Exploring the Future Potential of AI-Enabled Smartphone Processors
Why Beyoncé Is More Popular Than Me – Fairness, Diversity and Other Measures
1. Web Science and Technologies
University of Koblenz–Landau, Germany
Why Beyoncé Is More Popular Than Me
Fairness, Diversity and Other Measures
Jérôme Kunegis
Albert-Ludwigs-Universität Freiburg
July 27, 2012
2. Fairness
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3. Jérôme Kunegis Why Beyoncé Is More Popular Than Me
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4. (1) The Pareto Principle
“20% of people own 80% of land.”
(In 1910s Italy)
(Pareto, 1919)
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5. A IR
N F
U
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6. 8.9% of bands make up 91.1% of plays on Last.fm.
14.6% of user groups account for 75.4% of group memberships on Flickr.
17.4% of movies receive 82.6% of ratings on MovieLens.
17.7% of profiles receive 82.3% of ratings on Czech dating site Libimseti.cz.
19.7% of all cats receive 80.3% of all friendships on Catster.com.
20.3% of all users receive 79.7% of “friend” and “foe” links on Slashdot.
21.3% of users receive 78.7% of wall posts on Facebook.
22.9% of users make up 77.1% of all “@” mentions on Twitter.
23.1% of projects make up 76.9% of project memberships on Github.
27.3% of users receive 72.7% of replies on Digg.
27.6% of all hamsters receive 72.4% of all friendships on Hamsterster.com.
35.7% of all Twitter users receive 64.3% of all follows.
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7. Degree distribution
C(n) » n¡°
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8. TODO
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9. Which distribution is fairer?
Flickr friendships OR Digg replies
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10. Lorenz Curve – Gini Coefficient
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11. Flickr Digg
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12. Perfect Power Laws
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13. (2) Entropy
High entropy
Low entropy
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14. @kunegis @beyonce @ststaab
@noshir @barabasi
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15. Entropy
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16. max He = ln jVj
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18. Gini vs Entropy
½ = ¡0.71
p < 0.001
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19. (3) Random Walks
Diversity No diversity
Pret(L) large Pret(L) small
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20. Weighted Spectral Distribution
Pret(L) = §(i, j, . . . k) (d(i) d(j) . . . d(k)){1
= tr(NL)
= § k ¸k L
where ¸k are eigenvalues of N = D{1/2 A D{1/2.
Here: Use L = 4 and k · R
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21. Eigenvalues of N
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22. (4) Controllability
Diversity No diversity
(Liu, Slotine & Barabási 2011)
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23. Find a maximal directed 2-matching
#Knobs needed = jVj { max jMj
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24. Comparison
Power Law Gini Norm. Entropy Random walks Controllability
Generality Power-law All networks All networks All networks All networks
Interpretation Many (!) Economy Physical Simulation Control theory
Runtime Slow Fast Fast Medium Fast
Coverage d(u) ≥ dmin All All All All
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26. “The Rich Get Richer”
(Barabási & Albert 1999)
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27. “R
an
do
m
Wa
lks
Ar
riv
eL
es
sO
ft e
n”
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28. “Ne
two
rks
Get
E as
ier
to C
ont
rol”
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29. Experiments
20 networks from konect.uni-koblenz.de
9 authorship, 3 communication, 3 social, 3
interaction, 1 rating, 1 physical
Measure Diversity No diversity Diversity
decreasing trend increasing
Diameter 12 8 0
Gini coefficient 13 3 5
Fractional rank 10 6 4
Weighted spectral distribution 12 7 1
Controllability 15 5 0
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30. Thank You
Jérôme Kunegis @kunegis
Work in collaboration with Julia Preusse, Sergej Sizov, Damien
Fay & Felix Schwagereit
WeST – Institute for Web Science and Technologies
University of Koblenz–Landau, Germany
konect.uni-koblenz.de
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31. References
J. Kunegis, S. Sizov, F. Schwagereit, D. Fay. Diversity Dynamics in Online
Networks. Proc. Conf. on Hypertext and Social Media, 2012.
J. Kunegis, J. Preusse. Fairness on the Web: Alternatives to the Power Law.
Proc. Web Science Conf., 2012.
Y.-Y. Liu, J.-J. Slotine, A.-L. Barabási. Controllability of Complex Networks.
Nature, 473:167–173, May 2011.
J. Leskovec, J. Kleinberg, C. Faloutsos. Graph Evolution: Densification and
Shrinking Diameters. ACM Trans. Knowledge Discovery from Data, 1(1):1–40,
2007.
A.-L. Barabási, R. Albert. Emergence of Scaling in Random Networks.
Science, 286(5439):509–512, 1999.
V. Pareto. Manuale di economia politica con una introduzione alla scienza
sociale (Manual of political economy). Milano : Societa Editrice Libraria, 1919.
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