Band on the Run: Connecting neighborhoods through live music

In this article we use machine learning to explore the ways that neighborhoods are connected by live music.

Topos
Topos
Feb 26, 2018 · 9 min read
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From Right Here to Everywhere

A musical scene can indelibly define a place. The specific culture of a neighborhood can give birth to a new sound. From New Orleans Jazz to DC Hardcore, Greenwich Village Folk to Queensbridge Hip Hop, musical scenes have been intertwined with the identity of geographic areas ranging from specific street intersections (Haight Ashbury) to entire metropolitan areas (Nashville).

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Left: The Grateful Dead at the corner of Haight and Ashbury (credit: Herbie Greene) — Right: Medieval troubadours painted by Simone Martini c. 1315 A.D.
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Left: Chicago Footwork in Japan (credit: John Calvert), Right: Vaporwave-A genre born on the internet (credit: Reddit)
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The jet set: Lady Gaga, Kendrick Lamar, Katy Perry
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Home/away or on the tour bus: The Radioactive Chicken Head, Bob Schneider, Sam Evian
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Hyper local: Andy Coe Band, Surprise Party, Just Another Folk Singer

A Model Built on Co-occurrence

Collaborative Filtering (CF) is one of the most widely used machine learning approaches for determining distance between entities. Once calculated, these distances are often used to power recommendations. From Spotify’s Discover Weekly to Amazon’s product recommendations, CF algorithms form an important part of many well known recommendation engines.

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Neighborhoods that co-occur frequently on tour schedules become closely connected

Exploration: Neighborhood Similarity

We start exploring our tour-based similarity metric by looking at three very different neighborhoods: Bushwick NYC, Downtown LA, and Maryvale, Phoenix

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Neighborhood similarities visualized in three dimensional space
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Acid Mothers Temple <<<->>> Acid Baby Jesus
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Popular Musical Acts: Acid Mothers Temple, John Maus, Ty Segall, Widowspeak, Acid Baby Jesus
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The Trans Siberian Orchestra — a band that has only ever played arenas
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Popular Musical Acts: Lady Gaga, Rihanna, Katy Perry,Justin Bieber, Trans-Siberian Orchestra
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Brad Paisley, Toby Keith, Mötley Crüe
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Popular Musical Acts: Brad Paisley, Toby Keith, Mötley Crüe, Slipknot, Journey

The Closest Connections

By allowing only the strongest links (>top .1 percentile) between neighborhoods to remain, we can observe some interesting neighborhood groupings. One striking aspect of these groups is their diversity: some are tightly connected geographically (Group 2) while others span the breadth of the country (Group 5); some have narrow genre preferences (Group 4) while others exhibit more eclectic tastes (Group 1).

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Network diagram of neighborhood clusters

Group 1: Pacific Northwest

Separated by 182 Miles, this small cluster of two neighborhoods spans a wide range of genres. Within this stylistic diversity, the most frequent acts tend to be older, established medium-popularity performers

Group 2: Insider NYC

Separated by just 4 Miles, this small cluster is the tightest geographically. Group 2 is also the most ‘local’, with 16 of the top 20 (mainly alt/indie) performers based in NYC.

Group 3: Almost Country

Largely comprised of western neighborhoods (with Tinley Park IL as the sole exception), group 3 has a corresponding passion for country music; half of the top ten acts are mainstream country musicians (Brad Paisley, Luke Bryan, Toby Keith, Zac Brown Band, Rascal Flatts). As in the earlier exploration of Maryvale, Mainstream metal and 70’s classic rock are also favorites.

Group 4: Central Downtown Areas

Connecting centrally located downtown areas, Group 4 is the most geographically dispersed. In contrast to this geographic diversity, Group 4 is tightly focused on a particular spectrum of sound — the pop-punk/emo/post-punk continuum (with some Comedic Metal — Steel Panther, Gwar — sprinkled in).

Group 5: Arena Haloes

Centered around huge stadiums (NYC’s Madison Square Garden, The Boston Garden, Chicago’s United Center) the neighborhoods in Group 5 are visited by arena-filling superstars like Bon Jovi, Kanye West, and of course, Billy Joel whose monthly MSG residency (and accompanying helicopter commute) has become legendary.

Recommendations

Similarity metrics are often constructed in order to power recommendation engines. And where Spotify might recommend an album or Netflix might suggest a movie, here we give examples of using our similarity metric to recommend venues and neighborhoods for touring musicians, focusing on locations where the musician rarely, if ever, performs. For each act, we also produce a list of similar musicians based on their touring schedules.

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From Nodes to Edges

In this article, we’ve constructed a narrow, highly specific view of place, ignoring myriad factors that shape neighborhoods. While there is a small but statistically significant correlation between the similarity metric constructed here and the Topos Similarity Index (which increases for certain cities), these measures are largely orthogonal. The TSI is a holistic measure of similarity, encompassing everything from the form of the built environment to the ratio of big box stores to local retailers, while here we have worked with a single data source pertaining to one facet of culture.

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Tour Based Similarity vs the Topos Similarity Index for Boston <> US. Pearson Correlation of .249, p <<.05

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