The document discusses how network analysis can be used to analyze success in the rap music industry. It examines how an artist's crew, city, and collaborations may impact their popularity and technical skills. Key measures explored include centrality, top albums/songs, influence, and technical expertise. Regression analysis is used to determine if collaborating with popular or influential artists correlates with higher success rates in subsequent years. The network analysis seeks to identify influential artists, promising regional scenes, and how technical rapping ability relates to an artist's position in the network.

1. Rap Network Analysis
How does your crew and your city affect your success in the rap music industry?

2. “
Crew love is one of the core
tenets of hip-hop…
And the camaraderie of MCs from the same neighborhood or city, or simply the
same label, often gives fans something to rally around that’s bigger and more
meaningful than any one individual.”
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3. A Few Crews You May Know
YMCMB
Lil Wayne, Tyga, (formerly
Drake and Nicki Minaj)
G.O.O.D. Music
Kanye, Pusha T, Big Sean
A$AP Mob
A$AP Rocky, A$AP Ferg,
A$AP Yams, A$AP Twelvyy
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4. How do individual
rappers’ networks
affect their
success?
1. Centrality
2. Top album/song list
3. Influence
4. Technical Expertise
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5. Collaborations (2016)
Edge list of rappers who did songs together
in 2016, and how many songs they
collaborated on
Data Set
Technical Ability
Data sets that describe rhyming ability on a
scale and level of vocabulary
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Top 100 Albums/Song (2016)
A list of all the rap albums/songs that made it to
Billboard Top 100 Albums at one point in 2016
Activity
Location and years active for
each rapper

6. 1. Centrality

7. Artists Tend to Collaborate Within Their Own City
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8. Artists Tend to Collaborate Within Their Own City
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9. Artists with Top Centrality Measures
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Degree Betweenness Closeness
1 The Game E-40 ScHoolboy Q
2 E-40 Mistah F.A.B Mistah F.A.B.
3 Ty Dolla $ign Ty Dolla $ign E-40
4 Wiz Khalifa A$AP Rocky Jadakiss

10. Use Cases
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1. Identify what binds the artists: Are artists from the same city more connected to each
other? Or are more famous artists more connected?
2. Identify budding regions: What are the new areas where artists can be found
3. Identify who is the most connected: This will determine who is producing the most,
with the widest variety of people, touching the widest range of consumers

11. 2. Top albums/songs

12. How do centralities affect probabilities of making to the Top Billboard List?
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13. Use Cases
1. Relationship between centrality and sales: Does centrality correlate with an
artist’ ability to produce a top song or album?
2. Identify who is topping the charts: Do different connections or city circles
affect how well an artist’s song or album performs on the charts?
3. Discover who is worth collaborating with: Use these centralities as input for
our model to predict whether the next artist candidate to collaborate with?
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14. 3. More Regression on Influence

15. We First Define Popularity of Rappers
1. Define Popularity for rappers: We define popularity the time a rapper made
it to the Billboard because of his/her hit song.
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16. Plot w.r.t. Popularity
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17. We then Regress Popularity on Success
1. Discover the importance of collaborating with popular artists: If a rapper
who is less popular collaborates with an artist who is more popular in 2016,
are they more likely to have a popular top album or song in 2017 or 2018?
Does the collaboration with top producers has a long-lasting effect on the
future status of the less popular rapper?
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18. We Then Define Status Relationship
1. Define status relationship for artists: We can define a status relationship for
a pair of rappers A -> B as the proportion of times that rapper A has served as
a lead rapper in albums it has participated in with rapper B:
2. statusAB = count(deals with B in which A is lead)/total deals with B
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19. We Calculate Status Based on Eigenvector Centrality
1. Define status/influence for artists: Let this proportion be the entries of a
matrix representing relationship between each of the rappers—that is, a
network. Then, each rapper's status can be represented as its eigenvector
centrality in this network.
2. How to Interpret status: A rapper's status is represented by its ability to be a
lead rapper on albums, as well as to be connected to other rappers that lead
their own albums.
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20. Then We Regress Status on Success
1. Discover the importance of collaborating with influential artists: If an artist
with lower status collaborates with an artist with higher status in 2016, are
they likely to have a top album or song in 2017 or 2018? Does your network
with top producers affect your future status?
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21. 4. Technical Expertise

22. How do Centralities Influence Technical Expertise?
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23. Use Cases
1. Identify the artists with the best technical expertise: We measure technical expertise
by rhyme factor and vocabulary. Who is the best? What cliques and networks are the
best?
2. Identify relationship between quality and centrality measures: Correlate the “rhyme
factor” with regions. For example; do artists from Atlanta in general have a
higher rhyme factor/richer vocab/better skill than artists from NYC? Does the
region where the artist belongs to a factor in determining his success?
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24. Questions?
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