Proceedings

VIRTUAL CNWW ARCHIVES - 2021

PUBLIC PLAYLIST

CNWW 2021 TEAMS

Team Trail Systems
Team Zebra Crossing

Members: Nicolo Gozzi, Suman SD, Clayson, Celes, Briane Samson, Michelle Cirunay

Description: Given a road network, we would like to decompose the network into its components and measure some metrics for the total network and each of its components and see if the total behaviour is just a sum, less than/greater than the behaviour of its components (1) i.e. grid, tree, culdesac, irregular parts. We would also like to decompose the network according to roads (2) classified under hierarchy and then observe traffic for every addition/reduction of (1) and (2).

Mascot: zebra with a traffic light as its head

Slack channel: #team-road-traffic

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Team FinNet Folks

Members: Nicolò Gozzi, Raymond Pang, Ali Parviz, Furkan Gursoy

Description: Statistical arbitrage is a trading technique aimed at finding correlated pairs of stocks and trade their price differences. But, what happens if you have a network of correlated stocks rather than a couple? Can we extend existing techniques to account for the complex relationships among stocks?

Mascot: A flying squirrel

Slack Channel: #team-statarb

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Team SHAMPWW

Social Health Adaptivity in Managed Populations (edge) Weight Watchers (SHAMPWW)

Members: Scott Donaldson, Allison Johnson, Catherine Herzog, Jianjian Gao, Cristy Stone, Alice Schwarze, Mirela Causevic

Description: Comparison of changes between different managed populations when contagion is introduced

Mascot: Multiple poodles (or "shampoodles", if you will)

Slack Channel: #Team-SHAMPWW

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Team WOMBAT

Working-group On Monetization of Bipartisan Advertising on Television (WOMBAT)

Members: Ben Emery, Bridget Keown, Laura Vander Meiden, Mahsa Nouri Zonouz

Description: We propose to analyze political ad campaigns on local news to disentangle what partisan political ads, both local and national, that people saw in their homes during the 2012 election cycle (with data taken from ProPublica datasets). We will consider the ownership of these individual stations to attempt to analyze how these ads were placed in individual stations. Through a consideration of voter registration, turnout, and Twitter data from the 2012 election, we hope to understand the effects of partisan ads and money on the US voting population.

Mascot: A COMbat Wombat dressed as a local news reporter

Slack Channel: #team-politics-projects

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Super nodes super team

Super nodes super team

Members: Phil Chodrow, Nicole Eikmeier, Mari Kawakatsu, Nicholas Landry, Ali Parviz, Alice Schwarze, Benji Zusman

Description: Because many real-world networks are simply too large to visualize or analyze, one often ends up workingwith reduced networks with fewer nodes and/or edges, particularly when studying dynamical processes onnetworks. For a networkGwith an associated dynamical process, we are interested in identifying reducednetworks with fewer nodes thanGbut a similar trajectory of the associated dynamical process. We investigatehow the reduced network that best preserves trajectories differs for various dynamical systems. Consideringtwo general types of methods for reducing the number of nodes in a network — node sampling and nodeaggregation — we demonstrate via exhaustive search of the space of reduced networks ofGthat even forlinear dynamical systems, obtaining the best reduced networks are different. Based on our observations forsmall networks, we propose heuristic algorithms for finding good reduced networks for several dynamicalprocesses and compare our proposed algorithms to conventional methods for reducing the number of nodesin a coupled dynamical system (e.g., community detection and degree-based node binning). We demonstratethat our heuristics can help to find meaningful reduced networks for neuronal networks.

Mascot: achipmunk with a lot of nuts in its mouth and it wears a superhero suit with a superhero cape. The superhero "S" is made up of dots and lines so that it looks like a network.

Slack channel: #team-supernodes

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Team commitNet

Team commitNet

Members: Annemarie van der Marel, Benjamin Cinget, Furkan Gursoy, Grace Smith-Vidaurre, Tuan Pham Minh

Description: We are looking into the connections among GitHub users and repositories to assess how users maximize their visibility on this platform. We are also exploring how collaboration networks on GitHub reflect the users’ social networks on the same platform (i.e., follower relationships on Github) and on a different platform (e.g., Twitter).

Mascot: catbird eating grapes

Slack Channel: #team-commitNet

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Team School of Fish
Team Before and After

Team Before and After

Members: Connor Klopfer, Alexandre Caouette, Marya Poterek, Manuchehr Aminian, Alice Schwarze, Catherine M Herzog, Lauren Stanton, Allison Johnson, Lisa Barrett, Alexis Earl, Annemarie van der Marel

Description: We aim to explore the reconfiguration of social networks of different species in response to external or internal stimuli. These stimuli can range from a contagion, a change in the ecosystem, or introduction of a predator. We hope to find a way to compare this response in the social network across species in a quantitative manner.

Mascot: A vampire platypus with ant antennae wearing a scarf

Slack Channel: #team-before_and_after

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Team Graph Optimization

Team Graph Optimization

Members: Ali Parviz, Pooneh Mousavi,Samin Aref

Description: We formulate the problem of maximizing modularity of a given network as a graph optimization problem and solve this problem exactly using a mathematical solver.Then, we use the results of the solver for comparing the performance of several heuristics which attempt to maximize modularity for community detection.
Mascot: Captain Haddock

Slack Channel: #team-graph-optimization-project

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Team CNWWligans

Team CNWWligans

Members: Connor Gibbs; Alex Gates; Sirag Erkol; Joey O'Brien; Simon Aubé; Laurent Hébert-Dufresne

Description: We will be analyzing passing networks within premier league to (1) study the evolution of passing networks throughout the game, identifying any changes in strategy, and (2) explore the potential of estimating win-loss-draw throughout the game, comparing our results to betting markets.

Mascot: Soccer crazed eager beavers.

Slack channel: #team-soccer-prob-model

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Team Reddit BANdits

CNWW ARCHIVES - 2019

Ahmed Eissa
Alec Kirkley
Alexandre Terrigeol
Anshuman Swain
Béatrice Désy
Blake Williams
Brendan Case
Brennan Klein
Célestin Coquidé
Chris Brimacombe
Dakota Murray
Deepa Pureswaran
Diana Elisa Garcia Cortes
Francis Normand
Jane Adams

Jerome Guay
Josh Minot
Kate Wootton
Louisa Di Felice
Mari Kawakatsu
Nicole Eikmeier
Osnat Mokryn
Pantelis Loupos
Philip Chodrow
Randall Harp
Ritwika VPS
Rodrigo A. Migueles Ramírez
Samuel F Rosenblatt
Sara Williams
Sarah West
Shihui FENG
Valerie Valerio
Vincent Thibeault
Weston D. Viles

Mixing Patterns in Interdisciplinary Collaboration Networks: Assessing Interdisciplinarity Through Multiple Lenses - Shihui Feng and Alec Kirkley

View Abstract

Network analysis of collective motion - Vincent Thibeault, Brennan Klein, and Antoine Allard

View Abstract

Reef habitat connectivity and disease risk - Brendan Case and Sara Williams

View Abstract

Fusion-fission in wolf packs of Yellowstone National Park - Alexandre Terrigeol, Valerie Valerio, Sarah West, Blake Williams

View Abstract

*A subset of CNWW 2019 team project abstracts are not listed here because they are in preparation for publication. Abstracts and proceeding papers will be listed here after publication .