Evaluating MoodPic - a Concept for Collaborative Mood Music Playlist Creation

This paper studies a MoodPic concept and a prototype implementation enabling collaborative creation of mood picture based musical play lists, evaluated qualitatively with 30 Finnish participants. In general, MoodPic was found to be a successful concept and stated to add novel experiences to music listening. Accessing music through mood pictures was highly appreciated and seen as a good way to discover new music over the genre boundaries and receive music recommendations from real users based on their mood picture interpretation. Sorting music based on mood pictures instead of genres was seen as an interesting and easy way to interact with music. Based on the interview results, this paper introduces several ideas for further improving the music listening experience using mood pictures as a basis for play lists. This paper summarizes the main findings and proposes an extensive set of generalized design implications to take into account when designing solutions for social music discovery.

[1]  Frank Bentley,et al.  Personal vs. commercial content: the similarities between consumer use of photos and music , 2006, CHI.

[2]  In-Kwon Lee,et al.  Generating affective music icons in the emotion plane , 2009, CHI Extended Abstracts.

[3]  Ichiro Fujinaga,et al.  Musical genre classification: Is it worth pursuing and how can it be improved? , 2006, ISMIR.

[4]  J. Sloboda,et al.  Music and emotion: Theory and research , 2001 .

[5]  David W. McDonald,et al.  Musical fingerprints: collaboration around home media collections , 2009, GROUP '09.

[6]  Nina Reeves,et al.  An ethnographic study of music information seeking: implications for the design of a music digital library , 2003, 2003 Joint Conference on Digital Libraries, 2003. Proceedings..

[7]  Stefanie Nowak,et al.  Content-based mood classification for photos and music: a generic multi-modal classification framework and evaluation approach , 2008, MIR '08.

[8]  Nicholas J. Belkin,et al.  Categories of Music Description and Search Terms and Phrases Used by Non-Music Experts , 2002, ISMIR.

[9]  Michael Burmester,et al.  Hedonic and ergonomic quality aspects determine a software's appeal , 2000, CHI.

[10]  Jukka Holm,et al.  Associating Emoticons with Musical Genres , 2010, NIME.

[11]  J. Russell.  A circumplex model of affect. , 1980 .

[12]  Arto Lehtiniemi.  Evaluating SuperMusic: streaming context-aware mobile music service , 2008, ACE '08.

[13]  Abigail Sellen,et al.  The Use of Conventional and New Music Media: Implications for Future Technologies , 2001, INTERACT.

[14]  K. R. Priya.  Grounded Theory Methodology , 2013 .

[15]  Jukka Holm,et al.  Using Animated Mood Pictures in Music Recommendation , 2012, 2012 16th International Conference on Information Visualisation.

[16]  D. Rennie.  Grounded Theory Methodology , 1998 .

[17]  Jeffrey J. Scott,et al.  MUSIC EMOTION RECOGNITION: A STATE OF THE ART REVIEW , 2010 .

[18]  Masataka Goto,et al.  Musicream: New Music Playback Interface for Streaming, Sticking, Sorting, and Recalling Musical Pieces , 2005, ISMIR.

[19]  Mark W. Newman,et al.  Listening in: practices surrounding iTunes music sharing , 2005, CHI.

[20]  Youngmoo E. Kim,et al.  MoodSwings: A Collaborative Game for Music Mood Label Collection , 2008, ISMIR.