Do your friends make you smarter? Exploring social interactions in search

Do your friends make you smarter? Exploring social interactions in search

Supervised by: David KirshBrynn M. Evans

Photo Credit: Mikey Ottawa

i. Search as an activity ii. Related workiii. My previous workiv. Theoretical orientationv. Conclusion

Search as an activity

What hummingbird species is this?

Search Question

Photo Credit: OpenThreads

Icon Credit: fasticon.com & iconaholic.com

Apr 13 Apr 16 Apr 30Apr 20 May 9


Apr 13 Apr 16

GOOGLE

Apr 30Apr 20 May 9


Apr 13 Apr 16

GOOGLE BOOK

Apr 30Apr 20 May 9


Apr 13 Apr 16

FRIENDSGOOGLE BOOK

Apr 30Apr 20 May 9


Apr 13 Apr 16

FRIENDS SOCIAL NETWORK

(http://watch.birds.cornell.edu)

GOOGLE BOOK

Apr 30Apr 20 May 9

http://watch.birds.cornell.edu

http://watch.birds.cornell.edu


Apr 13 Apr 16

FRIENDS SOCIAL NETWORKGOOGLE BOOK

Apr 30Apr 20 May 9 Anna’s Hummingbird!

✔

search ≠ database lookup

search ≠ keyword queries

Photo Credit: B1gJ4k3

search ≠ database lookup

search ≠ keyword queries

Photo Credit: B1gJ4k3

search = an activity

Even smaller searches are embedded in rich activities

Even smaller searches are embedded in rich activities

Photo Source: Peter Voerman

examples from EVANS & CHI 2008

A reaction to the classic view of search

single‐user activity

query‐response mechanism

few keywords, short sessions

log files from single search engine

Photo Credit: Thomas Hawk

classic view of search

Photo Credit: David Wild

revised view of search

activity can involve other people (remotely or co‐located)

highly dynamic, fluid process

search can last over an extended period

search takes place in a rich ecology of social and information resources

ActivitiesGoalsOperators

With a revised notion of search......comes a revised method of study

Searches are composed of:


Log files reveal operators




Observations reveal activities



Related work

SEARCH GOAL

SEA

RC

H L

OC

ATIO

N

ALLEN 1977; CROSS ET AL 2001; CROSS & SPROULL 2004; BORGATTI & CROSS 2003

Information seeking in physical contexts

Photo Credit: Rachael Lovinger

ALLEN 1977; CROSS ET AL 2001; CROSS & SPROULL 2004; BORGATTI & CROSS 2003

Information seeking in physical contexts

Photo Credit: Rachael Lovinger

PROXIMITYHIERARCHY (STATUS) SOCIAL OBLIGATIONS

MORRIS 2008; PICKENS ET AL. 2008; PAUL & MORRIS 2009; SHAH 2008.

(Joint) collaborative search online

CO-SENSESEARCH TOGETHER

SEARCH GOAL

SEA

RC

H L

OC

ATIO

N

How can we improve search with social networking technologies?

Research Questions

Empirical question:

Design question:

How do social interacTons help with individual search tasks?

My previous work

study one survey: everyday searches

study two

study three

survey: difficult or failed searches

observaTons: cogniTve benefits of social interacTons during search

Characterization studies of social search(studies one and two)

EVANS & CHI 2008; EVANS & CHI 2009

generic or “everyday” 150

difficult or failed 150

SEARCH STUDY N =

Mechanical Turk

Photo Credit: egoldviet (USED WITHOUT PERMISSION)

Large scale characterization studies



SEARCH STUDY N =

searching for informaTon assumed to be present, but otherwise unknown

INFORMATIONAL




SEARCH STUDY N =

59%

87%

INFORMATIONAL

searching for informaTon assumed to be present, but otherwise unknown

INFORMATIONAL




SEARCH STUDY N =

59%

87%

INFORMATIONAL

DURING

• search preparaTon• problem formulaTon

• search execuTon• lookup, foraging, re‐finding

• reflecTon, synthesis• feedback, iteraTon• sensemaking

AFTERBEFORE




SEARCH STUDY N =

59%

87%

INFORMATIONAL

40%

61%

SOCIAL INTERACTIONS

DURING

• search preparaTon• problem formulaTon

• search execuTon• lookup, foraging, re‐finding

• reflecTon, synthesis• feedback, iteraTon• sensemaking

AFTERBEFORE


SEARCH GOAL

SEA

RC

H L

OC

ATIO

N

Social tactics do support informational searches, but in different ways:

Social networks: users parse problems themselves, firstTargeting friends: users synthesize info better, later

Cognitive benefits of social searching(study three)

EVANS, KAIRAM, PIROLLI 2009; EVANS, KAIRAM, PIROLLI 2009

PARTICIPANTS (N=8)PRE-TEST SURVEY

• knowledge of energy policies• computer and internet use

• search experTse

• social acTviTes

Icon Credit: Iconaholic.com, dryicon.com

Recruiting subjects

EVANS, KAIRAM, PIROLLI 2009; EVANS, KAIRAM, PIROLLI 2009

Two task questions

Icon Credit: iconfactory.com, http://ecotechdaily.com/wp-content/uploads/2008/05/oil_drums_450.jpg

http://ecotechdaily.com/wp-content/uploads/2008/05/oil_drums_450.jpg


“If we lowered the speed limit nationally to 55 mph, how many fewer barrels of oil would the U.S. consume every year?”

55 mph

Two task questions




“If we lowered the speed limit nationally to 55 mph, how many fewer barrels of oil would the U.S. consume every year?”

55 mph

“What role does pyrolytic oil (or pyrolysis) play in the debate over carbon emissions?”

Pyrolytic oil

Two task questions




Icon Credit: fasticon.com, deleket.com, sykonist.deviantart.com

• friends (email, phone, IM, etc.)

• social networks• blogs•QuesTon‐Answer sites

• search engines (Google, Yahoo)

•Wikipedia

Two search conditions

NON-SOCIALSOCIAL

Talk

-alo

ud p

roto

col

12:00 - 35:00

Icon Credit: mugenb16.deviantart.com, bombiadesign.com, dryicon.com

5:00 - 20:00 5:00 - 40:00 5:00 - 18:00

Protocol

NON-SOCIALSOCIAL INTERVIEW INTERVIEW

Block duration

SEARCHING

NETWORK ASKING

TARGETED ASKING

Icon Credit: fasticon.com, deleket.com, walrick.deviantart.com

Three social tactics

Coding of activities

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SS03

TIME

SEARCHING NETW. ASKING TARGETED ASKING OFF-TASKTHINKINGCHECKING

LEGEND


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SS03

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SS03

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TARGETED ASKING

LEGEND


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!,!!,!!" !,!),#$" !,#&,$&" !,$#,%(" !,$*,&*" !,%(,!!"

SS03

TIME

THINKINGCHECKING FOR REPLIESOFF-TASK

SEARCHING

NETWORK ASKING


TARGETED ASKING

LEGEND

1 identified or perceives facts, data, or info

2understands the meaning of info; presents a translaTon of info

3 integrates and synthesizes learned info

SCORE DESCRIPTION

TIMEEx. of learning of one fact over time

SCORE 1 2 3

Depth of processing

1 identified or perceives facts, data, or info

2understands the meaning of info; presents a translaTon of info

3 integrates and synthesizes learned info

(FINAL)SCORE FOR FACT #1

SCORE DESCRIPTION

TIMEEx. of learning of one fact over time

SCORE 1 2 3

Depth of processing

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the U.S. enacted a 55mph speed limit in 1974

TIME


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+

123323

21

17PERFORMANCE SCORETIME


ID#social tactics

Performance score

S04 1 1

S07 1 3

S02 1 6

S06 2 2

S05 2 9

S08 3 7

S01 3 9

S03 3 17

Spearman R: 0.77

More social tactics leads to better performance

ID#social tactics

Performance score

S04 1 1

S07 1 3

S02 1 6

S06 2 2

S05 2 9

S08 3 7

S01 3 9

S03 3 17

Spearman R: 0.77

More social tactics leads to better performance

SOCIAL TACTICS

TARGETED ASKING

NETWORK ASKING

SEARCHING

Number of social tactics is more predictive of task performance than...

...social network sizeNumber of social tactics is more predictive of task performance than...

...social network size

...how much knowledge is in the network


...social network size

...how much knowledge is in the network


...the user’s:• background knowledge • and interest in energy policy

Are there complimentary benefits to different social tactics?

NETWORK ASKING

TARGETED ASKING

Results

NETWORK ASKING

TARGETED ASKING

Thinking beforeposTng quesTon

Thinking a'erreceiving replies

Results

60% OF USERS

29% OF USERS

0% OF USERS

100% OF USERS

NETWORK ASKING

TARGETED ASKING



TIME

TIME

Results

More thinking before posting questions on social networking sites

60% OF USERS

29% OF USERS

0% OF USERS

100% OF USERS

NETWORK ASKING

TARGETED ASKING



TIME

TIME

Results

More thinking after receiving replies sent from targeted friends

60% OF USERS

29% OF USERS

0% OF USERS

100% OF USERS

NETWORK ASKING

TARGETED ASKING



TIME

TIME

Results

Social networking sites: Thinking before posting to many

“Now, what could I say?”“Is this better phrased as two questions?”

“Let’s see...what do I really want to be asking?”

Social networking sites: Thinking before posting to many

Targeting friends: Thinking after getting replies from few


instant messenger

Pyro means...

email

Long reply...

“What are people’s average driving speeds anyway?”

“If ‘pyro’ means fire, then this might be a process to...”

“Given that, then I needto also know...”


instant messenger

Pyro means...

email

Long reply...

Nature of Replies

• short, conversa2onal• funny, not relevant

• long, detailed• focused, relevant

TARGETED ASKINGNETWORK ASKING

“Lots more waste sitting idly in traffic”

“Isn’t that something I rub on my [body]? Are you still in San Francisco?”

Nature of Replies




“Because no one drives the speed limit”

“Lots more waste sitting idly in traffic”

“Isn’t that something I rub on my [body]? Are you still in San Francisco?”

Nature of Replies




“There’s no one national speed limit, there are two: 55 miles per hour in general, 65 miles per hour for certain roads.”

“15-25% savings. But if those cars were electric, we’d have all those barrels left to use for something else.”

“Because no one drives the speed limit”

Network prediction

PREDICTED

probability of at least one

(relevant) reply

NETWORK SIZE

Network prediction

0

20

40

60

80

100

1 ... ... 450 ... ... 700 ... ... 1000

PREDICTED


(relevant) reply

NETWORK SIZE

Network prediction

0

20

40

60

80

100

1 ... ... 450 ... ... 700 ... ... 1000

OBSERVED

PREDICTED


(relevant) reply

NETWORK SIZE

Network prediction

0

20

40

60

80

100

1 ... ... 450 ... ... 700 ... ... 1000

OBSERVED

TARGETED ASKING NETWORK ASKING

How can we improve search with social networking technologies?

Design question:

Research Question

Theoretical orientation

“Inhabitedness”

“Inhabitedness”

Photo Credit: Niall Kennedy

Social Presence Theory

“A communicator’s sense of awareness of the presence of an interaction partner”

Short, Williams, & Christie 1976

Photo Credit: Carlo Nicora; George Duncan

ROBERT & DENNIS 2005

??

Inhabitedness

Photo Credit: Carlo Nicora; George Duncan, Sebastian Tauchmann,Guennadi Ivanov-Kuhn

Social Presence

Inhabitedness


Social Presence Structure of the Space

+

Inhabitedness


CARMONA, HEATH, OC, & TIESDELL 2003

Banks of the Seine, Paris A street cafe in Manchester, UK

Structure of the space

Banks of the Seine, Paris



A street cafe in Manchester, UK

Social Presence Structure of the Space+

Inhabitedness

nature of the relaTonship!e strength (e.g., strong !es, weak !es)

relaTve group membershipsocial network size

apparent idenTtypseudonym vs. real name

visibilityfrequency of updates

features of the channelmul!media content

the acTviTes supported“social objects”

• operaTonalize the model

• develop hypotheses about how inhabitedness predicts behaviors

• test our predicTons experimentally

Analytical

Methodological

Next Steps...

Conclusion

Photo Credit: David Wild

TARGETED ASKING

NETWORK ASKING

generic or “everyday”

difficult or failed

SEARCH STUDY

40%

61%

SOCIAL INTERACTIONS

Predicted

0

20

40

60

80

100

1 ... ... 450 ... ... 700 ... ... 1000

Observed

old models ??

“Inhabitedness”

Photo Credit: Niall Kennedy

Third year classKaya de BarbaroMatthew LeonardJosh LewisAnne Marie Piper

SupervisorDavid Kirsh

Outside Collaborators Ed H. ChiPeter PirolliSanjay KairamMichael MullerElizabeth Churchill

PARCPARCPARCIBM ResearchYahoo! Research

Friend Helpers!Chris MessinaSharoda PaulMichael Bernstein

Third year advisorAndrea Chiba

Thank you!!

Search as an ac2vity: • Searches are embedded in rich acTviTes that benefit from social interacTons with others, and from social communiTes online

Research Findings: • More thinking before asking quesTons to large social networks;• More thinking amer genng replies from targeted friends

Towards a theory: • Social presence theory alone doesn’t explain most social search behaviors

• Inhabitedness may explain some of these behaviors

• This is a rich area for future design work

Discussion

Photo Credit: Peter Lee

Do your friends make you smarter? Exploring social interactions in search

Technology

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