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Social Interaction Taxonomy Classifies User Tasks
1. Institute of Systems Engineering – System- and Computer Architecture
A Social Interaction Taxonomy:
Classifying User Interaction Tasks in Web Applications
Institute of Systems Engineering
System- and Computer Architecture (SRA)
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2. Institute of Systems Engineering – System- and Computer Architecture
Outline
Introduction
User interaction in web applications,
Social Interaction Cloud,
Cloud
Classification of user interaction.
Social Interaction T
S i lI t ti Taxonomy (SIT)
Use case: Squirl Online Community
q y
Global Interaction (Meta) Rewarding Community based on SIT
Evaluation setting and results:
Impact of rewarding mechanisms on user behavior
Summary and outlook
S d tl k
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Introduction: user interaction in web applications
Overall aim of this contribution:
meta rewarding system to reward users for any kind of interaction,
community and application independent
independent,
aiming at an extensible meta rewarding model.
Therefore, interactions available i web applications (
Th f i t ti il bl in b li ti (social
i l
networks) need to be classified, aggregated and assigned with
incentive/rewards.
Which kind of interaction tasks are there in web applications?
How to classify and order interactions in a preferably generic and
extensible way?
t ibl ?
A taxonomy would be suitable to describe the properties of and
relations be ee interaction tasks in a s uc u ed way.
e a o s between e ac o as s structured ay
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Introduction: Social Interaction Cloud
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Users and resources
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Social Interaction Taxonomy
(SIT)
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Points assigned to interactions
as basic reward measurement
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Level types and aggregated interactions
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Ontology GIAR.rdf
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GIAR Config xml file
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Use case:
Global Interaction Rewarding Community Squirrl
Tasks that are
rewarded in Squirl
so far (exemplary):
Last.fm
favorites
listening
Flickr
upload
tagging
Facebook
F b k
adding friends
login in.
We will extend it
by and by.
Mashup of all
popular
communities.
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Squirl user stats
Very important for
users‘ motivation to
g
give feedback and to
visualize their
progress.
Competition wih
other users
becomes possible.
Levels, points,
medals, badges,
medals badges
highscores, …
only virtual rewards
so far
far.
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Evaluation:
Impact of rewarding mechanisms on user behavior
We developed an example web application aiming at tag
assessment in folksonomies like Flickr
Flickr.
Users have to rank photo tags in Flickr according to their
relevance
l
Which tags are best matching according to the shown image?
Are there wrong or missing tags?
Rewarding the following interaction tasks:
Rank: for each tag ranked
Tag: for each tag added
Rate: for each photo title rated
Explore: for each photo rewarding version or non rewarding version
non-rewarding
explored.
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Setting: rewarding and non-rewarding test application
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Evaluation result
12,958 interactions executed by participants from both groups,
obviously rewarding mechanisms have enormous effect on user motivation,
90% of all interactions executed by participants from the group that used the rewarding
version,
every title of every explored picture has been rated by group 1, whereas group 2 only
rated every fourth photo title, ranking activity increases with rewarding,
Rewarding mechanisms do not only result in more interactions, but also in more regularity
as users who are rewarded for activities tend to do more and are more consistent in the
activity than users, who are not rewarded.
Important for users to compare themselves socially with others and keep track of their
progression.
50 % of all requested Squirrl statistics have been requests for leaderboards that enable
social comparison ,
30% of all stats requests have been requests for level progressions, which enable users
to keep track of their evolution.
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Evaluation results, rewarded versus not rewarded
interaction
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Interactions per day of group 1 and group 2
(with and without rewards) during the evaluation period
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Conclusion and outook
Rewarding mechanisms that are adapted out of game design influence a user’s
motivation to activity and participation in web applications in a positive way.
With SIT and the Global Interaction Rewarding model (GIAR), we offer a generic
and application independent solution for a meta rewarding system of users
activity in web application – especially social media applications and networks.
Example Global Interaction Rewarding Community Squirrl as meta mashup and
rewarding:
ongoing development,
beta release planned this year.
Mashup has to be t d d by d by
M h h t b extended b and b
Twitter for micro blogging,
Dailymile for sports
Blip.fm for more music
p
Soup.io for posting, sharing and reacting,
…
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Sources
N. Ullmann, “Design and implementation of a global rewarding model
based on user interaction tasks”, master thesis, Leibniz Universität
Hannover,
Hannover System and Computer Architecture, 2010
Architecture 2010.
M. Steinberg, N. Ullmann, J. Brehm
g
“A Social Interaction Taxonomy: Classifying User Interaction Tasks in
Web Applications”
In: DigitalWorld 2011, Proc. International Conference on Mobile, Hybrid,
and On-line Learning, eLmL, 2011.
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Thank you very much
for your attention!
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