human-information interaction · importance of sensemaking x75% of “significant tasks” on the...
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stanford hci group / cs147
http://cs147.stanford.edu06 November 2007
Human-Information Interaction
Scott Klemmertas: Marcello Bastea-Forte, Joel Brandt,Neil Patel, Leslie Wu, Mike Cammarano
Questions about the Project
Engelbart Video
Form Me to You
ADAPTIVE BEHAVIOR107 (months) SOCIAL Social Behavior106 (weeks)105 (days)104 (hours) RATIONAL Adaptive Behavior
103
102 (minutes)101 COGNITIVE Immediate Behavior100 (seconds)10-1
10-2 BIOLOGICAL 10-3 (msec)10-4
MegStewart
HUMAN INFORMATION INTERACTION
GOMS
Routine cognitive skillWell-known path
Information Search
Problem solvingHeuristic searchExponential if don’t know what to do
OPTIMALITY THEORYInformationEnergy
MaxUseful info
TimeMaxEnergyTime [ ][ ]
Optimal Foraging Theory Information Foraging Theory
Information Foraging Theory:
patchWithinpatchBetweenWB TTGain
TTGR
−− +=
+=
Microeconomics of information access.
People are information rate maximizers of benefits/costsInformation has a cost structure
Desk DeskShelf
Computer
ActiveProjectPiles
ReferenceArea
INFORMATION PATCHES
e.g. desk piles,Alta vista search list
unlike animalsforaging for food, humans can do patch construction
We’ll stay in a patch longer…
When a patch is highly profitableAs distance between patches increasesWhen the environment as a whole is less profitable
WITHIN-PATCH ENRICHMENT:
INFORMATION SCENT
perception of value and cost of a path to a source based on proximal cues
Relevance-Enhanced Thumbnails Within-patch
enrichmentEmphasize text that is relevant to query
Text callouts
020406080
100120140160180
Picture Homepage E-commerce Side-effects
Tot
al S
earc
h T
ime
(s)
Text Plain Enhanced
Allison Woodruff
PHASE TRANSITION IN NAVIGATION COSTS AS FUNCTION OF INFORMATION SCENT
Notes: Average branching factor = 10Depth = 10
0 2 4 6 8 100
50
100
150
Depth
Num
ber o
f pag
es v
isite
d
.100
.125
.150
0 2 4 6 8 100
50
100
150
.100
.150
Probability of choosing wrong link (f)
0 0.05 0.1 0.15 0.20
20
40
60
80
100
f
Num
ber o
f Pag
es V
isite
d pe
r Lev
el
Linear Exponential
IMPORTANCE FOR WEB DESIGN
Jarad Spool, UIE
Peter Pirolli
MACHINE MODELING OF INFORMATION SCENT
cell
patient
dose
beam
new
medical
treatments
procedures
InformationGoal Link Text
PREDICTION OF LINK CHOICER2 = 0.72
0
5
10
15
20
25
30
35
0 5 10 15 20 25 30 35Observed frequency
Pred
icte
d fr
eque
ncy
R2 = 0.90
0
10
20
30
40
50
0 10 20 30 40 50Observed frequency
Pred
icte
d fr
eque
ncy(a) ParcWeb (b) Yahoo
USER FLOW MODEL
Flow users through the network
User need (vector of goal concepts)
Determine relevance of documents
.5.3
.2
Calculate Pr(Link Choice) for each page Examine user patternsStart users at page
SENSE MAKING TASKSCharacteristics
Massive amounts of dataIll-structured taskOrganization, interpretation, insight neededOutput, decision, solution required
ExamplesUnderstanding a health problem and making a medical decisionBuying a new laptopWeather forecastingProducing an intelligence report
Importance of Sensemaking75% of “significant tasks” on the Web are more than simple “finding” of information (Morrison et al., 2001)
Understanding a topic (e.g., about health)Comparing/choosing products
Information retrieval does not support these tasks (Bhavnani et al., 2002)
E.g., Estimated that one must visit 25 Web pages in order to read about 12 basic concepts about skin cancer
SENSEMAKING
SHOEBOX
EVIDENCE FILE
Search & Filter
Read & Extract
Schematize
Build Case
Tell Story
Search for Information
Search for Relations
Search for Evidence
Search for Support
Reevaluate
TIME or EFFORT
STRU
CTUR
E
SCHEMAS
HYPOTHESES
PRESENTATION
EXTERNAL DATA
SOURCES
SENSEMAKING
SHOEBOX
EVIDENCE FILE
Search & Filter
Read & Extract
Schematize
Build Case
Tell Story
Search for Information
Search for Relations
Search for Evidence
Search for Support
Reevaluate
TIME or EFFORT
STRU
CTUR
E
SCHEMAS
HYPOTHESES
PRESENTATION
EXTERNAL DATA
SOURCES
Sensemaking Loop
Foraging Loop
Credits & Further Reading
This lecture draws heavily on Stu Card’s slides on HIIPeter Pirolli, Information Foraging