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RecSys 2018 - Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
1. IRGIR Group @UAM
Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems
Vancouver, Canada, 5 October 2018
Enhancing Structural Diversity in Social
Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems (RecSys 2018)
Javier Sanz-Cruzado and Pablo Castells
Universidad Autónoma de Madrid
http://ir.ii.uam.es
Vancouver, Canada, October 5th 2018
2. IRGIR Group @UAM
Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems
Vancouver, Canada, 5 October 2018
Contact Recommendation
etc.
3. IRGIR Group @UAM
Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems
Vancouver, Canada, 5 October 2018
Motivation
What is the goal of contact recommendation?
First goal
Transfer offline friendships
to the online network
ASAP
Then what?
Accuracy
Network density
Complementary goals
• Network evolution: structure, global properties
• Filter bubbles, glass ceiling, etc.
4. IRGIR Group @UAM
Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems
Vancouver, Canada, 5 October 2018
Goals
1. Define suitable metrics to measure global benefits
of recommendation
2. What do the metrics really mean?
Do they relate to any aspect of network functionality?
5. IRGIR Group @UAM
Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems
Vancouver, Canada, 5 October 2018
Potentially relevant structural features of social networks
Effects on
network structure
Structural
diversity
metrics
Non-redundancy
(weak ties)
Weak links have been closely related to
– Information novelty
– Enrichment in the information flow
Diversity
Social Network
Analysis
6. IRGIR Group @UAM
Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems
Vancouver, Canada, 5 October 2018
How can we measure structural effects of contact recommendation?
User Score
𝑢2 0.9
𝑢3 0.8
𝑢4 0.1
𝑢1
𝑢2
𝑢3 𝑢4
𝑢5
Structural
diversity metricRecommendation
ranking
7. IRGIR Group @UAM
Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems
Vancouver, Canada, 5 October 2018
Local diversity: triadic closure
Consider the direct environment of the link
Triadic closure: minimum unit of structural redundancy
Clustering coefficient complement
– Global metric
– Measures the proportion of non-redundant triads in the network
B
A
C B
A
C
a) Non-redundant
triad
b) Redundant
triad
8. IRGIR Group @UAM
Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems
Vancouver, Canada, 5 October 2018
Global diversity
Weak ties between communities
Modularity complement:
Number of weak ties
1
10
2
3
4
5
6
11
7
8
9
1
10
2
3
4
5
6
11
7
8
9
Low
High
Community Edge Gini Complement
– New metric
– Distribution of weak links between pairs of communities
Weak link redundancy Weak link diversity
9. IRGIR Group @UAM
Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems
Vancouver, Canada, 5 October 2018
Effect of recommendation algorithms on structural network diversity
Recommender P@10 Modularity Community Gini
Clustering
Coefficient
Implicit MF 0.0625 0.1550 0.0447 0.9766
Pers. SALSA 0.0577 0.1656 0.0447 0.9819
Adamic-Adar 0.0505 0.1487 0.0413 0.9748
MCN 0.0476 0.1461 0.0403 0.9746
Popularity 0.0234 0.2947 0.0613 0.9890
Jaccard 0.0169 0.1464 0.0434 0.9652
Centroid CB 0.0156 0.1652 0.0498 0.9627
Random 0.0006 0.2797 0.0901 0.9839
Training graph - 0.1464 0.0390 0.9829
What do these numbers really mean for the network?
10. IRGIR Group @UAM
Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems
Vancouver, Canada, 5 October 2018
Metric meaning w.r.t. network funcionality
We analyze the potential effects on reducing filter bubbles
– Does structural diversity increase information diversity?
Experiment
– Twitter data sample: ~10,000 users, ~230,000 interaction links (details in the paper)
– Start with a baseline recommendation: Implicit MF (Hu et al. 2008)
– Apply greedy rerankers for optimizing some structural diversity metric
– Extend the network with top 𝑘 recommended links
– Run propagation of (real downloaded) tweets through the network
– Measure information diversity
11. IRGIR Group @UAM
Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems
Vancouver, Canada, 5 October 2018
Diffusion properties
Focus on diversity
– Measured in terms of tweet hashtags (as representing topics)
The metric: Hashtag Gini Complement
– How evenly are hashtags propagated over the population
𝐻𝐺𝐶 𝑡 = 1 − 𝐺𝑖𝑛𝑖 𝑋 𝑡
𝑋 𝑡 = 𝑢 ∈ 𝒰 ℎ ∈ ℋ 𝑢 𝑡 ℎ∈ℋ
12. IRGIR Group @UAM
Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems
Vancouver, Canada, 5 October 2018
Results
P@10
Diversity
Clustering coef.
Modularity
Our metric
13. IRGIR Group @UAM
Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems
Vancouver, Canada, 5 October 2018
Conclusions & future work
We have proposed evaluation perspectives beyond accuracy
– Structural diversity: new metrics elaborating on weak ties
– Global network effects beyond (averaged) isolated user gains
Effects of metric enhancement on network functionality
– Weak ties improve the diversity of propagated information
Future work
– Study further metrics: distance-based, novelty, diversity…
– Try other networks (Facebook, Instagram, etc.)
14. IRGIR Group @UAM
Enhancing Structural Diversity in Social Networks by Recommending Weak Ties
12th ACM Conference on Recommender Systems
Vancouver, Canada, 5 October 2018
Thank you for your attention!
Questions?
Javier Sanz-Cruzado
E-mail: javier.sanz-cruzado@uam.es
Twitter: @JavierSanzCruza
Pablo Castells
E-mail: pablo.castells@uam.es
Twitter: @pcastells
Hinweis der Redaktion
Hello, my name is Javier Sanz-Cruzado, and I am going to show you the work I have developed along Pablo Castells and Sofía Pepa, named Structural Novelty and Diversity in Link Prediction.