Interpreting User Inactivity on Search Results
The lack of user activity on search results was until recently perceived as a sign of user dissatisfaction from retrieval performance, often, referring to such inactivity as a failed search (negative search abandonment). However, recent studies suggest that some search tasks can be achieved in the contents of the results displayed without the need to click through them (positive search abandonment); thus they emphasize the need to discriminate between successful and failed searches without follow-up clicks. In this paper, we study users’ inactivity on search results in relation to their pursued search goals and investigate the impact of displayed results on user clicking decisions. Our study examines two types of post-query user inactivity: pre-determined and post-determined depending on whether the user started searching with a preset intention to look for answers only within the result snippets and did not intend to click through the results, or the user inactivity was decided after the user had reviewed the list of retrieved documents. Our findings indicate that 27% of web searches in our sample are conducted with a pre-determined intention to look for answers in the results’ list and 75% of them can be satisfied in the contents of the displayed results. Moreover, in nearly half the queries that did not yield result visits, the desired information is found in the result snippets.
KeywordsTask-oriented search queries without clickthrough search abandonment user study interactive IR
Unable to display preview. Download preview PDF.
- 1.Agichtein, E., Brill, E., Dumais, S., Rango, R.: Learning user interaction models for predicting search result preferences. In: Proceedings of the 29th ACM SIGIR Conference (2006)Google Scholar
- 4.Claypool, M., Le, P., Waseda, M., Brown, D.: Implicit interest indicators. In: Proceedings of the International Conference on Intelligent User Interfaces, pp. 33–40 (2001)Google Scholar
- 6.Cutrell, E., Guan, Z.: What are you looking for? an eye-tracking study of information usage in web search. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 407–416 (2007)Google Scholar
- 8.Granka, L.A., Joachims, T., Gay, G.: Eye-tracking analysis of user behaviour in www results. In: Proceedings of the ACM SIGIR Conference, pp. 478–479 (2004)Google Scholar
- 9.Huang, J., Efthimiadis, E.N.: Analyzing and Evaluating Query Reformulation Strategies in Web Search Logs. In: Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM), Hong Kong, November 2-6, pp. 77–86 (2009)Google Scholar
- 16.Qiu, F., Liu, Z., Cho, J.: Analysis of user web traffic with a focus on search activities. In: Proceedings of the International Workshop on the Web and Databases, WebDB (2005)Google Scholar
- 17.Radlinski, F., Kurup, M., Joachims, T.: How does clickthrough data reflect retrieval quality. In: Proceedings of the CIKM Conference (2008)Google Scholar
- 19.Sarma, A., Gollapudi, S., Ieong, S.: Bypass rates: reducing query abandonment using negative inferences. In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 177–185 (2008)Google Scholar
- 20.Scott, J.L., Huffman, B., Tokuda, A.: Good abandonment in mobile and pc internet search. In: Proceedings of the 32nd Annual ACM SIGIR Conference, Boston, MA, pp. 43–50 (2009)Google Scholar
- 21.Sharma, H., Jansen, B.J.: Automated evaluation of search engine performance via implicit user feedback. In: Proceedings of the 28th ACM SIGIR Conference, pp. 649–650 (2005)Google Scholar
- 23.Stamou, S., Efthimiadis, E.N.: Queries without clicks: successful or failed searches? In: Proceedings of the SIGIR Workshop on the Future of Information Retrieval Evaluation, Boston, MA, USA (2009)Google Scholar
- 25.Teevan, J., Adar, E., Jones, R., Potts, M.: Information re-retrieval: repeat queries in Yahoo’s logs. In: Proceedings of the 30th ACM SIGIR Conference (2007)Google Scholar