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Virtual, January 3-16, 2021
Hashtag: #CNWW20
Follow us on Twitter!
@CNWWs

IMPORTANT UPDATE: due to COVID-19, travel restrictions, and concerns over the health and safety of our mentors, hosts, and participants we have decided to hold CNWW 2021 virtually this year. CNWW aims to connect people across borders to solve interconnected problems. Virtual CNWW will be limited to 80 participants selected from the application pool and will be free for all participants. Existing applications for the physical meeting in Québec will be considered for the virtual meeting.

The event will be larger, with a more flexible structure. Note that the dates may change. We will share details soon and are leaving applications open
here. We apologize for the inconvenience and we appreciate your flexibility. CNWWs handle turbulence just fine.

About

The Complex Networks Winter Workshop (CNWW) is an international school that offers an extraordinary opportunity for participants to engage in rigorous transdisciplinary complexity science research alongside some of the top researchers in the field of networks. The CNWW is designed for graduate students, postdoctoral fellows, and professionals. The lectures will present open problems and recent advances in the field of complex networks. Participants of this program will collaborate in small transdisciplinary research groups involving other participants as well as faculty. All course lectures will be given in English.

Program Dates: January 3-16, 2021

The CNWW is a collaboration between the University of Vermont Complex Systems Center and the Sentinel North Program of the Université Laval.

To sign up for notifications about CNWW click here.

Up to 80 international graduate students, postdoctoral fellows and professionals from different disciplines will be accepted. Application Deadline: October 23, 2020


  • Agenda

    COMING SOON
  • Logistics
    COMING SOON
  • Participation Fees
    Updated for Virtual CNWW - All Participants: $0
  • Faculty Bios

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    Laurent Hébert-Dufresne
    CNWW Director
    @LHDnets

    Assistant Professor, University of Vermont Department of Computer Science; Member, The Vermont Complex Systems Center

    Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.

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    Antoine Allard
    CNWW Director
    @all_are

    Assistant professor, Département de physique, de génie physique et d'optique, Université Laval, Québec, Canada

    Antoine's research combines statistical mechanics, graph theory, nonlinear dynamics and geometry to develop mathematical models of complex networks and to study the structure/function relationship specific to complex systems. His recent projects involve the mapping of real complex networks unto hyperbolic space to characterize the evolution of international trade, the use of greedy routing to unveil the spatial organization of the brain at various scales and across species, and the analytical solution of percolation on networks with a strong induced core-periphery structure to assess the potential of the Zika virus as a sexually transmitted infection.

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    Brooke Foucault Welles- Professor, Communication Studies in the College of Arts, Media and Design, Northeastern University Network Science Institute
    @foucaultwelles

    Brooke Welles is a Professor of Communication Studies in the College of Arts, Media and Design. Her research examines how social networks shape behavior, including how individuals identify resources within their social networks and leverage them to achieve personal and organizational goals.

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    Peter Dodds
    Director, Vermont Complex Systems Center
    @peterdodds

    Dodds's research focuses on system-level, big data problems in many areas including language and stories, sociotechnical systems, Earth sciences, biology, and ecology. His foundational funding was an NSF CAREER award granted to study sociotechnical phenomena (2009-2015). Together with Chris Danforth, he co-runs the Computational Story Lab.


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    C. Brandon Ogbunu
    Assistant Professor of Ecology and Evolutionary Biology
    Brown University
    @big_data_kane

    C. Brandon Ogbunu is an Assistant Professor in the Department of Ecology and Evolutionary Biology at Brown University. He is an evolutionary systems biologist, and uses experimental evolution, mathematical modeling, and computational biology to better understand the underlying causes and consequences of disease, across scales: from the biophysics of proteins involved in drug resistance to the social determinants underlying disease. In doing so, he aims to develop theory that enriches our understanding of the evolutionary and ecological underpinnings of disease, while contributing to practical solutions for clinical medicine and public health. Read more about his research and activities here:

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    Elizabeth Hobson
    Assistant Professor, Department of Biological Sciences, University of Cincinnati
    @Eliz_Hobson

    I am a biologist who specializes in animal behavior, behavioral ecology, cognitive ecology, and social cognition. My research focuses on social information: what animals know about their social worlds, how they come to know it, and what they do with that information.

    To address these questions, I integrate aspects of ecology and evolution to determine how the combination of sociality and cognition affect the emergence of group social structures from a combination of individual-level social actions, cognitive abilities, and decisions about future interactions. Combining this perspective into a feedback loop, and developing and applying new quantitative tools, allows me to back-infer what animals know about their social worlds by looking at how their decisions about social interactions are contingent on different kinds of social knowledge. Detecting the use of social knowledge provides new insight into the connections between social decisions and cognitive processing, how they can be affected by ecological dynamics, and how they can lead to the evolution of complex sociality.

    Much of my previous research focused on avian sociality, where I investigated social behavior and network structures in parrots. In my current research I apply these tools to a much wider range of species, from ants to primates, and even humans, while incorporating more quantitative and computational approaches.

    I am currently an Assistant Professor at the University of Cincinnati. My goal for research in my lab is to use rigorous comparative methods and an evolutionary perspective to discover ways in which the extreme sociality of some species emerged, through investigating what individuals understand about their social worlds and the strategies individuals use to balance the costs and benefits of social living.


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    Daniel B. Larremore
    Asst. Professor, Univ. Colorado Boulder
    BioFrontiers Institute & Dept. of Computer Science
    @DanLarremore

    My research focuses on developing methods of networks, dynamical systems, and statistical inference, to solve problems in social and biological systems. I try to keep a tight loop between data and theory, and learn a lot from confronting models and algorithms with real problems.

    I obtained my PhD in Applied Mathematics from the University of Colorado Boulder in 2012, advised by Juan G. Restrepo, after which I spent three years as a postdoctoral fellow at the Harvard T.H. Chan School of Public Health studying the genetic epidemiology of malaria in the Center for Communicable Disease Dynamics. I then joined the Santa Fe Institute as an Omidyar Fellow until 2017, when I joined the faculty at the University of Colorado Boulder in the Department of Computer Science and the BioFrontiers Institute.
    Malaria's antigenic variation and evolution - The var genes of the malaria parasite P. falciparum evolve according to complicated and unknown rules, with selective pressures at multiple scales both within hosts and between hosts. I create and use mathematical tools to understand the structural and evolutionary constraints on var gene evolution, and their relationships with parasite virulence, population structure, and epidemiology.

    Networks and theory - The processes that generate complex networks leave hints about themselves in the patterns of edges, and the relationships between those patterns and vertex metadata. I work on mathematical descriptions of graph ensembles, inference of community structures, vertex ordering or ranking, and using metadata to better understand network formation.
    The scientific ecosystem - The scientific method of hypothesis, experiment, and conclusion poorly describes modern scientific discovery and productivity. Instead, science is done by people who play various social roles in the ecosystem of science. I investigate faculty hiring, productivity patterns, scientific careers, and the dynamics of discovery through large-scale data collection and modeling.


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    Cassidy R Sugimoto, Professor of Informatics, Indiana University Bloomington
    @csugimoto

    Cassidy Sugimoto is Professor of Informatics at the School of Informatics, Computing, and Engineering at Indiana University Bloomington. She is also currently serving a rotation with the National Science Foundation as the Program Director for the Science of Science and Innovation Policy (SciSIP) program. Sugimoto's research expertise is broadly situated in the domains of science policy, scholarly communication, and scientometrics. Simply speaking, she investigates the ways in which knowledge is produced, disseminated, and rewarded, with a particular interest in issues of diversity and inclusion.

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    Samuel Scarpino
    Assistant Professor in the Network Science Institute at Northeastern University.
    @svscarpino

    I am an Assistant Professor of Marine & Environmental Sciences and Physics and a core faculty member in the Network Science Institute at Northeastern University. I am also the Chief Data Scientist at Dharma.ai. My research spans a broad range of topics in complex systems and network science, including: infectious diseases, forecasting and predictive modeling, disease genomics and transcriptomics, outbreak surveillance, network science, and decision making under uncertainty. Our group, the Emergent Epidemics Lab, approaches these topics by investigating questions at the intersection of biology, behavior, and disease.


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    Patrick Desrosiers - Affiliate Professor, Laval University , Centre de recherche CERVO; Département de physique, Université Laval; Dynamica research group


    Theoretical and mathematical physicist Fields of interest: classical and quantum integrable systems, symmetric functions, random matrix theory, orthogonal polynomials in many variables, representation theory, conformal field theory, supersymmetry, complex systems.



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    Dominique Gravel - Professor, Holder of the Canada Research Chair in Integrative Ecology, Université de Sherbrooke

    Research Themes:
    Spatial ecology, biogeography and ecology of metacommunities; Networks of ecological interactions; Theoretical, numerical and computational ecology; Biodiversity and ecosystem functioning; Climate change and forestry.

    Current Research:
    Ecosystems are difficult to study because of the diversity of interactions between species and their complex relationships with the environment. If understanding the distribution of biodiversity is already a challenge, predicting its response to global change is even more so. I adopt a research approach that integrates several disciplines of ecology to better understand the impact of global changes on biodiversity. Thus, I use notions of biogeography, community ecology and ecosystem functioning.

    My research program ultimately aims to develop a global model of ecosystem functioning. To do this, I propose new conceptual tools and implement them using mathematical and computer models, as well as massive data ( Big Data ). I also carry out laboratory experiments using a microbial ecosystem (the food web inhabiting the leaves of carnivorous plants). My research will produce biodiversity scenarios for the future. This knowledge is needed to protect biodiversity in a changing environment.

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    Jim Bagrow
    Assistant Professor, University of Vermont
    Department of Mathematics and Statistics
    @bagrow

    Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).

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    Hyejin Youn - Assistant Professor at Kellogg School of Management at Northwestern University, and Northwestern Institute on Complex Systems (NICO)

    I am an assistant professor at Kellogg School of Management at Northwestern University, and Northwestern Institute on Complex Systems (NICO). I was a research fellow at Santa Fe Institute and Harvard Kennedy School, and visiting scientist at MIT Media Lab. Before that, I was a senior research fellow at Mathematical Institute at University of Oxford , and Institute for New Economic Thinking at the Oxford Martin School; and ran a National Science Foundation grant (USA) to study Technological Change from the Map of Capabilities with Aaron Cluaset, the University of Colorado at Boulder. My PhD is in Statistical Physics at KAIST. I serve on the editorial board of PLOS One.

    My research aims to develop a mathematical and computational framework to understand complex systems. These include (see the detail here):
    Science of Cities
    Pathway of Innovation
    Linguistics (Semantic shift)

    Please visit my publication page or Google scholar profile for the more details on my publications
  • Participants
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    Coming Soon!

  • Application Requirements
    • Completed application form
    • Up-to-date curriculum vitae

    Applications will be accepted from graduate students, postdoctoral fellows, faculty, and professionals. We envision a diverse cohort of participants for the CNWW, applicants from all disciplines with an interest in networks are encouraged to apply. Proficiency in English and some background in science or mathematics are required. Participants are expected to attend the entire session. Applicants are welcome from all geographic regions. Underrepresented minorities and women are encouraged to apply.

    Applications will be open until: October 23, 2020

    Selection Criteria:

    Applications will be evaluated by the CNWW Selection Committee based on the evaluation criteria below.

    Knowledge transfer is a major goal of the CNWW. For this reason, participants will be chosen based not only on the excellence of their academic record, but also on their ability to share their knowledge and openness to thinking and learning outside established frameworks.

    Selection criteria include:

    - The excellence of the academic record
    - Ability to research, transdisciplinary collaboration and leadership
    - Relevance of the applicant's research field with the CNWW

  • Further Reading
    • Network Science, by Albert-László Barabási
    • Layeghifard, M., Hwang, D. M., & Guttman, D. S. (2017). Disentangling Interactions in the Microbiome: A Network Perspective. Trends in Microbiology, 25, 217–228. https://doi.org/10.1016/j.tim.2016.11.008
    • Giulio Cimini, Tiziano Squartini, Fabio Saracco, Diego Garlaschelli, Andrea Gabrielli, Guido Caldarelli (2018). The Statistical Physics of Real-World Networks. arXiv:1810.05095 https://arxiv.org/abs/1810.05095
    • Park, J., & Newman, M. E. J. (2004). Statistical mechanics of networks. Physical Review E, 70, 066117. https://doi.org/10.1103/PhysRevE.70.066117 https://arxiv.org/abs/cond-mat/0405566
    • Park, J., & Newman, M. E. J. (2005). Solution for the properties of a clustered network. Physical Review E, 72, 026136. https://doi.org/10.1103/PhysRevE.72.026136 https://arxiv.org/abs/cond-mat/0412579
    • Serrano, M. Á., Krioukov, D., & Boguñá, M. (2008). Self-Similarity of Complex Networks and Hidden Metric Spaces. Physical Review Letters, 100, 078701. https://doi.org/10.1103/PhysRevLett.100.078701https://arxiv.org/abs/0710.2092
    • Krioukov, D., Papadopoulos, F., Vahdat, A., & Boguñá, M. (2009). Curvature and temperature of complex networks. Physical Review E, 80, 035101. https://doi.org/10.1103/PhysRevE.80.035101 https://arxiv.org/abs/0903.2584
  • Outline of Projects

    Slack:

    Before you arrive, visit our CNWW Slack to start forming project ideas.

    Forming Groups:

    -Groups can be any size. They typically break down to about 3-5 people
    -You can be in more than one group but be aware of managing your time and try not to spread yourself too thin
    -We prefer you to form multi-disciplinary groups and try to work with people in fields other than your own
    -This is a unique opportunity to try something new, so have fun!

    Projects:

    -There are specific times scheduled to work in your groups, but please feel free to use unscheduled free time to work as well
    -We recognize that a week isn’t necessarily enough time to complete all the projects you will begin at the CNWW, and we hope you will begin and continue collaboration with your fellow CNWW participants and CNWW faculty before and after the dates of the program.

    Faculty Mentors:

    -During the program, faculty will be available during the project work times to assist groups with their projects. Make sure to utilize their expertise and ask lots of questions. Feel free to involve them in projects too if you would like.

    Available Data Sets and Challenge Questions:

    -While you are free to use any data set or tackle any question you would like for the projects we will also list a few possible data sets and questions that you will have access to for the CNWW.

    Presentations:

    -Group Presentation Day: TBA
    -The presentations are a meant to be a quick overview of your group projects, they shouldn’t be more than a few slides.
    -Presentations are informal but must be between 10-15 minutes long per group - this includes time for questions. Please practice and time your talk beforehand.
    -We will post a sign-up sheet for the presentation schedule in the CNWW classroom

    Post Program Write Up:

    -A one-page write-up (one per group) about your project will be due by TBA
    -We will release CNWW letters of completion upon receipt of write-ups.
    -We will post all CNWW write-ups on our website. If you are in the process of publication please still send Juniper your write-up and she will not post the write-up to the website, and will keep it in the private archive until notified of publication.
    -If you do publish a paper from a collaboration at the CNWW please let us know and send us a link so we can promote it and share your awesome work! This also helps us keep track of the success of the program.

  • Social Calendar

    COMING SOON

  • Organizers
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    Juniper Lovato
    Director of Partnerships and External Programs
    UVM Complex Systems Center
    @juniperlov

    At the Vermont Complex Systems Center, Juniper works across generations and geographical limits to make resources and knowledge on cutting-edge complexity science more accessible to those with a hunger and curiosity for learning and exploration. Juniper came to Burlington in 2018. She previously served as the Director of Education for the Santa Fe Institute, an independent complexity science research center. She is also a co-founder of MAKE Santa Fe, a not-for-profit community makerspace in Santa Fe, New Mexico. Juniper received her Master’s in the Western Classics from St. John’s College in 2013 where she completed a thesis on the nature of pleasure in work in Aristotle’s Nicomachean Ethics.

    Contact: juniper.lovato@uvm.edu
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    Marie-France Gévry
    Training programs coordinator - Sentinel North
    Université Laval
    @MFGevry

    Marie-France Gévry leads the development and implementation of Sentinel North innovative transdisciplinary training strategy at Université Laval (scholarship programs, Ph.D. schools, transversal skills development, learning community). She holds a Bachelor's and a Master's degree in Biology from UQAR, and cumulates 10 years of experience coordinating major training projects at Université Laval, from Africa to the Arctic. Creative and passionate about training and science, Marie-France has a particular interest in mycology, plant and behavioural ecology, biodiversity, northern environments, network research and regional development.

    Contact : marie-france.gevry@sn.ulaval.ca

  • Organizing Institutions

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    University of Vermont Complex Systems Center

    The Vermont Complex Systems Center is a highly collaborative, open, and playful space that embraces intellectual curiosity, kindness, and rigor. We are a post-disciplinary team of researchers working at the University of Vermont on real-world, data-rich, and meaningful complex systems problems of all kinds.

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    Sentinel North Program of the Université Laval
    Funded by the Pinnacle Canada Research Excellence Fund, Sentinel North enables Laval University to draw on more than half a century of excellence in northern research and optics and photonics to develop new technologies and improve our understanding. the northern environment and its impact on human beings and their health. Sentinel North deploys a major transdisciplinary research program and, among other things, enables the training of a new generation of researchers capable of solving the complex problems of the changing North.

  • Program Rules and Anti-Harassment Policy
    Program Rules:

    1. Participants will attend the entire scheduled program
    2. Participants agree to complete all pre and post program surveys
    3. Participants agree to be courteous and respectful to all other participants, staff, and faculty of the program. And to follow our anti-harassment policy:
    Anti Harassment Policy:

    This policy is adapted from the example available from the one written and promoted by the Ada Initiative co-founders.

    CNWW is dedicated to providing a harassment-free workshop experience for everyone, regardless of gender, sexual orientation, disability, race, or religion. We do not tolerate harassment of workshop participants in any form. Sexual language and imagery is not appropriate for any workshop venue, including presentations. Workshop participants violating these rules may be sanctioned or expelled from the CNWW at the discretion of the conference organizers.Harassment includes: offensive verbal comments related to gender, sexual orientation, disability, race, religion; sexual images in public spaces; deliberate intimidation, stalking, following, harassing photography or recording; sustained disruption of talks or other events; inappropriate physical contact; unwelcome sexual attention. Participants asked to stop any harassing behavior are expected to comply immediately. We expect participants to follow these rules at all time. If a participant engages in harassing behavior, the conference organizers may take any action they deem appropriate, including warning the offender or expulsion from the conference. If you are being harassed, or notice that someone else is being harassed, or have any other concerns, please contact a CNWW organizer immediately. We value your attendance.
  • Participants and Proceedings
    2019 CNWW Alumni:
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    • 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
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    • 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
    2018 CNWW Alumni:
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    • Achim Randelhoff, Takuvik, ULaval
    • Adrian Ortiz Cervantes, University of Auckland
    • Albert Tessier-Poirier, Université de Sherbrooke
    • Alexander Haak, Improbable
    • Ana M. Martín González, Copenhagen University
    • Ashlee Pigford, McGill University
    • Ben Emery, University of Vermont
    • Brennan Klein, Northeastern University
    • Charles Burdet, CR CHUQ - Université Laval
    • Charles Murphy, Université Laval
    • Claudia Manca, Université Laval
    • Dina Mistry, Northeastern University
    • David Sutherland Blair, Universitat Pompeu Fabra
    • Eline van den Broek-Altenburg, University of Vermont
    • Elizabeth Tripp, Dartmouth College
    • Emily Studd, McGill University
    • Fabrizio Damicelli, UKE - Hamburg University
    • Gudibanda Kashyap, IISER Pune
    • Guillaume St-Onge, Université Laval
    • Jessica Davis, Northeastern University
    • José R. Nicolás, National Autonomous University of Mexico
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    • Justin Taylor, Improbable
    • Kelly Gothard, University of Vermont
    • Mahta Ramezanian, University of Waterloo
    • Marco Mina, Université du Québec à Montréal
    • Melody K Schiaffino, San Diego State University
    • Michel Lavoie, Université Laval
    • Niall Keleher, U.C. Berkeley
    • Nick Stjern, University of Washington
    • Niokhor Dione, Université Laval
    • Ollin Demian Langle Chimal, University of Vermont
    • Oscar Granados, UJTL | PUJ
    • Reuben Escorpizo, University of Vermont
    • Ryan J. Gallagher, NSI, Northeastern University
    • Saint-Béat Blanche, Takuvik International Joint Laboratory
    • Samuel F. Rosenblatt, University of Vermont
    • Sarah Shugars Northeastern University
    • Sonya Ahamed, University of Vermont
    • Sophie Dufour-Beauséjour, Université INRS / CEN

    2019 CNWW Processings:

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

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

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

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

    *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 .

    2018 CNWW Processings:

    Embedding the growth of complex networks by extracting temporal patterns
    How collaborative projects develop: A network-based approach to evaluating team formation
    Effect of misinformation on diseases contagion
    Power to Corrupt
    Characteristics of animal social networks
    Underlying Motivations of Substance Abuse: A Study of Moral Values and Co-Occurring Addictive Behavior in Online Social Networks
    *A subset of CNWW 2018 team project abstracts are not listed here because they are in preparation for publication. Abstracts and proceeding papers will be listed here after publication .
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