1. Effects of Position and Number of Relevant Documents on Users’ Evaluations of System Performance A presentation by Meg Eastwood on the 2010 paper by D. Kelly, X. Fu, and C. Shah INF 384H September 26th, 2011 1

3. Ph.D., Rutgers University (Information Science)

4. MLS, Rutgers University (Information Retrieval)

5. BA, University of Alabama (Psychology and English)

6. Graduate Certificate in Cognitive Science, Rutgers Center for Cognitive Science2

7. Primary Aim of Research “to investigate the relationship between actual system performance and users’ evaluations of system performance” (pg 9:2) 3

8. Secondary Aim of Research “to develop an experimental method that can be used to isolate and study specific aspects of the search process” (pg 9:2) 4

9. Previous Experimental Protocols Traditional lab-based Naturalistic TREC Interactive Track Study entire search episodes Thomas and Hawking (2006) Trade control for “ecological validity” 5 Both designs include so many variables that it can be “difficult to establish causal relationships” (pg 9:2)

10. Literature Review Main criticisms of previous studies: Evaluation measures were calculated based on TREC assessor’s relevance judgments, not user judgments Users not provided with explicit instructions Users may have been fatigued Low sample sizes 6

11. Methods 7

12. Studies 1 and 2 : effect of position of relevant documents on user’s evaluation of system performance Study 3: effect of number of relevant documents 8

13. 9 Participants were asked to help researchers evaluate four search engines For each search engine, read topic and posed one query

14. 10 After issuing query, all participants were re-directed to the same results page with 10 standardized results

15. 11 Participants asked to evaluate full text of each search result in the order presented and judge the relevance

16. 12 After evaluating all the documents on the results page, participants were asked to evaluate the search engine

17. Study 1 Operationalized average precision at n Subjects required to evaluate all 10 documents 13

18. Study 2 Also operationalized average precision at n Subjects instructed to find five relevant documents 14

19. Study 3 – Operationalized Precision at n 15

20. Topics and Documents 16 Selected topics associated with newspaper articles about current events Selected documents with “high probability of being judged relevant or not relevant” (pg 9:12)

21. Study Participants 17 “Convenient sample” (pg 9:27) of undergraduates from UNC 27 participants for each study (1 -3) Demographic information collected: Sex Age Major Search experience Search frequency

22. Results Relevance Assessments 18

23. Did users’ relevance judgments agree with baseline assessments? 19

24. Did users’ relevance judgments agree with baseline assessments? 20

25. Did the topic affect differences in relevance assessments? 21

26. How much did relevance assessments vary between documents? 22

27. Results Evaluations of System Performance 23

28. Did participants modify evaluation ratings? 24

29. Participant ratings compared between performance levels and studies 25

30. Participant ratings compared between performance levels and studies 26 Study 1 showed no significant differences in ratings according to performance level

31. Participant ratings compared between performance levels and studies 27 Studies 2 and 3 did show significant differences in ratings according to performance level

32. What are the differences between study 1 and study 2? Intended difference: Completion time? 28

33. What are the differences between study 1 and study 2? Unintended differences: Instructions for study 2 provided clearer performance objective Subjects felt more successful in study 2? 29

34. User Experienced Precision 30 “experimental manipulations [of precision] were only 90% effective” (pg 9:24)

35. Are user-experienced precision values correlated with user ratings of system performance? 31

36. Are user-experienced precision values correlated with user ratings of system performance? 32

37. Regression analysis: can you use experienced precision to predict user evaluation? 33

38. Authors’ Discussion and Conclusions “…variations in precision at 10 scores have the greatest impact on subjects’ evaluation ratings.” (pg 9:26) Thoughtful analysis of experimental caveats and generalizability of results Convenient sample of students Only one genre of documents represented Are these results specific to informational/exploratory tasks? 34

39. Suggested Class Discussion Topics Areas where the experiment may have been too tightly controlled/artificial: Controlling order in which users could rate documents? Areas where the experiment may not have been as controlled as the authors intended: Allowing subjects to formulate own queries Study 2 allowed participants to feel “successful”? Ten-point evaluation scale versus five-point evaluation scale? 35

40. References Kelly, D., Fu, X., and Shah, C. 2010. Effects of position and number of relevant documents retrieved on users’ evaluations of system performance. ACM Trans. Inf. Syst. 28, 2, Article 9 (May 2010), 29 pages. DOI 10.1145/1740592.1740597. http://doi.acm.org/10.1145/1740592.1740597 36