TagFlip: Active Mobile Music Discovery with Social Tags

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


play something nice for a while

exploration and discovery

3

how to narrow down?




4

• radio stations • curated playlists • recommendation

how to narrow down?




5


• library visualization

• critiquing, weighting, etc.

how to narrow down?


?6







?7






• not much control • black box

problem • pigeon-holing


?8








• elaborate interfaces

• large screens • for long sessions




?9








Pu and Chen, 2006




?10








Pampalk and Goto, 2007




?11








O’Donovan et al., 2008




?12








Bostandjiev et al., 2012


?13











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TagFlip

?




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TagFlip

high user control +

low interaction effort +

small screen


TagFlip

Contributions:

• Design and evaluation of a tag-based interactive recommendation interface

• Design choices, lessons, and future directions

• Strengths of tag-based discovery

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Design


• 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


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• High impact interaction • Fine tuning/precise control • Low interaction effort and mental load • Transparency • Small screen

key design factors


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• left to right flow

design choices

Iterative user-centred design


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• left to right flow

design choices



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• left to right flow • tag strength

design choices



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• left to right flow • tag strength

design choices



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

design choices



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• left to right flow • tag strength • communicating target set sizes • “excluding” tags

design choices



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Evaluation


• 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


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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


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questionnaires video captureinterview

evaluation data


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evaluation data

• Usability - SUS questionnaire

• Recommendation • Based on ResQue

framework (Pu and Chen, RecSys 2010)


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video captureinterview

evaluation data




questionnaires

• Pros and cons of each app


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video capture

evaluation data

• Objective performance

interview

• Pros and cons of each app




questionnaires


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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


evaluation data


1.Quality of recommendations

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questionnaires

• Usability

• Recommendation


2.Interface and interaction adequacy

3.Control and transparency

4.Attitudes and behavioural intentions (trust)


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

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questionnaires

2. Interface and interaction adequacy




scores from 0 to 4


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


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

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questionnaires

2. Interface and interaction adequacy




scores from 0 to 4


• 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


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video capture

interview


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


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video capture

interview


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


video capture

interview

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• 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


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

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Conclusion


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• stagnant mobile recommendation scene

• encouraging results with TagFlip

• great potential for tag-based interaction

Conclusion


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• design solutions to remaining problems

• excluding tags, tag strength, etc.

• longitudinal studies

• more advanced processing

• excluding music types?

• topic modelling

Future work


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Thank you!

TagFlip: Active Mobile Music Discovery with Social Tags

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