Post on 12-Apr-2017
Active Mobile Music Discovery with Social Tags
Torsten Möller
IUI 2016 March 2016, Sonoma, CA
Mohsen Kamalzadeh
Christoph Kralj Michael Sedlmair
TagFlip
motivation design evaluation conclusion
• online streaming services
• over 30 millions songs
• need 200 years to listen to everything!
• how to narrow down?
2
motivation design evaluation conclusion
play something nice for a while
exploration and discovery
3
how to narrow down?
motivation design evaluation conclusion
play something nice for a while
exploration and discovery
4
• radio stations • curated playlists • recommendation
how to narrow down?
motivation design evaluation conclusion
play something nice for a while
exploration and discovery
5
• radio stations • curated playlists • recommendation
• library visualization
• critiquing, weighting, etc.
how to narrow down?
motivation design evaluation conclusion
?6
play something nice for a while
• radio stations • curated playlists • recommendation
exploration and discovery
• library visualization
• critiquing, weighting, etc.
motivation design evaluation conclusion
?7
play something nice for a while
• radio stations • curated playlists • recommendation
exploration and discovery
• library visualization
• critiquing, weighting, etc.
• not much control • black box
problem • pigeon-holing
motivation design evaluation conclusion
?8
play something nice for a while
• radio stations • curated playlists • recommendation
exploration and discovery
• library visualization
• critiquing, weighting, etc.
• not much control • black box
problem • pigeon-holing
• elaborate interfaces
• large screens • for long sessions
motivation design evaluation conclusion
• elaborate interfaces
• large screens • for long sessions
?9
play something nice for a while
• radio stations • curated playlists • recommendation
exploration and discovery
• library visualization
• critiquing, weighting, etc.
• not much control • black box
problem • pigeon-holing
Pu and Chen, 2006
motivation design evaluation conclusion
• elaborate interfaces
• large screens • for long sessions
?10
play something nice for a while
• radio stations • curated playlists • recommendation
exploration and discovery
• library visualization
• critiquing, weighting, etc.
• not much control • black box
problem • pigeon-holing
Pampalk and Goto, 2007
motivation design evaluation conclusion
• elaborate interfaces
• large screens • for long sessions
?11
play something nice for a while
• radio stations • curated playlists • recommendation
exploration and discovery
• library visualization
• critiquing, weighting, etc.
• not much control • black box
problem • pigeon-holing
O’Donovan et al., 2008
motivation design evaluation conclusion
• elaborate interfaces
• large screens • for long sessions
?12
play something nice for a while
• radio stations • curated playlists • recommendation
exploration and discovery
• library visualization
• critiquing, weighting, etc.
• not much control • black box
problem • pigeon-holing
Bostandjiev et al., 2012
motivation design evaluation conclusion
?13
play something nice for a while
• radio stations • curated playlists • recommendation
exploration and discovery
• library visualization
• critiquing, weighting, etc.
• not much control • black box
problem • pigeon-holing
• elaborate interfaces
• large screens • for long sessions
motivation design evaluation conclusion
14
play something nice for a while
• radio stations • curated playlists • recommendation
exploration and discovery
• library visualization
• critiquing, weighting, etc.
• not much control • black box
problem • pigeon-holing
TagFlip
?
• elaborate interfaces
• large screens • for long sessions
motivation design evaluation conclusion
15
TagFlip
high user control +
low interaction effort +
small screen
motivation design evaluation conclusion
TagFlip
Contributions:
• Design and evaluation of a tag-based interactive recommendation interface
• Design choices, lessons, and future directions
• Strengths of tag-based discovery
16
motivation design evaluation conclusion
17
Design
motivation design evaluation conclusion
• High level abstraction over music library • Understandable to ordinary users • Navigate based on social tags
• genre • mood • location • year • instruments • etc.
• 100,000 songs • 350 tags (processed from 500,000) • Android
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TagFlip
motivation design evaluation conclusion
19
motivation design evaluation conclusion
20
• High impact interaction • Fine tuning/precise control • Low interaction effort and mental load • Transparency • Small screen
key design factors
motivation design evaluation conclusion
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• left to right flow
design choices
Iterative user-centred design
motivation design evaluation conclusion
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• left to right flow
design choices
Iterative user-centred design
motivation design evaluation conclusion
23
• left to right flow • tag strength
design choices
Iterative user-centred design
motivation design evaluation conclusion
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• left to right flow • tag strength
design choices
Iterative user-centred design
motivation design evaluation conclusion
25
• left to right flow • tag strength • communicating target set sizes
design choices
Iterative user-centred design
motivation design evaluation conclusion
26
• left to right flow • tag strength • communicating target set sizes • “excluding” tags
design choices
Iterative user-centred design
motivation design evaluation conclusion
27
Evaluation
motivation design evaluation conclusion
• Is there room for this type of interface? • compared with Spotify’s mobile app • within subjects • 16 users (8 female), median age = 26
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Evaluation
motivation design evaluation conclusion
29
• with each app: - alternating order of apps - 5 minutes familiarization - 10 minutes test
- find new songs that you like - use any feature of apps
- usability and recommendation questionnaires
• post-hoc interview
Protocol
motivation design evaluation conclusion
30
questionnaires video captureinterview
evaluation data
motivation design evaluation conclusion
31
questionnaires video captureinterview
evaluation data
• Usability - SUS questionnaire
• Recommendation • Based on ResQue
framework (Pu and Chen, RecSys 2010)
motivation design evaluation conclusion
32
video captureinterview
evaluation data
• Usability - SUS questionnaire
• Recommendation • Based on ResQue
framework (Pu and Chen, RecSys 2010)
questionnaires
• Pros and cons of each app
motivation design evaluation conclusion
33
video capture
evaluation data
• Objective performance
interview
• Pros and cons of each app
• Usability - SUS questionnaire
• Recommendation • Based on ResQue
framework (Pu and Chen, RecSys 2010)
questionnaires
motivation design evaluation conclusion
34
Hypotheses
• H1: Higher overall score for TagFlip in rec. questionnaire
• H2: Smaller number of interactions per liked song in TagFlip
• H3: More liked songs with TagFlip
questionnaires video captureinterview
evaluation data
motivation design evaluation conclusion
1.Quality of recommendations
35
questionnaires
• Usability
• Recommendation
video captureinterview
2.Interface and interaction adequacy
3.Control and transparency
4.Attitudes and behavioural intentions (trust)
motivation design evaluation conclusion
0 1 2 3 4
2.67
2.26
2.33
2.29
2.51
3.03
2.83
2.72
2.48
3.03
TagFlip Spotify
36
questionnaires
2. Interface and interaction adequacy
1.Quality of recommendations
3.Control and transparency
4.Attitudes and behavioural intentions (trust)
scores from 0 to 4
video captureinterview
p values form paired sample t-test
questionnaires
• Usability
• Recommendationp<0.05
statistically significant*
All questions
p<0.05
p<0.05
p<0.05
motivation design evaluation conclusion
0 1 2 3 4
2.67
2.26
2.33
2.29
2.51
3.03
2.83
2.72
2.48
3.03
TagFlip Spotify
37
questionnaires
2. Interface and interaction adequacy
1.Quality of recommendations
3.Control and transparency
4.Attitudes and behavioural intentions (trust)
scores from 0 to 4
video captureinterview
• TagFlip sig. higher in • overall subjective recommendation capability
(Hypothesis 1 confirmed)
p values form paired sample t-test
questionnaires
• Usability
• Recommendationp<0.05
statistically significant*
All questions
p<0.05
p<0.05
p<0.05
motivation design evaluation conclusion
38
video capture
interview
• Objective performance
10 20 30 40
34.58
25.61interactions per liked
song
2 4 6 8 10
7.06
7number of liked songs
questionnaires
p<0.05
motivation design evaluation conclusion
39
video capture
interview
• Objective performance
10 20 30 40
34.58
25.61interactions per liked
song
2 4 6 8 10
7.06
7number of liked songs
questionnaires
p<0.05
• TagFlip needed sig. less interaction (H2 confirmed)
• Equal number of liked songs (H3 not confirmed
motivation design evaluation conclusion
video capture
interview
40
• pros: • precise control (all 16
participants) • fine-tuning (11)
• cons: • Spotify better for passive
listening (8)
• 7 participants very enthusiastic • 7 other participants open to using
questionnaires
motivation design evaluation conclusion
video capturequestionnaires interview
• Higher overall satisfaction with TagFlip
• High user control with TagFlip
• Lower interaction effort with TagFlip
• Fine-tuning ability is key in user enthusiasm
41
motivation design evaluation conclusion
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Conclusion
motivation design evaluation conclusion
43
• stagnant mobile recommendation scene
• encouraging results with TagFlip
• great potential for tag-based interaction
Conclusion
motivation design evaluation conclusion
44
• design solutions to remaining problems
• excluding tags, tag strength, etc.
• longitudinal studies
• more advanced processing
• excluding music types?
• topic modelling
Future work
motivation design evaluation conclusion
45
Thank you!