The document summarizes research on representing and evaluating social context on mobile devices. It describes related work using context-aware systems and experience sampling methods. It then outlines a study that used ontologies and a mobile prototype to model relationship types, mood, communication channels, and settings based on user-initiated and system-triggered surveys. The results showed that communicated content, relationship types, and mood are impacted by social contexts, and that experience sampling is suitable for studying social contexts, while semantic web ontologies are useful for representing complex contextual models.
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Representing and Evaluating Social Context on Mobile Devices
1. Divert: Mother-in-law
Representing and Evaluating
Social Context on Mobile Devices
Kris Mihalic
ICT&S Center, University of Salzburg, Austria
Manfred Tscheligi
ICT&S Center, University of Salzburg, Austria
2. Research on Context
• Context is a hot topic in HCI
– Context-aware systems, location-based services,
etc.
• Also an issue in other sciences
– E.g. social sciences: context in human
communication
• Lack of empirically based research
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
3. Related research
• ContextContacts
– Contextual cues about callees current situation
– Privacy management: what data can safely be
communicated; service control
– Oulasvirta / Raento / Tiitta (2005)
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
4. Related research
• Reality Mining
– Sampled context information over a longer period
of time on the users device
– Measurements of strength, dynamics and evolution
of social networks
– Eagle / Pentland, 2006
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
5. Related research
• Defined Delivery (DeDe)
– Allows sender of a message to define the context
or situation in which the message should be
delivered to recipient
– Field trial with socially tight group of seven
individuals for one month
– Sender must have good knowledge of recipient’s
activities and habits
– Jung / Persson / Blom (2005)
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
6. Related research
• Ethno-methodologically inspired study
observing people in their daily activities
• Results describe phenomena in mobility
– How situational and planned acts intermesh in
navigation
– How people construct personal and group spaces
– How temporal tensions develop and dissolve
• Tamminen et al. (2003)
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
7. Related research
• Focus group on usage of mobiles
– Students and field workers
– Phone as personal artifact
– Social constraints: importance of socially higher
persons
– Side-stepping: using phone during "free" times
– Mihalic / Tscheligi (2006)
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
8. Interactional Context
• Emerges through the interaction between users
by means of the device
• Associated with actions and events
• Comprises a variety of social factors
– Formality
– Mood
– Situation constraints
– etc.
• Research on interactional context still
underrepresented, but highly important with
mobiles
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
9. Objectives
1. Examine how social relationships can be
utilized in a mobile system in order to provide
a more appropriate service to the user
2. Represent a dynamic model of social context
in the system
3. Research on suitable methods for evaluating
social context in-situ
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
10. Approach
• Focus group on how people perceive social
relationships when using mobile phones
(Mihalic / Tscheligi 2006)
• Requirements
• Context-of-use model as ontology
• Prototypical implementation
• Evaluation in the field
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
11. Model
• Comprises
– Relationship type
– Mood
– Communication channel and content
– Settings
• Modeled as ontologies
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
13. Mood
• PANAS scheme
(Watson / Clark /
Tellegen 1988)
• Single list of choices
rather than semantic
differential scale
• Added 'neutral' item
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
16. Study design
• Eight participants for one week (including
weekend)
• Field workers: insurance agents, technicians and
installers, IT coordinators
• Aged between 26 and 51 (37 on average)
• All male
• Experienced mobile phone users
• User-initiated and system triggered sampling
– 8 notifications between 8:30am and 10:30pm
– Participants instructed to report on their own
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
17. ESM
• Experience Sampling Method (ESM)
– AKA beeper studies, time sampling
• Field study technique from psychology
• Used to understand
– Mood
– Social interactions
• Primary choice for understanding user in
context as well as context factors
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
18. ESM Overview
• Participants fill out questionnaire when alerted
– Researcher is not present
– Alerted several times per day
– Business as usual until alerted
– Triggered within users’ current context
• Duration usually 1-2 weeks
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
19. Prototype
• Conduct evaluation based on scenarios
• Supports ESM methodology
• Client part runs on a mobile phone
• Server part needed for “heavy-duty” work
– No Semantic Web technologies available for mobile
phones
– Porting of Semantic Web technologies to mobile
OS out of scope
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
21. Mobile client
• Implemented in Python
• Runs on Symbian Series 60 2nd Ed.
• Two modes
– User can answer questionnaire by herself
– Questionnaire is automatically initiated by the
Service (via SMS)
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
23. Backend service
• Implemented as Java Web-Application
• Runs on a J2EE compliant server (Tomcat)
• Uses Semantic Web framework (Jena)
• Uses OWL as ontology repository
• Provides (simple) web-based UI for
management and administration
• Communication to Mobile client via SMS
(gateway) and HTTP
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
25. Ontologies
• ESM ontology
– Describes the study, participants, questionnaires,
alerts and triggers, questions and answers
– Can be used for any study (with or without an user
ontology)
• User ontology
– Describes relations between the user and her
communication partners (e.g. phone book records)
– Is particular to this study
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
26. Results
• Mood
• Communication channels and content
• Recommended and overridden settings
• Methodology
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
28. Results: Mood
60% PA
16% NA
24% neutral
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
29. Results: Mood and relationships
Tighter social relationships and social activities
associated with higher PA? (Vittengl / Holt 1998; Clark /
Watson 1988)
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
31. Results: Methodology
P#6: "If the questionnaire comes immediately after the
call or SMS, and I get the call at midnight, then I would
respond!"
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
32. Results: User feedback
• Positive
– Use of prototype straightforward, would use for
longer period
– Users didn’t experience the system as obtrusive or
interrupting their tasks
• Negative
– Technical issues (data settings…)
– Skeptical about fully automated solution
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
33. In a nutshell
1. Communicated content and relationship types have an
impact on choosing the communication channels -
messaging for private, and voice for business; mood is
dependant on the kind of the relationship - positive mood
is associated with distant relationships
2. Semantic Web ontologies are suitable for representing
complex and dynamic information in a system, with a
lack of systems available on mobile platforms
3. ESM is appropriate for studying social context in-situ;
using a combination of event-based and time-based
sampling can provide higher user acceptance and better
results
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi
34. Acknowledgment
Parts of this work have been carried out under the FIT-IT
grant of the Austrian Federal Ministry for Transport,
Innovation and Technology, contract number 809272/9295.
MobileHCI 2007 Singapore Kris Mihalic, Manfred Tscheligi