seminar: algorithms for large social networks in theory...
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Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Institute of Theoretical Informatics – Algorithmics
www.kit.eduKIT – University of the State of Baden-Wuerttemberg andNational Laboratory of the Helmholtz Association
Seminar: Algorithms for Large SocialNetworks in Theory and Practice
Yaroslav Akhremtsev · Peter Sanders · Christian SchulzDarren Strash
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Introductions
Please introduce yourself, by stating:
Your nameWhat 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 InformaticsAlgorithmics
Introductions
Please introduce yourself, by stating:
Your nameWhat 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 SandersSearch data structures, some external memory algorithms
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Introductions
Please introduce yourself, by stating:
Your nameWhat 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?
Christian Schulz
2nd year postdoc with Peter SandersExpert in engineering efficient graph partitioning algorithms
Yaroslav Akhremtsev
PhD researcher with Peter SandersSearch data structures, some external memory algorithms
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Motivation
Make money
AdvertisingProduct recommendation
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Motivation
Make money
AdvertisingProduct recommendation
Understand our behavior
Sociologists–How do communities form? How do we identifycommunities? Who is “important”?Military–Who is a terrorist? Where will an attack happen next?Emergency Responders–How do we communicate, and howcan we collaborate better?
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Motivation
Make money
AdvertisingProduct recommendation
Understand our behavior
Sociologists–How do communities form? How do we identifycommunities? Who is “important”?Military–Who is a terrorist? Where will an attack happen next?Emergency Responders–How do we communicate, and howcan we collaborate better?
Algorithmics
Tons of publicly available dataInteresting open problemsExploiting the structure of real-world data
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Social Networks
Facebook, Google+, TwitterCommunication (e-mail, commenting on blog)Contact (meetings, sex, war)CitationsItems purchased together (+ people who made similarpurchases)Working together (co-authors, actors)Criminal/Terrorist networksPolitical corruption
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
What do we want to compute?
Graph Features
Subgraphs: triangles, cliques, cycles, pathsCommunity overlapClusters / partitions
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
What do we want to compute?
Graph Features
Subgraphs: triangles, cliques, cycles, pathsCommunity overlapClusters / partitions
Graph Measures
Correlation coefficientCentralityDiameterLargest clique / independent set / vertex cover
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
What do we want to compute?
Graph Features
Subgraphs: triangles, cliques, cycles, pathsCommunity overlapClusters / partitions
Graph Measures
Correlation coefficientCentralityDiameterLargest 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 InformaticsAlgorithmics
Theory and Practice
Types of articles in this area...
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Theory and Practice
Types of articles in this area...
Theory
Problem
Application
Algorithm
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Theory and Practice
Types of articles in this area...
Theory
Problem
Application
Algorithm
Experiments
ProblemApplication
Algorithm
Experiments
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Theory and Practice
Types of articles in this area...
Theory
Problem
Application
Algorithm
Experiments
ProblemApplication
Algorithm
Experiments
Applications
Problem
Application
Algorithm
Understanding
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Theory and Practice
This Seminar
Understanding
Experiments
Algorithm
Application
Problem
End-to-end (synthesis)
Assigned a topic problem, with aninteresting “seed” paper.Theory paper? Further discussapplications, experiments, and what welearn from applying the algorithm.Experimental paper? Further discusstheory, applications, understanding.Applications? Further discuss theory,experiments, and what we learn fromapplying the algorithm.
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Course Outline
Presentations
To be made with Ipe [http://ipe7.sourceforge.net/]5-minute teaser presentation45-minute full presentation
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Course Outline
Presentations
To be made with Ipe [http://ipe7.sourceforge.net/]5-minute teaser presentation45-minute full presentation
Comprehensive write-up
To be written with LATEX template12–15 pages
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Course Outline
Presentations
To be made with Ipe [http://ipe7.sourceforge.net/]5-minute teaser presentation45-minute full presentation
Comprehensive write-up
To be written with LATEX template12–15 pages
Supervisor
Work with a supervisor, who will help guide you withpresentations and write-up.
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Grade Breakdown: Presentations
5-minute teaser presentation - 10%
Motivation & persuasivenessClarity of presentationUse of illustrative images
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Grade Breakdown: Presentations
5-minute teaser presentation - 10%
Motivation & persuasivenessClarity of presentationUse of illustrative images
45-minute full presentation (40min + 5min for questions) - 50%Same as teaser presentation, plus:
Incorporating feedback from teaser presentationCohesivenessShowing clear understanding of methodsDiscussion of theory and applicationsAbility to answer questions
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Write-up - 40%
GrammarClear structureAnalysis of competitors and applicationsShow clear understanding of methodCritical analysis of techniques
Grade Breakdown: Write-up
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Guidelines: Presentations
Plan to talk for about 2 minutes per slideAvoid discussing basics, use majority of time to discussunique properties of your subjectUse bullet points, not paragraphsAvoid long theorems–keep it simpleUse helpful images!Proofread your slidesUnsure about something? Talk to your supervisorIt’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 InformaticsAlgorithmics
Guidelines: Write-up
Structure:Use the templateProvide succinct, but complete abstractWhy is this topic so important, and what makes thepaper great/unique?Complete bibliography with BibTeX
Use search tools such as Google Scholar to find relatedworkThoroughly discuss related workDiscuss the end-to-end impact of your topic
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Today Choose articles, set up first meeting withsupervisor24.04 Template & Ipe introduction + assign additionalarticles as needed15.05 5-minute teaser presentations12.06 2 presentations (TBD)19.06 2 presentations (TBD)26.06 2 presentations (TBD)10.07 Write-ups due
Class Schedule
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Dynamic subgraph counting
A Dynamic Data Structure for Counting Subgraphs in SparseGraphsZdenek Dvorak and Vojtech Tuma
Considers graphs with bounded expansionMaintaining counts during graph updates takes polylogarithmictime
Theory
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Dynamic subgraph counting
A Dynamic Data Structure for Counting Subgraphs in SparseGraphsZdenek Dvorak and Vojtech Tuma
Considers graphs with bounded expansionMaintaining counts during graph updates takes polylogarithmictime
Theory
· · ·5
4
6
0
3
6
1
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Dynamic subgraph counting
A Dynamic Data Structure for Counting Subgraphs in SparseGraphsZdenek Dvorak and Vojtech Tuma
Considers graphs with bounded expansionMaintaining counts during graph updates takes polylogarithmictime
Theory
· · ·5
3
7
0
2
5
3
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Triangle listing
Triangle Listing Algorithms: Back from the Diversionby Mark Ortmann and Ulrik Brandes
Fits existing algorithms into a common methodologyAlmost all theoretical algorithms match the best algorithmExperimental analysis on large sparse graphs
Theory Exp
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Clique finding
Finding Maximal Cliques in Massive Networks by H*-graphJ. Cheng, Y. Ke, A. Fu, J. Xu Yu, and L. Zhu
External memory algorithmUsed 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 InformaticsAlgorithmics
Diameter
An Exact Algorithm for Diameters of Large Real DirectedGraphsTakuya Akiba, Yoichi Iwata, and Yuki Kawata
First algorithm to compute diameter exactly for large sparsegraphs.
Experiments
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Diameter
An Exact Algorithm for Diameters of Large Real DirectedGraphsTakuya Akiba, Yoichi Iwata, and Yuki Kawata
First algorithm to compute diameter exactly for large sparsegraphs.
Experiments
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Diameter
An Exact Algorithm for Diameters of Large Real DirectedGraphsTakuya Akiba, Yoichi Iwata, and Yuki Kawata
First algorithm to compute diameter exactly for large sparsegraphs.
Experiments
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Shortest path queries
Dynamic and Historical Shortest-Path Distance Queries onLarge Evolving Networks by Pruned Landmark LabelingTakuya Akiba, Yoichi Iwata, and Yuichi Yoshida
A new algorithm for reporting the shortest distance betweenpoints in dynamic graphsSignificantly faster than previous methods
Experiments
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Shortest path queries
Dynamic and Historical Shortest-Path Distance Queries onLarge Evolving Networks by Pruned Landmark LabelingTakuya Akiba, Yoichi Iwata, and Yuichi Yoshida
A new algorithm for reporting the shortest distance betweenpoints in dynamic graphsSignificantly faster than previous methods
Experiments
1
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Shortest path queries
Dynamic and Historical Shortest-Path Distance Queries onLarge Evolving Networks by Pruned Landmark LabelingTakuya Akiba, Yoichi Iwata, and Yuichi Yoshida
A new algorithm for reporting the shortest distance betweenpoints in dynamic graphsSignificantly faster than previous methods
Experiments
4
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Personalized PageRank
Computing Personalized PageRank Quickly by ExploitingGraph StructuresTakanori Maehara, Takuya Akiba, Yoichi Iwata, and Ken-ichiKawarabayashi
Apply a graph decomposition to acheive faster algorithm forlarge sparse graphs
Experiments
[0.98, 1.12, ..., 9.8] + = Score/Ranking
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
Partner prediction
Romantic Partnerships and the Dispersion of Social Ties: ANetwork Analysis of Relationship Status on FacebookLars Backstrom and Jon Kleinberg
New graph measure dispersionUse measure to determine which Facebook friend is aromantic partner
Application Understanding
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
1. Dynamic subgraph counting2. Triangle listing3. Clique finding4. Diameter5. Shortest path queries6. Personalized PageRank7. Partner prediction
Articles
Theory
Theory
Experiments
Experiments
Experiments
Experiments
Th
Application Understanding
Exp
Darren Strash:Seminar: Algorithms for Large Social Networks in Theory and Practice
Institute of Theoretical InformaticsAlgorithmics
1. Dynamic subgraph counting (Darren)2. Triangle listing (Yaroslav)3. Clique finding (Darren)4. Diameter (Darren)5. Shortest path queries (Yaroslav)6. Personalized PageRank (Darren)7. Partner prediction (Christian)
Articles
Contact Info:
Darren: [email protected]: [email protected]: [email protected]