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RecSys 2018 - Enhancing Structural Diversity in Social Networks by Recommending Weak Ties

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Slides of the presentation of the full paper at the 12th ACM Conference on Recommender Systems (2-7 October 2018, Vancouver, Canada)

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RecSys 2018 - Enhancing Structural Diversity in Social Networks by Recommending Weak Ties

  1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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

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