New paper in PRX on control of epidemic spreading

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.

Anatomy of an AI-powered malicious social botnet

A preprint of the paper titled “Anatomy of an AI-powered malicious social botnet” by Yang and Menczer was posted on arXiv. Concerns have been raised that large language models (LLMs) could be utilized to produce fake content with a deceptive intention, although evidence thus far remains anecdotal. This paper presents a case study about a coordinated inauthentic network of over a thousand fake Twitter accounts that employ ChatGPT to post machine-generated content and stolen images, and to engage with each other through replies and retweets. ChatGPT-generated content promotes suspicious crypto and news websites and spreads harmful comments. While the accounts in the AI botnet can be detected through their coordination patterns, current state-of-the-art LLM content classifiers fail to discriminate between them and human accounts in the wild. These findings highlight the threats posed by AI-enabled social bots and have been covered by Tech Policy Press, Business Insider, Wired, and Mashable, among others. And to no one’s surprise, versions of these articles likely summarized by ChatGPT already appear on plagiarized “news websites.”

Fortunato elected Fellow of the American Physical Society

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!

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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