Talk given to the University of Glasgow IR group on the 18th June 2012. #HCIR

1. Search User Interface Design
Dr Max L. Wilson
Mixed Reality Lab
University of Nottingham, UK
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

2. About Me
Social Media Search
My Research Areas Casual Search
Search User Interface Design
My Framework
Information vs Interaction
Brain Response
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

3. Software Engineering MEng
HCI & Information Science PhD
Web Science and Semantic Web
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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4. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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5. UIST
2008
JCDL
2008
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

6. My PhD
Bates, M. J. (1979a). Idea tactics. Journal of
the American Society for Information
Belkin, N. J., Marchetti, P. G., and Cool, C. Science, 30(5):280–289.
(1993). Braque: design of an interface to support
user interaction in information retrieval. Bates, M. J. (1979b). Information search
Information Processing and Management, 29(3): tactics. Journal of the American Society for
325–344. Information Science, 30(4):205–214.
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

7. My PhD
Wilson, M. L., schraefel, m. c., and White, R. W. (2009). Evaluating advanced
search interfaces using established information-seeking models. Journal of the
American Society for Information Science and Technology, 60(7):1407–1422.
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

8. Come and Sii what I’ve built
http://mspace.fm/sii
Best JASIST article 2009
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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9. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

10. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

11. About Me
Social Media Search
My Research Areas Casual Search
Search User Interface Design
My Framework
Information vs Interaction
Brain Response
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

12. to observe that experience with or of the subject matter was In the post-task interviews, we asked users to informally
important to the information seekers. We also see two very augment their relevance judgments with scores out of 5.
interesting codes appear in this task, which are able to Overall, the mean score for all rated tweets over all three
compliment each other, the first being shared sentiment, tasks was 2.2, indicating a very low relevancy score.
and secondly entertaining. Both of these codes are Individually, the first task, which was temporal in nature,
Social Media Search
subjective in nature, which could be expected a subjective
task. Useful links and experience were also played an
important role in this task. Many participants found this
scored 2.7. The second task, which involved users search
for information regarding purchasing an iPhone, scored a
very low 1.25. The third and final task, which was a
In Tweet Content T1 T2 T3
Experience Someone reporting a personal experience, but not necessarily suggestion / direction. 15 12 13
Direct Someone making a direct recommendation, but not necessarily relaying a personal 3 3 20
Recommendation experience.
Social Knowledge Containing information that is spreading socially, or becoming general knowledge. 7 6 6
Specific Where facts are listed directly in tweets e.g. prices, times etc. 51 10 47
Information
Reflection on Tweet
Entertaining The reader finds them amusing. 1 3 2
Shared Sentiment The reader agrees with the author of the tweet. 1 2 1
Relevant
Time The time is current. 14 0 2
Location The location is relevant to the query. 6 1 40
Trust
Trusted Author The twitter account has a reputation / following. 3 2 6
Trusted Avatar The visual appearance cultivates trust. 2 0 2
Trusted Link A link to a trustworthy recognizable domain. 14 1 7
Links
Actionable Link The user can perform a transaction by using the link (heavily dependent on trust). 9 0 0
Media Link The link is to rich multimedia content. 9 0 0
Useful Link The link provides valuable information content, e.g. authoritative information, educated 61 30 43
reviews, and discussions.
Meta Tweet
Retweeted Lots Its information that others have passed on lots. 4 0 4
Conversation It is part of a series of tweets, and they all need to be useful. 1 4 4
Table 3. The 16 codes and the 6 categories extracted from responses and tweet pairs from the useful tweets. Further, columns 3-5 show how
ICWSM 2011
frequently each was associated with the temporal (T1), subjective (T2) and location-sensitive (T3) tasks.
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

13. Social Media Search
INSERT VIDEO
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

14. D
behaviours documented so far.
4.1 Need-less browsing d
Casual Leisure Search
Much like the desire to pass time at the television, we saw
many examples (some shown in Table 3) of people passing
a
time typically associated with the ‘browsing’ keyword. 5
h
1) ... I’m not even *doing* anything useful... just browsing
eBay aimlessly...
f
2) to do list today: browse the Internet until fasting break o
time.. S
3) ... just got done eating dinner and my family is watch-
ing the football. Rather browse on the laptop
i
4) I’m at the dolphin mall. Just browsing. b
a
Table 3: Example tweets where the browsing activ- d
ity is need-less. f
t
From the collected tweets it is clear that often the inform- s
ation-need in these situations are not only fuzzy, but2010
HCIR typi- W
cally absent. The aim appears to be focused on the activity, t
where the measure of success would be in how much they
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

15. Casual Leisure Search
Springer Book Chapter - Award: Outstanding Author Contribution
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

16. About Me
Social Media Search
My Research Areas Casual Search
Search User Interface Design
My Framework
Information vs Interaction
Brain Response
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

17. Search User Interface Design
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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18. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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20. 4
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Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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21. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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22. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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23. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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24. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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25. 4
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Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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26. 4
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Input Features
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27. 4
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28. 1
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Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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29. 14 13
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Personalisable Features
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Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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30. SUI Design Taxonomy
Input Features
Control Features
Informational Features
Personalisable Features
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

31. SUI Design Taxonomy
Input Features Search box
Query-by-example
Control Features Clusters/Categories
Taxonomies
Informational Features Facets
Social annotations
Personalisable Features
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

32. Auto-complete/suggest 4.1. INPUT FEATURES 31
(a) Apple – shows lots of contextual informa- (b) Google – prioritising previous searches.
tion and multimedia.
Figure 4.1: Examples of AutoComplete.
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

33. SUI Design Taxonomy
Input Features
Query Suggestions
Control Features Corrections
Sorting
Filters
Informational Features
Groupings
Personalisable Features
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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34. 46
Sorting
4. MODERN SEARCH USER INTERFACES
(a) Sorting in Amazon (b) Sorting in Walmart (c) Sorting in Yahoo!
(d) Tabular sorting in Scan.co.uk.
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

35. SUI Design Taxonomy
Snippets
Input Features Usable Info
Thumbnails
Previews
Control Features
Relevance Info
2D & 3D Viz
Informational Features Guiding numbers
Zero-click answers
Personalisable Features Signposting
Pagination
Social Info
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

36. Usable Information
Figure 4.17: Snippets in Ciao’s search results can be extended using the ‘more’ link.
Figure 4.18: Results in Sainsbury’s groceries search can be added to the shopping basket without having
to leave the search page.
allows searchers to add items to their cart from the SERP, as shown in Figure 4.18. If searchers are
unsure if an item is right for them, however, they can view a page with more information about
each product, and buy from there too. Ciao!, in Figure 4.17, also has a range of usable links in
their results, including links directly to reviews, pricing options, and to the category that an item
belongs in. In Google Image Search, there is a usable link that turns any result into a new search for
‘Similar Images,’ as discussed in the Query-by-example section above. Further, searchers may now
Dr Max L. Wilson ‘+1’ a result in a Google SERP, without affecting or interrupting their search. Finally, searching http://cs.nott.ac.uk/~mlw/
in
Monday, 2 July 12 23

37. 74 4. MODERN SEARCH USER INTERFACES
Social Information
Recommendation
• Track and reuse information about the behaviour of a systems
searchers.
Figure 4.39: Amazon often provides feedback to tell searchers what people typically end up actually
buying.
or even the way they are presented. Further, they can affect the Control features that are provided.
For clarification, there has been a lot of work that has focused on algorithmic personalisation for
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12 search, which has a whole book of its own [133]. Instead, this section focuses on different types of

38. SUI Design Taxonomy
Input Features
Control Features
Informational Features
Personalisable Features Current-search
Persistent
Socialised
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

39. 76 4. MODERN SEARCH USER INTERFACES
Search Histories
Recommendation
• Help searchers to return to previously viewed SERPs and results.
(a) History of searches in PubMed. (b) History of searches and results in Ama-
zon.
Figure 4.41: SUIs can help searchers get back to previous searches by keeping a history.
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

40. SUI Design Taxonomy
Input Control
Informational Personalisable
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

41. The Search Box
Input Control
Query
Only
sb
Informational Personalisable
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

42. The Search Box
Input Control
with
auto- sb
suggest
Informational Personalisable
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

43. The Search Box
Input Control
If query
sb is persistent
in search box
Informational Personalisable
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

44. The Search Box
Input Control
with auto-
suggest,
and query
left in
sb place, and
if auto-
suggest
includes
search
Informational Personalisable history
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

45. The Sweet Spot for SUI design
Input Control
Informational Personalisable
Good SUI features fit into >1 category
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

46. Search User Interface Design
• The Taxonomy
• Historical context
• Lots of examples
• 20 Design Recommendations
• Future Trends
• Evaluation notes
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

47. About Me
Social Media Search
My Research Areas Casual Search
Search User Interface Design
My Framework
Information vs Interaction
Brain Response
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

48. Search User Interface Design
Does Interaction Matter?
Does interaction provide significant benefits to users?
Or is it just more information and more data?
How should companies prioritise investment in these areas?
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

49. Information vs Interaction
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

50. Information vs Interaction
Useful info - or Efficient interaction?
• Kelly et al (2009) - query suggests > term suggestions
• Ruthven (2003) - humans not good at choosing useful ones
• Diriye (2009) - slow people down during simple tasks
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

51. Information vs Interaction
Useful data? Efficient
(from good algorithm) interaction?
• Hearst & Pederson (1996) - better task performance
• Pirolli et al (1996) - helped to understand corpus
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

52. Information vs Interaction
Powerful interaction?
or lots of useful data?
• Hearst (2006) - careful metadata is always better than clusters
• Wilson & schraefel (2009) - good for understanding corpus
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

53. Information vs Interaction
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

54. Information vs Interaction
Query data
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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55. Information vs Interaction
Clustered
Query data
algorithms
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

56. Information vs Interaction
Clustered Faceted
Query data
algorithms metadata
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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57. Information vs Interaction
Query data
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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58. Information vs Interaction
Figure 1: The three interaction conditions in the stu
common form. UIC in the middle presents secondar
hierarchical clustering. UIF on the right, which inclu
terms, or facets, that can be applied to or removed fr
- H1: Searchers will be more efficient with more
powerful interaction, using the same metadata, when
completing search tasks.
- H2: Searchers will enjoy more powerful interaction,
Query data despite using the same metadata.
- H3: Searchers will use query recommendations more
when they are presented differently.
Dr Max L. Wilson In order to accept or reject these hypotheses, we designed a
http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12
3x2 repeated-measures study using two independent

59. 3 Conditions
UIQ UIC UIF
Figure 1: The three interaction conditions in the study. UIQ on the left presents query suggestions in their
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
common form. UIC in the middle presents secondary query suggestions with an interaction model based on
Monday, 2 July 12

60. xperience, standard Two standard types of user study task were used in the
he Bing API for the study: 1) a simple lookup task and 2) an exploratory task.
op-level entities in All six tasks are shown in Table 1.
n, UIC then asked
2 Types of Task
The simple lookup tasks had a fixed answer, but the chosen
h were represented task description was presented in such a way that the most
To create the same likely query would not find the answer without subsequent
wsing through the queries or refinements. This approach was chosen to
ies, the searchers intrinsically encourage participants to use the IIR features
box. As well as on the left of each user interface condition.
n selected in the
dard terminology to Table 1: Tasks set to participants in the study.
em in hierarchy]’. S = Simple, E = Exploratory
technically issuing ID S/E Task Description
xperience appeared 1 S What is the population of Ohio?
fferent sub-clusters
y. 2 E Find an appropriate review of “Harry Potter and
the Deathly Hallows”.
filtering systems,
- Compare the rating with the previous film.
of metadata made
mbination in order 3 S Find the first state of America.
s able to flexibly 4 E Deduce the main problems that Steve Jobs
f keyword filters in incurred with regards to his health.
or and narrow their 5 S What is the iPad 3’s proposed processor name?
typically maintain
6 E Explore information related to Apple’s next
arch box, and then
iPhone, the iPhone 5.
results to portions
- Note the expected release date. There could well
be multiple rumours.
elves to using just
aimed L. Wilson
Dr Max
to create a http://cs.nott.ac.uk/~mlw/
to apply 12
Monday, 2 July multiple The exploratory search tasks were chosen to be tasks with

61. 18 People
Intro + UI1 UI2 UI3 QA +
Consent 2 tasks 2 tasks 2 tasks Debrief
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

62. 18 People
Intro + UI1 UI2 UI3 QA +
Consent 2 tasks 2 tasks 2 tasks Debrief
Queries
Refinements
Pageviews
Time
Measures
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

63. 18 People
Intro + UI1 UI2 UI3 QA +
Consent 2 tasks 2 tasks 2 tasks Debrief
Queries
Refinements Ease of use
Pageviews Task Satisfaction
Time
Measures
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

64. 18 People
Intro + UI1 UI2 UI3 QA +
Consent 2 tasks 2 tasks 2 tasks Debrief
Queries
Quickest
Refinements Ease of use
Most Enjoyable
Pageviews Task Satisfaction
Best Design
Time
Measures
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

65. Simple vs Exploratory
Measure S E Diff
Time 176s 179s no
Queries 1.75 2.33 p<0.05
Pageviews 1.65 2.09 p<0.005
Refinements 2.42 2.45 no
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

66. Log data By UI
Measure Simple Exploratory
Queries UIQ < UIC & UIF UIQ > UIC & UIF
Refinements No diff UIQ & UIC < UIF
Visits No diff UIQ > UIC & UIF
Time UIQ > UIC < UIF UIC < UIF < UIQ
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

67. Subjective Responses
Measure Simple
Easy of Use UIQ & UIC > UIF
Satisfaction UIQ & UIC > UIF
Question UIQ UIC UIF
Quickest to correct answer 11 5 2
Most enjoyed during task 4 11 3
Most appealing design 5 11 2
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

68. What did we actually learn?
• We did see different behaviour in all 3 conditions
• People were good at simple tasks with original UIQ
• People were faster and more effective with UIC
and preferred it
• People used more filters and viewed fewer pages with UIF
but did not like it so much
• But is it better or worse behaviour?
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

69. Information vs Interaction
Query data
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

70. Information vs Interaction
Clustered Faceted
Query data
algorithms metadata
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

71. Information vs Interaction
Facets
Clusters
Performance
Suggestions
(hypothetically)
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

72. About Me
Social Media Search
My Research Areas Casual Search
Search User Interface Design
My Framework
Information vs Interaction
Brain Response
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

73. SUI Design + Brain Response
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

74. SUI Design + Brain Response
Cognitive Load Theory
Total Mental Capacity
Easy Task
Simple UI
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

75. SUI Design + Brain Response
Cognitive Load Theory
Total Mental Capacity
Hard Task
Simple UI
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

76. SUI Design + Brain Response
Cognitive Load Theory
Total Mental Capacity
Hard Task
Complex UI
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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77. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

78. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

79. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
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80. SUI Design & Brain Response
Clear design recommendations
Cost vs Gain of adding a feature
Ways to reduce cost of a feature
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

81. About Me
Social Media Search
My Research Areas Casual Search
Search User Interface Design
My Framework
Information vs Interaction
Brain Response
Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12

82. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
Monday, 2 July 12