New paper in Nature Physics

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.

Fortunato elected Fellow of the Network Science Society

Santo Fortunato has been elected Fellow of the Network Science Society (NSS) for seminal work in network community structure leading to advances in multiresolution approaches and validation, and for contributions to disseminating network science. The Fellowship is awarded annually to members of the community for their exceptional lifelong individual contributions to any area of network science research and to the community of network scientists, both locally and globally. The award has been announced at NetSci 2022, the flagship event of the NSS. Fortunato is the first member of Luddy to receive this prestigious recognition. Check the official press release of the school!

Networks Tool Visualization

New network visualization tool maps information spread

Today the Observatory on Social Media and CNetS launched a revamped research tool to give journalists, other researchers, and the public a broad view of what’s happening on social media. The tool helps overcome some of the biggest challenges of interpreting information flow online, which is often difficult to understand because it’s so fast-paced and experienced from the perspective of an individual account’s newsfeed.

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OSoMe/CNetS/NaN

Postdoc position 2022

CNetS and the Observatory on Social Media invite applications for a Postdoctoral Fellow position. The anticipated start date is August 1, 2022. The position is initially for 12 months and can be renewed for up to 24 additional months, depending on performance and funds availability.

The Postdoctoral Fellow will work with Alessandro Flammini, Filippo Menczer, and collaborators at IU and other universities on sponsored research related to online influence campaigns, at the intersection of machine learning, network, data, and computational social science. The Fellow will be expected to coordinate a team of graduate students, conduct research on significant projects in the areas of online information diffusion and manipulation, present work in progress at professional conferences and sponsored workshops, and assist with the development of funding proposals and scientific papers.

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Luddy AI Center

We’re moving and hiring!

We have two big announcements! First, CNetS (along with IUNI and OSoMe) is moving to the new Luddy Center for Artificial Intelligence. Second, we have a new tenure-track assistant professor position in Artificial Intelligence and Network Science. We welcome any candidates who study AI, complex systems, and network science (all broadly defined). Potential research areas include, but are not limited to, deep learning, graph neural networks, complex systems, complex networks, computational neuroscience, computational social science, social media analytics, agent-based models, and the impacts of AI and social media on society.  We especially welcome applications from members of underrepresented groups in computing. More info and application here!

New grant on optimization problems in complex networks

The US Air Force Office of Scientific Research has awarded the grant Algorithmic and theoretical approaches to optimization problems on complex networks to CNetS faculty Filippo Radicchi. The project will study different classes of optimization problems (OPs) on complex networks, including optimal percolation, optimal sampling, optimal navigation, and optimal seeding. The research will address the practical, algorithmic and theoretical aspects of the OPs, focusing on the generalization of the problem settings to realistic scenarios, the development of numerical techniques for the solution of the OPs, and the establishment of analytical baselines for the objective assessment of the performance of the optimization algorithms.

The total budget of the award is 450,000 USD, the project’s duration is three years.

drifter bots

Probing political bias on Twitter with drifter bots

Our latest paper “Neutral bots probe political bias on social media” by Wen Chen, Diogo Pacheco, Kai-Cheng Yang & Fil Menczer just came out in Nature Communications. We find strong evidence of political bias on Twitter, but not as many think: (1) it is conservative rather than liberal bias, and (2) it results from user interactions (and abuse) rather than platform algorithms. We tracked neutral “drifter” bots to probe political biases. In the figure, we see the drifters in yellow and a sample of their friends and followers colored according to political alignment. Large nodes are accounts sharing a lot of low-credibility links.

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ICWSM Test of Time Award

Twitter echo chambers

Our 2011 paper Political Polarization on Twitter was recognized at the 2021 AAAI International Conference on Web and Social Media (ICWSM) with the Test of Time Award. First author Mike Conover, who was then a PhD student and is now Director of Machine Learning Engineering at Workday, accepted the award at a ceremony at the end of the ICWSM conference. Other authors are Jacob Ratkiewicz (now a Tech Lead at Google), Bruno Gonçalves (now VP at JPMorgan Chase), Matt Francisco (now Lecturer at IU Luddy School), Alessandro Flammini (Professor of Informatics at IU Luddy), and Filippo Menczer (Distinguished Professor and Director of the Observatory on Social Media at IU).

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New grant on AI and multilayer networks

The Army Research Office has awarded the grant Multilayer network embeddings and applications to real-world problems to CNetS faculty Santo Fortunato and Filippo Radicchi. The project lies at the interface between artificial intelligence and network science and aims at developing embeddings of multilayer networks in vector space. While graph embeddings have become very popular over the past decade, most of the research in this area focuses on the analysis of isolated graphs. However, networks in the real world do not exist in isolation, but they are coupled with other networks. For example in social media, the same person may interact with different individuals depending on the online platform. 

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