ABSTRACT
The complex and dynamic nature of search processes surrounding information seeking have been exhaustively studied. Recent studies have highlighted search processes with different intentions, such as those for entertainment purposes or re-finding a visited information object, are fundamentally different in nature to typical information seeking intentions. Despite the popularity of such search processes on the Web, they have not yet been thoroughly explored. Using a video retrieval system as a use case, we study the characteristics of four different search task types: seeking information, re-finding a particular information object, and two different entertainment intentions (i.e. entertainment by adjusting arousal level, and entertainment by adjusting mood). In particular, we looked at the cognition, emotion and action aspects of these search tasks at different phases of a search process. This follows the common assumption in the information seeking and retrieval community that a complex search process can be broken down into a relatively small number of activity phases. Our experimental results show significant differences in the characteristics of studied search tasks. Furthermore, we investigate whether we can predict these search tasks given user's interaction with the system. Results show that we can learn a model that predicts the search task types with reasonable accuracy. Overall, these findings may help to steer search engines to better satisfy searchers' needs beyond typically assumed information seeking processes.
- I. Arapakis, J. M. Jose, and P. D. Gray. Affective Feedback: An Investigation into the Role of Emotions in the Information Seeking Process. In SIGIR, 395--402, 2008. Google ScholarDigital Library
- I. Arapakis, I. Konstas, and J. M. Jose. Using Facial Expressions and Peripheral Physiological Signals as Implicit Indicators of Topical Relevance. In MM, pages 461--470, 2009. Google ScholarDigital Library
- I. Arapakis, Y. Moshfeghi, H. Joho, R. Ren, D. Hannah, and J. M. Jose. Enriching User Profiling with Affective Features for the Improvement of a Multimodal Recommender System. CIVR, 2009. Google ScholarDigital Library
- N. Belkin. Helping People Find What They Don't Know. Communications of the ACM, 43(8):58--61, 2000. Google ScholarDigital Library
- N. Belkin, C. Clarke, N. Gao, J. Kamps, and J. Karlgren. Report on the SIGIR Workshop on Entertain Me: Supporting Complex Search Tasks. In ACM SIGIR Forum, volume 45, 51--59. 2012. Google ScholarDigital Library
- N. Belkin, C. Cool, A. Stein, and U. Thiel. Cases, Scripts, and Information-Seeking Strategies: On the Design of Interactive Information Retrieval Systems. Expert systems with applications, 9(3):379--395, 1995.Google Scholar
- N. Belkin, R. Oddy, and H. Brooks. Ask for Information Retrieval: Part i. Background and Theory. Journal of Documentation, 38(2):61--71, 1982.Google ScholarCross Ref
- P. Borlund and P. Ingwersen. The Development of a Method for the Evaluation of Interactive Information Retrieval Systems. Journal of Documentation, 53(3):225--250, 1997.Google ScholarCross Ref
- A. Broder. A Taxonomy of Web Search. In ACM SIGIR forum, volume 36, 3--10. 2002. Google ScholarDigital Library
- Z. Cheng, B. Gao, and T.-Y. Liu. Actively Predicting Diverse Search Intent from User Browsing Behaviors. In WWW, 221--230. 2010. Google ScholarDigital Library
- P. Ekman and R. J. Davidson. The Nature of Emotion: Fundamental Questions. Oxford University Press, 1994.Google Scholar
- D. Elsweiler, M. Harvey, and M. Hacker. Understanding Re-finding behavior in Naturalistic Email Interaction Logs. In SIGIR, 35--44. 2011. Google ScholarDigital Library
- D. Elsweiler, S. Mandl, and B. Kirkegaard Lunn. Understanding Casual-Leisure Information Needs: a Diary Study in the Context of Television Viewing. In IIiX, 25--34, 2010. Google ScholarDigital Library
- D. Elsweiler, M. Wilson, and M. Harvey. Searching4fun. 2012.Google Scholar
- D. Elsweiler, M. Wilson, and B. Lunn. Understanding Casual-Leisure Information Behaviour. Library and Information Science, 211:241, 2011.Google Scholar
- K. E. Fisher, S. Erdelez, and L. McKechnie. Theories of Information Behavior. Information Today Inc, 2005. Google ScholarDigital Library
- Q. Guo and E. Agichtein. Towards Predicting Web Searcher Gaze Position from Mouse Movements. In CHI Extended Abstracts, 3601--3606, 2010. Google ScholarDigital Library
- J. Gwizdka and I. Lopatovska. The Role of Subjective Factors in the Information Search Process. JASIST, 60(12):2452--2464, 2009. Google ScholarDigital Library
- P. Ingwersen. Information Retrieval Interaction. Number s 246. Taylor Graham London, 1992. Google ScholarDigital Library
- P. Ingwersen. Polyrepresentation of Information Needs and Semantic Entities: Elements of a Cognitive Theory for Information Retrieval Interaction. In SIGIR, 101--110, 1994. Google ScholarDigital Library
- C. Kuhlthau, J. Heinström, and R. Todd. The 'information Search Process' Revisited: Is the Model Still Useful. Information Research, 13(4):13--4, 2008.Google Scholar
- C. C. Kuhlthau. A Principle of Uncertainty for Information Seeking. Journal of Documentation, 49(4):339--355, 1993.Google ScholarCross Ref
- C. C. Kuhlthau. Accommodating the User's Information Search Process: Challenges for Information Retrieval System Designers. Bulletin of ASIS&T, 25(3):12--16, 2005.Google Scholar
- X. Li, Y. Wang, and A. Acero. Learning Query Intent from Regularized Click Graphs. In SIGIR, volume 339, 346. 2008. Google ScholarDigital Library
- I. Lopatovska. Searching for good mood: Examining relationships between search task and mood. ASIST, 46(1):1--13, 2009.Google ScholarCross Ref
- R. McGill, J. W. Tukey, and W. A. Larsen. Variations of Box Plots. American Statistician, 32(1):12--16, 1978.Google Scholar
- Y. Moshfeghi and J. M. Jose. Role of Emotion in Information Retrieval for Entertainment (Position Paper). Searching4FUN Workshop in ECIR, 2012.Google Scholar
- M. B. Oliver. Mood management and Selective Exposure. Communication and Emotion: Essays in Honor of Dolf Zillmann, 85--106, 2003.Google Scholar
- A. Poddar and I. Ruthven. The Emotional Impact of Search Tasks. In IIiX, 35--44. 2010. Google ScholarDigital Library
- D. Robins. Shifts of Focus in Information Retrieval Interaction. In ASIST, volume 34, 123--134, 1997.Google Scholar
- T. Saracevic. Relevance: A Review of and a Framework for the Thinking on the Notion in Information Science. JASIST, 26(6):321--343, 1975.Google ScholarCross Ref
- C. Sheldrick Ross. Finding without Seeking: The Information Encounter in the Context of Reading for Pleasure. Information Processing & Management, 35(6):783--799, 1999. Google ScholarDigital Library
- Y. Shen, J. Yan, S. Yan, L. Ji, N. Liu, and Z. Chen. Sparse Hidden-Dynamics Conditional Random Fields for User Intent Understanding. In WWW, 7--16. 2011. Google ScholarDigital Library
- J. A. Singer and P. Salovey. Mood and Memory: Evaluating the Network Theory of Affect. Clinical Psychology Review, 1988.Google ScholarCross Ref
- A. Spink, H. Greisdorf, and J. Bateman. From Highly Relevant to Not Relevant: Examining Different Regions of Relevance. Information Processing & Management, 34(5):599--621, 1998. Google ScholarDigital Library
- R. Taylor. Question-Negotiation an Information-seeking in Libraries. Technical report, DTIC Document, 1967.Google Scholar
- J. Teevan, E. Adar, R. Jones, and M. Potts. Information Re-Retrieval: Repeat Queries in Yahoo's Logs. In SIGIR, 151--158. 2007. Google ScholarDigital Library
- C. van Rijsbergen. (Invited Paper) A New Theoretical Framework for Information retrieval. In SIGIR, 194--200. 1986. Google ScholarDigital Library
- P. Vorderer. Entertainment theory. Communication and Emotion: Essays in Honor of Dolf Zillmann, 131--153, 2003.Google Scholar
- R. W. White, J. M. Jose, and I. Ruthven. An Implicit Feedback Approach for Interactive Information Retrieval. Information processing & management, 42(1):166--190, 2006. Google ScholarDigital Library
- M. Wilson and D. Elsweiler. Casual-leisure Searching: the Exploratory Search Scenarios that Break our Current Models. In HCIR, 28--31, 2010.Google Scholar
- D. Zillmann. Mood Management: Using Entertainment to Full Advantage. In L. Donohew, H.E. Sypher, & E.T. Higgins (Eds.), Communication, social cognition, and affect, 147--171, 1988.Google Scholar
Index Terms
- On cognition, emotion, and interaction aspects of search tasks with different search intentions
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