Seminar: Algorithms for Large Social Networks in Theory and
Seminar: Algorithms for Large Social Networks in Theory and Practice Yaroslav Akhremtsev · Peter Sanders · Christian Schulz Darren Strash Institute of Theoretical Informatics – Algorithmics Darren Strash: KIT – University of the State of Baden-Wuerttemberg and National Laboratory Algorithms of the Helmholtz for Association Seminar: Large Social Networks in Theory and Practice Institute of Theoretical Informatics www.kit.edu Algorithmics Introductions Please introduce yourself, by stating: Your name What year you are in (+ Bachelor’s or Master’s) Who you work with, and what you work on (if applicable) If you want: Why social networks? Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Introductions Please introduce yourself, by stating: Your name What year you are in (+ Bachelor’s or Master’s) Who you work with, and what you work on (if applicable) If you want: Why social networks? Yaroslav Akhremtsev PhD researcher with Peter Sanders Search data structures, some external memory algorithms Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Introductions Please introduce yourself, by stating: Your name What year you are in (+ Bachelor’s or Master’s) Who you work with, and what you work on (if applicable) If you want: Why social networks? Yaroslav Akhremtsev PhD researcher with Peter Sanders Search data structures, some external memory algorithms Christian Schulz 2nd year postdoc with Peter Sanders Expert in engineering efficient graph partitioning algorithms Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Motivation Make money Advertising Product recommendation Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Motivation Make money Advertising Product recommendation Understand our behavior Sociologists–How do communities form? How do we identify communities? Who is “important”? Military–Who is a terrorist? Where will an attack happen next? Emergency Responders–How do we communicate, and how can we collaborate better? Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Motivation Make money Advertising Product recommendation Understand our behavior Sociologists–How do communities form? How do we identify communities? Who is “important”? Military–Who is a terrorist? Where will an attack happen next? Emergency Responders–How do we communicate, and how can we collaborate better? Algorithmics Tons of publicly available data Interesting open problems Exploiting the structure of real-world data Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Social Networks Facebook, Google+, Twitter Communication (e-mail, commenting on blog) Contact (meetings, sex, war) Citations Items purchased together (+ people who made similar purchases) Working together (co-authors, actors) Criminal/Terrorist networks Political corruption Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics What do we want to compute? Graph Features Subgraphs: triangles, cliques, cycles, paths Community overlap Clusters / partitions Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics What do we want to compute? Graph Features Subgraphs: triangles, cliques, cycles, paths Community overlap Clusters / partitions Graph Measures Correlation coefficient Centrality Diameter Largest clique / independent set / vertex cover Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics What do we want to compute? Graph Features Subgraphs: triangles, cliques, cycles, paths Community overlap Clusters / partitions Graph Measures Correlation coefficient Centrality Diameter Largest clique / independent set / vertex cover Models Detect and predict patterns (brokerage) Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Theory and Practice Types of articles in this area... Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Theory and Practice Types of articles in this area... Theory Algorithm Application Problem Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Theory and Practice Types of articles in this area... Theory Experiments Experiments Algorithm Algorithm Application Problem Application Problem Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Theory and Practice Types of articles in this area... Theory Experiments Applications Experiments Understanding Algorithm Algorithm Algorithm Application Problem Application Problem Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Application Problem Institute of Theoretical Informatics Algorithmics Theory and Practice This Seminar Understanding Experiments Algorithm Application Problem End-to-end (synthesis) Assigned a topic problem, with an interesting “seed” paper. Theory paper? Further discuss applications, experiments, and what we learn from applying the algorithm. Experimental paper? Further discuss theory, applications, understanding. Applications? Further discuss theory, experiments, and what we learn from applying the algorithm. Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Course Outline Presentations To be made with Ipe [http://ipe7.sourceforge.net/] 5-minute teaser presentation 45-minute full presentation Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Course Outline Presentations To be made with Ipe [http://ipe7.sourceforge.net/] 5-minute teaser presentation 45-minute full presentation Comprehensive write-up To be written with LATEX template 12–15 pages Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Course Outline Presentations To be made with Ipe [http://ipe7.sourceforge.net/] 5-minute teaser presentation 45-minute full presentation Comprehensive write-up To be written with LATEX template 12–15 pages Supervisor Work with a supervisor, who will help guide you with presentations and write-up. Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Grade Breakdown: Presentations 5-minute teaser presentation - 10% Motivation & persuasiveness Clarity of presentation Use of illustrative images Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Grade Breakdown: Presentations 5-minute teaser presentation - 10% Motivation & persuasiveness Clarity of presentation Use of illustrative images 45-minute full presentation (40min + 5min for questions) - 50% Same as teaser presentation, plus: Incorporating feedback from teaser presentation Cohesiveness Showing clear understanding of methods Discussion of theory and applications Ability to answer questions Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Grade Breakdown: Write-up Write-up - 40% Grammar Clear structure Analysis of competitors and applications Show clear understanding of method Critical analysis of techniques Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Guidelines: Presentations Plan to talk for about 2 minutes per slide Avoid discussing basics, use majority of time to discuss unique properties of your subject Use bullet points, not paragraphs Avoid long theorems–keep it simple Use helpful images! Proofread your slides Unsure about something? Talk to your supervisor It’s ok to be nervous. Keep calm and carry on Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Guidelines: Write-up Structure: Use the template Provide succinct, but complete abstract Why is this topic so important, and what makes the paper great/unique? Complete bibliography with BibTeX Use search tools such as Google Scholar to find related work Thoroughly discuss related work Discuss the end-to-end impact of your topic Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Class Schedule Today Choose articles, set up first meeting with supervisor 24.04 Template & Ipe introduction + assign additional articles as needed 15.05 5-minute teaser presentations 12.06 2 presentations (TBD) 19.06 2 presentations (TBD) 26.06 2 presentations (TBD) 10.07 Write-ups due Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Dynamic subgraph counting A Dynamic Data Structure for Counting Subgraphs in Sparse Graphs ˇ Dvoˇrak ´ and Vojtech ˇ Tuma Zdenek ˚ Considers graphs with bounded expansion Maintaining counts during graph updates takes polylogarithmic time Theory Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Dynamic subgraph counting A Dynamic Data Structure for Counting Subgraphs in Sparse Graphs ˇ Dvoˇrak ´ and Vojtech ˇ Tuma Zdenek ˚ Considers graphs with bounded expansion Maintaining counts during graph updates takes polylogarithmic time 0 5 4 3 ··· 6 6 Theory Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice 1 Institute of Theoretical Informatics Algorithmics Dynamic subgraph counting A Dynamic Data Structure for Counting Subgraphs in Sparse Graphs ˇ Dvoˇrak ´ and Vojtech ˇ Tuma Zdenek ˚ Considers graphs with bounded expansion Maintaining counts during graph updates takes polylogarithmic time 0 5 3 2 ··· 7 5 Theory Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice 3 Institute of Theoretical Informatics Algorithmics Triangle listing Triangle Listing Algorithms: Back from the Diversion by Mark Ortmann and Ulrik Brandes Fits existing algorithms into a common methodology Almost all theoretical algorithms match the best algorithm Experimental analysis on large sparse graphs Theory Exp Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Clique finding Finding Maximal Cliques in Massive Networks by H*-graph J. Cheng, Y. Ke, A. Fu, J. Xu Yu, and L. Zhu External memory algorithm Used to list all cliques in graphs with up to 10 million nodes Experiments Th Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Diameter An Exact Algorithm for Diameters of Large Real Directed Graphs Takuya Akiba, Yoichi Iwata, and Yuki Kawata First algorithm to compute diameter exactly for large sparse graphs. Experiments Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Diameter An Exact Algorithm for Diameters of Large Real Directed Graphs Takuya Akiba, Yoichi Iwata, and Yuki Kawata First algorithm to compute diameter exactly for large sparse graphs. Experiments Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Diameter An Exact Algorithm for Diameters of Large Real Directed Graphs Takuya Akiba, Yoichi Iwata, and Yuki Kawata First algorithm to compute diameter exactly for large sparse graphs. Experiments Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Shortest path queries Dynamic and Historical Shortest-Path Distance Queries on Large Evolving Networks by Pruned Landmark Labeling Takuya Akiba, Yoichi Iwata, and Yuichi Yoshida A new algorithm for reporting the shortest distance between points in dynamic graphs Significantly faster than previous methods Experiments Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Shortest path queries Dynamic and Historical Shortest-Path Distance Queries on Large Evolving Networks by Pruned Landmark Labeling Takuya Akiba, Yoichi Iwata, and Yuichi Yoshida A new algorithm for reporting the shortest distance between points in dynamic graphs Significantly faster than previous methods 1 Experiments Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Shortest path queries Dynamic and Historical Shortest-Path Distance Queries on Large Evolving Networks by Pruned Landmark Labeling Takuya Akiba, Yoichi Iwata, and Yuichi Yoshida A new algorithm for reporting the shortest distance between points in dynamic graphs Significantly faster than previous methods 4 Experiments Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Personalized PageRank Computing Personalized PageRank Quickly by Exploiting Graph Structures Takanori Maehara, Takuya Akiba, Yoichi Iwata, and Ken-ichi Kawarabayashi Apply a graph decomposition to acheive faster algorithm for large sparse graphs [0.98, 1.12, ..., 9.8] + = Score/Ranking Experiments Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Partner prediction Romantic Partnerships and the Dispersion of Social Ties: A Network Analysis of Relationship Status on Facebook Lars Backstrom and Jon Kleinberg New graph measure dispersion Use measure to determine which Facebook friend is a romantic partner Application Understanding Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics Articles 1. 2. 3. 4. 5. 6. 7. Dynamic subgraph counting Triangle listing Clique finding Diameter Shortest path queries Personalized PageRank Partner prediction Theory Theory Exp Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Experiments Th Experiments Experiments Experiments Application Understanding Institute of Theoretical Informatics Algorithmics Articles 1. 2. 3. 4. 5. 6. 7. Dynamic subgraph counting (Darren) Triangle listing (Yaroslav) Clique finding (Darren) Diameter (Darren) Shortest path queries (Yaroslav) Personalized PageRank (Darren) Partner prediction (Christian) Contact Info: Darren: [email protected] Yaroslav: [email protected] Christian: [email protected] Darren Strash: Seminar: Algorithms for Large Social Networks in Theory and Practice Institute of Theoretical Informatics Algorithmics
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