Résumé de section

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    INP9087851 - NETWORK SCIENCE 2024-2025

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    Projects and IPs presentations

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    Course slides & material

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    Introduction

    • Le1 - Wed Oct 2, 2024 Introduction to the course: elearning site, projects and interdisciplinary projects, network examples, contents overview, exam dates.

    • Le2 - Fri Oct 4, 2024 Networks as graphs; Directed and undirected networks; Paths, Cycles, Diameter; Adjacency matrix; Nodes degrees and the degree distribution; Sparsity; Bipartite graphs; Signed graphs; Connectivity.

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    Centrality

    • Le3 - Wed Oct 9, 2024 Degree centrality; Power law versus Poisson distribution; Estimation methods for the degree exponent: ML approach; Explaining the power law; Erdos-Renyi random model: binomial and Poisson descriptions of the model; Small world; Power law versus Poisson distribution; Growth and preferential attachment; the Barabasi-Albert model.

    • Le4 - Fri Oct 11, 2024 Attractiveness and the Bianconi-Barabasi model; Analysis of the Bianconi-Barabasi model; Examples with equal and uniform fitness; Measuring fitness: the www; Other ideas for modelling the power-law, Properties of the power-law: largest hub, moments and scale-free networks, distances; PageRank: random walk, dead ends and spider traps, teleportation; PageRank with restart.

    • Le5 - Wed Oct. 16, 2024 PageRank versus degree centrality; convergence properties of PageRank; PageRank matrix structure via the condensation graph; Action of the teleport vector: one leaf-only, one eigenvalue set to 1 and the rest to (at most) c; Interpretation; Tuning the teleport vector: Local PageRank; Examples of application; Approximate PageRank and the push operation.

    • Le6 - Fri Oct. 18, 2024 Approximate PageRank and the push operation: proof of the precision guarantee; Application to link prediction; Topic specific PageRank; Signed PageRank; Preventing spamming; Row-normalized PageRank; HITs centrality.

    • Le7 - Wed Oct 23, 2024 Eigenvector and Katz centralities and their relation to PageRank and Degree centrality; Closeness and harmonic centrality; Betweenness centrality as a measure of brokerage; The clustering coefficient; Wrap-up on centrality measures.

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    Community detection

    • Le7 - Wed Oct 23, 2024 Community detection problem: Granovetter's view and the role of weak ties; The core-periphery model and overlapping communities; Modularity: definition.


    • Le8 - Fri Oct 25, 2024 Modularity: definition and matrix formalization; The Louvain algorithm for modularity optimization and its main characteristics; Solving greediness by consensus clustering; Generalizing modularity: the directed and signed network case; Modularity with overlapping communities.

    • Le9 - Wed Oct 30, 2024 Interdisciplinary projects overview and deadlines; Modularity in the two-communities case: spectral approach; The normalised cut criterion; Suboptimal solution to normalised cut: algebraic connectivity and Fiedler's eigenvector; Conductance and the network community profile; InfoMap criterion: node and community view.

    • Le10 - Wed Nov 6, 2024 The socio-psychological perspective on networks, by prof. Caterina Suitner.

    • Language and social cognition - the socio-psychological view on networks Fichier

    • Le11 - Wed Nov 13, 2024 Projects overview and deadlines; The InfoMap criterion: the node view, the community view, inside communities; Compact result; Normalized mutual information; Wrap-up on community assignment measures; The BigClam: rationale of a model-based approach and algorithm.

    • Le12 - Fri Nov 15, 2024 The BigClam: algorithm and performance; Stochastic block models: Degree corrected SBMs; Mixed membership SBMs; Weighted SBMs; Dendrograms: divisive and agglomerative approaches; Girvan-Newmann method; HDBSCAN.

    • Le13 - Wed Nov 20, 2024 Clique percolation; Wrap-up on community detection; Correlation networks.

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    Network layout, polarization

    • Le13 - Wed Nov 20, 2024 The layout problem; Aesthetic criteria; Spring-embedder algorithm; Repulsive and attractive forces; Fruchterman & Reingold; Force atlas 2; Gravity; Approximate repulsion.

    • Le15 - Wed Nov 27, 2024 Alessandro Galeazzi: Unveiling Echo Chambers and Users’ Opinions on Online Social Media

    • echo_chambers galeazzi 2024 Fichier

    • Le16 - Fri Nov 29, 2024 UMAP as a force-layout algorithm; Software tools.

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    Semantic networks

    Marqué

    • Le16 - Fri Nov 29, 2024 Semantic networks; Data collection: Reddit and TikTok; Data preprocessing and SpaCy; Building the semantic network; the role of TF-IDF; Topic detection; A comparison between InfoMap and Louvain.

    • Le17 - Wed Dec 4, 2024 Lab #1 scraping data from Reddit and TikTok by Sina Tavakoli.

    • Lab 1 data scraping from social networks Dossier

    • Le18 - Fri Dec 6, 2024 Lab #2 topic detection from textual data.

    • Lab2 topic detection Dossier

    • Le19 - Mon Dec 9, 2024 classroom Pe, 14:30 Feedback on projects (IPs and non IPs) -  only for those needing a feedback

    • Le20 - Wed Dec 11, 2024 A comparison between Louvain, Infomap, the spe ctral approach, DCSBMs and BIGClam; The trasnformer architecture: BERT, BERTA, GPT-2, and GPT-3 models; BERTopic model and its performance; Sentiment analysis: an overview; LIWC categories; BERTAgent; Using sentiment analysis.

    • Part4 semantic - updated version Fichier

    • Le21 - Fri Dec 13, 2024 Lab #3 network visualisation in Python by Lejla Dzanko

    • Lab 3 network visualization in Python Dossier

    • Le22 - Wed Dec 18, 2024 The non-negative matrix factorization approach; generalized Kullback-Leibler divergence metric; Latent Dirichlet allocation: statistical model; Variational auto-encoders and the ELBO function; VAE for topic detection: NVDM, ProdLDA, DirVAE, NFTM, and NBVAE models.

    • Le23 - Fri Dec 20, 2024 Lab #4 network visualisation in Gephi by Lejla Dzanko

    • Lab 4 network visualization with Gephi Dossier

    • Le24 - Wed Jan 8, 2025  Homophily and related concepts: Selective exposure, Polarization, Ego Chamber, Filter bubble; Degree homophily or assortativity; the correlation matrix; Nearest neighbour degree function and its exponent; Structural disassortativity; Structural and natural cutoffs; Random rewiring; Network robustness; Robustness of scale-free networks; Attack tolerance; Robustness optimization; An application example.

    • Le25 - Thu Jan 16, 2025 - DISLL, classroom 11 Feedback to interdisciplinary projects.

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    Video resources from past years (may be helpful)