This thread is a companion to Statistics in ListenBrainz and the GSoC 2017 proposal. However, this proposal focuses on what statistics to collect over the technical implementation.
You can leave comments in this Google Docs page too!
Implement new statistics to calculate insightful data on the listens submitted to ListenBrainz, to make the platform more competitive to other solutions and more interesting to the user
Currently, ListenBrainz collects two types of statistics:
ListenBrainz calculates a single statistic for the entire site:
- Total number of artists submitted by all users
ListenBrainz calculates the following statistics for users:
- Top recordings over a time interval
- Top artists over a time interval
- Top releases over a time interval
- Number of artists listened to over a time interval
ListenBrainz does not yet collect many statistics. In the future, this will become an important focus for the platform to compete with other proprietary services and provide insightful information to the user.
Two types of statistics were gathered for this proposal. Some are already implemented on other third-party sites, such as Last.fm, and others are new ideas that are not implemented by other competing, proprietary services.
Note that “entities” refers to artists, releases, and recordings.
Ideas for new statistics from third-party sites include…
Time spent listening: Total time spent listening to music over a time period
User percentiles for entities: Compare your listens for different entities compared to other users on the site (e.g. 80th percentile for number of artists listened to in a time period)
Top tags from entities: See patterns in tags from listens (i.e. pulling tags from MusicBrainz entities)
Listening clock: See when a user listened to the most music at what time of day over a time period
New discoveries: Highlight new entities that a user has not listened to before
Musical matches: See other users who listened to similar entities as you
Mainstream meter: Percentage of how many other users shared your listens
Example: If every user on the site listened to one artist, and a user only listened to that artist over a time period, their “mainstream meter” score would be 100%
New statistic ideas not yet implemented by a competing service include…
Revivals: Highlight when a user listens to an entity that they haven’t listened to since a period of time
Streaks: Entities that consistently appear in listens in a measure of time
Example: User listens to the same artist every week for six weeks
“Love at first sight”: New listens for entities that are over a certain threshold
Example: User listens to a recording for the first time, and over a week, they play that recording over 100 times
“Where did you listen?”: Highlight what client a user submitted listens from
- Listens do not currently collect client identifier (I don’t think)
This proposal maps ideas for new statistics and provides a chance to consider a long-term approach to how new statistics are added to ListenBrainz. Feedback is welcome, and a concrete action for where these suggestions should go is needed (new tickets?).