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

18

TagFlip

motivation design evaluation conclusion

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motivation design evaluation conclusion

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• 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

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• 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

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• left to right flow • tag strength • communicating target set sizes

design choices

Iterative user-centred design

motivation design evaluation conclusion

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• 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

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• 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

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questionnaires video captureinterview

evaluation data

motivation design evaluation conclusion

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questionnaires video captureinterview

evaluation data

• Usability - SUS questionnaire

• Recommendation • Based on ResQue

framework (Pu and Chen, RecSys 2010)

motivation design evaluation conclusion

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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

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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

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• 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!