The popularity of micro-blogging has made general-purpose information sharing a pervasive phenomenon. This trend is now impacting location sharing applications (LSAs) such that users are sharing their location data with a much wider and more diverse audience. In this paper, we describe this as social-driven sharing, distinguishing it from past examples of what we refer to as purpose-driven location sharing. We explore the differences between these two types of sharing by conducting a comparative two-week study with nine participants. We found significant differences in terms of users' decisions about what location information to share, their privacy concerns, and how privacy-preserving their disclosures were. Based on these results, we provide design implications for future LSAs. Authors are Karen Tang, Jialiu Lin, Jason Hong, and Norman Sadeh

1. Rethinking Location Sharing: Exploring
the Implications of Social-Driven vs.
Purpose-Driven Location Sharing
Karen P. Tang
Jialiu Lin, Jason Hong, Dan Siewiorek, Norman Sadeh
Human-Computer Interaction Institute
School of Computer Science
Carnegie Mellon University

2. Location-Based Services Are Here
2

3. Types of Location-Based Services
tracking personal trends (no sharing)
doing local searches (sharing with a service provider)
3
[google latitude] [yelp]

4. Location Sharing Applications (LSAs)
tracking personal trends (no sharing)
doing local searches (sharing with a service provider)
share locations with other people(a social network)
4

5. activecampus
[griswold, ’03]
lemming
[hong, ’04]
Past Research Examples of LSAs
5
2003 2004 2005 20082007 2009
esm study
[consolvo, ’05]
reno
[smith, ’05]
whereabouts
[brown, ’07]
watchme
[marmasse, ’04]
contextcontacts
[raento, ’05]
connecto
[barkhuus, ’08]
locaccino
[sadeh, ’09]
1992
active badge
[want, ’92]

6. activecampus
[griswold, ’03]
lemming
[hong, ’04]
Past Research Examples of LSAs
6
2003 2004 2005 20082007 2009
esm study
[consolvo, ’05]
reno
[smith, ’05]
whereabouts
[brown, ’07]
watchme
[marmasse, ’04]
contextcontacts
[raento, ’05]
connecto
[barkhuus, ’08]
locaccino
[sadeh, ’09]
1992
active badge
[want, ’92]
The most common use of the system was by the receptionist
who routinely used it when forwarding telephone calls from
the main switchboard.
Groups of people who regularly wanted to hold meetings
could find each other easily with very little notice.
“

7. activecampus
[griswold, ’03]
lemming
[hong, ’04]
Past Research Examples of LSAs
7
2003 2004 2005 20082007 2009
esm study
[consolvo, ’05]
reno
[smith, ’05]
whereabouts
[brown, ’07]
watchme
[marmasse, ’04]
contextcontacts
[raento, ’05]
connecto
[barkhuus, ’08]
locaccino
[sadeh, ’09]
1992
active badge
[want, ’92]
Given mobile users’ fragmented attention, the time it takes
to make a phone call must remain extremely short…These
[context] cues [which include location] should facilitate
decisions about whether to call, and if so, which
communication channel to use.
“

8. activecampus
[griswold, ’03]
lemming
[hong, ’04]
Past Research Examples of LSAs
8
2003 2004 2005 20082007 2009
esm study
[consolvo, ’05]
reno
[smith, ’05]
whereabouts
[brown, ’07]
watchme
[marmasse, ’04]
contextcontacts
[raento, ’05]
connecto
[barkhuus, ’08]
locaccino
[sadeh, ’09]
1992
active badge
[want, ’92]
Phoebe wonders what she and her husband, Ross, will do
for the evening, so she sends a location query to Ross. While
he is waiting at the bus stop near his office, Ross sends a
location update to Phoebe. Phoebe receives the message at
home, eagerly anticipating Ross’ arrival home. When Ross
gets off the bus, a location update is sent to Phoebe and she
knows that he’s only 10 minutes away. She sets out dinner
just in time for her husband’s arrival.
“

9. Common Themes for Past LSAs
driven by functional purposes:
• coordination
• collaboration
• interruptibility
• event planning
one-to-one sharing or small group sharing
9

10. Industry Trends for Information Sharing
integrated with online social networks (OSNs)
• diverse networks, lots of weak links [wellman, ‘01]
• very large networks [donah, ‘04]
sharing is often not because one needs to
share, but because one wants to share
driven by a social reason for sharing
10

11. Commercial Examples of LSAs
mostly aimed at social-driven sharing
11
2005 2006 2009 20102007 2008

12. Commercial Examples of LSAs
mostly aimed at social-driven sharing
12
2005 2006 2009 20102007 2008
“I'm just down the street!” Never miss another
chance to connect when you happen to be at the
same place at the same time. [facebook places]
Find out who’s around, what to do, and where to
go. Introducing…the new Loopt so you can always
stay connected… [loopt]
Share your location and stay connected with your
friends. [plazes]
“
“
“

13. Reframing Location Sharing
Purpose-Driven Social-Driven
motivations
coordination, collaboration,
interruptibility, planning
want (vs. need) to share,
social awareness
features
one-to-one
close-knit relationships
one-to-many
diverse relationship types
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14. Understanding the Differences
Q1: what are people sharing?
will social-driven sharing lead to different sharing decisions?
Q2: how are making their sharing decisions?
what privacy strategies are used in social-driven sharing?
Q3: are people making good choices?
do people’s preferences result in privacy-preserving choices?
14

15. User Study: Participants
2-week user study
9 participants, 3 female
18-46 years old (μ=27.1, σ=8.3)
⅔ undergrad & grad students, ⅓ staff
15

16. User Study: Part 1 (in the field)
participants given custom Nokia N95s
• treated as primary phone
collected continuous GPS traces
extracted significant places
• dwell time ≥ 5 mins
16

17. User Study: Part 2 (in the lab)
1. shown a map of each place
2. generate as many labels as possible
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[sample labeling exercise given to everyone as training]
Heinz Field
Football field
Steelers vs. Bengals
downtown Pittsburgh
Steelers’ home
100 Art Rooney Ave
Near golden triangle

18. User Study: Part 2 (in the lab)
purpose-driven scenario:
social-driven scenario:
18

19. User Study: Part 2 (in the lab)
purpose-driven scenario:
social-driven scenario:
19

20. Analysis: Taxonomy
coded each label:
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Heinz Field
Football field
Steelers vs Bengals
downtown Pittsburgh
Steelers’ home
100 Art Rooney Ave
Near golden triangle

21. Analysis: Taxonomy
coded each label:
21
Heinz Field
Football field
Steelers vs Bengals
downtown Pittsburgh
Steelers’ home
100 Art Rooney Ave
Near golden triangle
type of description example
geographic
100 Art Rooney Ave
Near Golden Triangle
Downtown
Pittsburgh
semantic
Heinz Field
Steelers vs. Bengals
Steelers’ home
Football field
hybrid Heinz Field @ downtown

22. Q1: What Do Users Share? [semantic]
social sharing preferences:
• more semantic labels*
• fewer hybrid labels**
social sharing had different semantic labels**
• prefer activity & personal labels (“home”, “work”)
• purpose-driven sharing preferred type of place
& business names (“coffee shop”, “Starbucks”)
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*p<0.01
**p<0.005

23. Q2: How Do Users Decide? [blurring]
insider knowledge
“If I just say Giant Eagle [a regional grocery store chain],
my friends will know which one I’m at.”
sharing activity vs. location
“I’d rather say what I am doing than that I’m at a certain
place.”
protecting friends’ locations
“I’m uncomfortable sharing where I am at, since it’s
someone else's place.”
23

24. Q2: How Do Users Share? [blurring intent]
purpose-driven: used to convey unavailability
social-driven: used to explicitly hide location
24

25. Q2: How Do Users Share? [blurring intent]
purpose-driven: used to convey unavailability
social-driven: used to explicitly hide location
…but also considered:
• social capital & image management
• what would appear more interesting to others?
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26. Q3: Do Users Make Good Choices?
examine 3 techniques for reverse engineering
• google maps
• google search + google maps
• routines + google search + google maps
“bad” choice = physically locatable (stalker threat)
26

27. Result: Leaky Privacy Decisions
purpose-driven: easily locatable
social-driven: susceptible to being located
27
resource(s) purpose-driven social-driven
map 50.0% 10.2%
map + web 62.3% 19.4%
map + web +
routines
90.8% 51.0%

28. Summary & Conclusions
reframing: purpose- vs. social-driven sharing
significant differences for social sharing:
• what: different types of disclosures [semantic]
• how: different intentions for blurring [to hide]
• how: considered social issues [impressions]
• actual privacy: still susceptible to attacks
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29. Summary & Conclusions
reframing: purpose- vs. social-driven sharing
significant differences for social sharing:
• what: different types of disclosures [semantic]
• how: different intentions for blurring [to hide]
• how: considered social issues [impressions]
• actual privacy: still susceptible to attacks
 context for sharing is an important factor
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30. Limitations & Future Work
hypothetical disclosure scenarios
small, homogenous participant pool
• predominantly college students
• already familiar social network users
comparing two extremes of location sharing
• many other types of possible location sharing
• one-to-one vs. one-to-many purpose-driven
• one-to-many vs. one-to-one social-driven
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31. Questions?
Karen P. Tang
Human-Computer Interaction Institute
School of Computer Science
Carnegie Mellon University
kptang@cs.cmu.edu
This research has been supported in part by the National Science
Foundation under grants CNS-0627513, IIS-0534406, and ITR-032535, by
the CyLab at Carnegie Mellon University under grants DAAD19-02-1-0389
from the Army Research Office, by Nokia, by Portugal ICTI, and by a
Microsoft Computational Thinking grant.
31