CNetS faculty Filippo Radicchi and Santo Fortunato, along with graduate students Siddharth Patwardhan and Varun Rao, have found that, in order to limit the spreading of epidemics, it is advantageous to act on the composition of social groups. Specifically, since contact networks consists of different levels (school, work, family, etc.), groups of individuals should be highly overlapping between layers to slow down the progression of the disease. The results of the theoretical analysis, carried out on artificial networks, were supported by using enrollment and residence data of students of Indiana University. The paper has just been published in Physical Review X and the American Physical Society has highlighted it with a feature in Physics. See also Luddy’s press release.
Santo Fortunato has been elected Fellow of the American Physical Society (APS) for foundational contributions to the statistical physics of complex networks, and particularly to the study of community detection in networks and applications to social and scientific networks. The Fellowship is awarded annually to no more than one half of one percent of members of the APS for exceptional contributions to physics through research or publications, important applications of physics, leadership and physics education. Check the official press release of the school!
In 2002 the paper Community structure in social and biological networks, by Michelle Girvan and Mark E. J. Newman, marked the beginning of network community detection, possibly the most popular topic in network science, which tackles the problem of automatically discovering communities — groups of nodes of the network that are strongly connected or that share similar features or roles.
Twenty years later, it’s time to see how the field is doing. In the Comment 20 years of network community detection, just published in Nature Physics, Santo Fortunato and Mark Newman present a brief overview of this fascinating topic and highlight future directions.
Santo Fortunato is the 21st recipient of the Zachary’s Karate Club Award, for being the first to mention the famous social network at NetSci 2022, during the satellite workshop Communities in Networks. Fortunato received the singular trophy from Jesus Arroyo Relion. He is the third member of CNetS to receive this award, after YY Ahn and Filippo Radicchi.
A team of CNetS researchers has created the first global map of labor flow in collaboration with the world’s largest professional social network, LinkedIn. The work is reported in the journal Nature Communications. The study’s lead authors are Jaehyuk Park and Ian Wood, PhD students working with YY Ahn. Wood is currently a software engineer at LinkedIn. Other authors on the study are CNetS PhD student Elise Jing; Azadeh Nematzadeh of S&P Global, who contributed to the study as a CNetS PhD student; Souvik Ghosh of LinkedIn; and Michael Conover, a CNetS PhD graduate and senior data scientist at LinkedIn at the time of the study. CNetS researchers created the map using LinkedIn’s data on 500 million people between 1990 and 2015, including about 130 million job transitions between more than 4 million companies. The researchers gained access to this data as one of only two teams — IU and MIT — selected to continue their work on the LinkedIn Economic Graph Research program beyond 2017. The study’s result represents a powerful tool for understanding the flow of people between industries and regions in the U.S. and beyond. It could also help policymakers better understand how to address critical skill gaps in the labor market or connect workers with new opportunities in nearby communities. More…
The National Institutes of Health, under the National Library of Medicine’s program on data science research, awarded a $1.55 million grant to an interdisciplinary team lead by Luis Rocha, a professor of informatics, member of CNETS and the director of the NSF-NRT complex networks & systems program at the School of Informatics, Computing, and Engineering. The four-year project, a collaboration between SICE and the Indiana University School of Nursing, will employ innovative data- and network-science methods to produce myAURA, an easy-to-use web service for epilepsy patients. myAURA will be based on a large-scale epilepsy knowledge graph built by integrating data from social media, electronic health records, patient discussion boards, scientific literature databases, advocacy websites, and mobile app data. The knowledge graph will, in turn, be used to fuel recommendation and visualization algorithms based on the automatic inference of relevant associations. The inference will follow algorithms developed by Rocha’s team to remove redundancy and extract factual information from large knowledge graphs as well as parsimonious network visualizations developed by Katy Börner, Distinguished Professor of Engineering & Information Science at SICE. Continue reading CNetS team awarded NIH grant to improve chronic-disease management with Data and Network Science
First global analysis of human birth-rate cycles reveals that post-holiday ‘baby boom’ persists across cultures, hemispheres. CNetS PhD student Ian Wood and Professors Luis Rocha and Johan Bollen, in collaboration with Joana Sá, used data science and computational social science methods to demonstrate that “Human Sexual Cycles are Driven by Culture and Match Collective Moods.” See full article at IU News and media coverage in many venues such as The Independent, Time, Newsweek, Publico, ScienceDaily, Phys.org, The National Post, DailyMail, The Hindustan Times, Men’s Fitness, Mother Jones, Drive with Yasmeen Khan (at 17:30) (audio of interview), etc. Discussion of the paper was a top trending topic on Reddit. Watch a short video about the research.
The National Science Foundation has awarded nearly $3 million to train future research leaders in Complex Networks and Systems, via the PhD Program established by CNETS faculty. The highly selective grant from the NSF’s Research Traineeship Award will create a dual Ph.D. program at Indiana University to train graduate students to be proficient in both a specific discipline, such as psychology or political science, as well as network, complexity and data science. The new Ph.D. program will also leverage the strengths of the Indiana Network Science Institute, or IUNI, to involve students in interdisciplinary research.”The biggest challenges currently faced by society require large teams of people who are ‘fluent’ in more than one scientific discipline,” said Luis Rocha, CNETS professor in the IU School of Informatics, Computing, and Engineering who will lead the new program. “But the current education model in academia is still largely focused on training researchers who know how to set up independent labs with agendas driven by a single person. If we want to take on the really big problems, we’ve got to create more scientists with deep expertise in multiple areas.” Full Press Release Available.
Congratulations to Onur Varol for successfully defending his dissertation entitled “Analyzing Social Big Data to Study Online Discourse and its Manipulation” on April 25th 2017, supervised by Filippo Menczer. Onur completed a PhD degree in the Complex Systems track of the Informatics PhD Program. Onur has accepted a postdoctoral position at Northeastern University at the Center for Complex Network Research.