examine teen data literacy practices and design for appealing data environment. I also led a subproject, exploring the interplay between teens’ Affective states (A), Behavioral states (B), and Cognitive states (C) in relation to the personal data they generate in social media, applying the “ABC model” from the social psychology domain. Given the results, we suggest librarians, educators and software developers apply a range of strategies in reaction to teens’ different ABC states to the design of data literacy programs, services, and software applications.
Chi, Y., Jeng, W., Acker, A., & Bowler, L. (2018, March). Affective, Behavioral, and Cognitive Aspects of Teen Perspectives on Personal Data in Social Media: A Model of Youth Data Literacy. In International Conference on Information (pp. 442-452). Springer, Cham. (iConference’18, 30% acceptance rate, Oral) [PDF]
Bowler, L., Acker, A., Jeng, W., & Chi, Y. (2017). “It lives all around us”: Aspects of data literacy in teen’s lives. Proceedings of the Association for Information Science and Technology, 54(1), 27-35. (ASIS&T’17) [PDF]