How do we #learn #language? As a search on a graph, in which activation spreads from word to word, biased towards unexplored lexical categories. Check my new-preprint 👇 arxiv.org/abs/2607.06258

Early Language Learning via Spreading Activation and Category Exploration in Complex Networks

Is word acquisition in children uneven with respect to semantic and lexical categories? To answer this question, we model early language learning as a search on a graph-based mental lexicon, driven by...

arxiv.org

New paper out! How do we get mad at football? It turns out fan emotional response is a far from linear phenomenon. In fact, it is. a "bursty" one: long stretches of quiet punctuated by sudden, chaotic explosions of emotions. Check it out! @dsalvaz.bsky.social link.springer.com/article/10.1...

Temporal dynamics of emotions in Italian online soccer fandoms - EPJ Data Science

This study investigates the emotional dynamics of Italian soccer fandoms through computational analysis of user-generated content from official Instagram accounts of 83 teams across Serie A, Serie B, ...

link.springer.com

Our first speaker at #TENET is Salvatore Citraro, who explores how to estimate node-level temporal homophily to capture heterogeneous mixing patterns in temporal networks. How? He uses a multi scale path-aware measure! #CCS2025

How do recommender systems shape our behavior? 📄 We review 144 studies across domains, from social media to GenAI. 🧭 With the EU Digital Services Act, data access is now possible. Our survey offers a guide to studying recommender-driven risks. 🔗 arxiv.org/abs/2407.01630

Salvatore Citraro, Edith Haim, Alessandra Carini, Cynthia S. Q. Siew, Giulio Rossetti, Massimo Stella SpreadPy: A Python tool for modelling spreading activation and superdiffusion in cognitive multiplex networks https://arxiv.org/abs/2507.09628

New pre-print! #SpreadPy, a Python implementation of spreading activation for both single-layer and multiplex networks. arXiv: arxiv.org/abs/2507.09628 GitHub: github.com/dsalvaz/Spre... @massimost.bsky.social @giuliorossetti.bsky.social @et al. #kddlab #sobigdata #isticnr #dipsco

SpreadPy: A Python tool for modelling spreading activation and superdiffusion in cognitive multiplex networks

We introduce SpreadPy as a Python library for simulating spreading activation in cognitive single-layer and multiplex networks. Our tool is designed to perform numerical simulations testing structure-...

arxiv.org

Call for Papers! 📣 📜 Join us in unraveling the impact of social media on human behavior 💻🙋🤳 for the 2nd edition of The Social Media Sway Workshop! 📅 Submit your papers by July 1st, 2025 (AoE). #SocialMedia #SMS25 #ASONAM25 #CFP sms-workshop.github.io.

🚀 The TENET @ @netsciconf.bsky.social program is live! Talks, posters & discussions all about temporal networks—don’t miss it! 🗓 Full program: sites.google.com/view/tenet-n... #NetSci2025 #TENET #TemporalNetworks #ComplexSystems #NetworkScience

TENET@Netsci25

Temporal networks are powerful models for understanding dynamical systems where entities and interactions appear and vanish as time goes by. Unlike static networks, which simply provide a snapshot of ...

sites.google.com

📢 TENET@ @netsciconf.bsky.social (June 2) Speaker announcement: 🎤 @martonkarsai.bsky.social, Central European University, Austria "Static representations of temporal networks and what they are good for" 📅 Submit your abstract by Feb 7 (info here: tinyurl.com/27ntstep) #NetSci2025 #Tenet2025

Information Diffusion and Opinion Dynamics on Node-Attributed Graphs: link.springer.com/chapter/10.1... With @vpansanella.bsky.social and @giuliorossetti.bsky.social

Structure-Attribute Similarity Interplay in Diffusion Dynamics on Social Networks

Social interactions are shaped by homophily, the tendency for individuals to connect with others who share similar attributes. Exploring this phenomenon is crucial for understanding a wide spectr...

link.springer.com

Our latest paper online (co-authored with @gmauro10.bsky.social and Emanuele Ferragina) explores emotional patterns in online behavior across 40 soccer fandoms during the 2023–24 Serie B and Lega Pro seasons. Read more: link.springer.com/chapter/10.1... More leagues and analyses coming soon :)

Burstiness in Emotions: A Case Study on Collective Affective Responses in Italian Soccer Fandoms

The bursty nature of emotions is rarely investigated outside cognitive and psychological studies. Therefore this work addresses a gap in the literature, investigating the phenomenon of emotional burst...

link.springer.com

A few months back we released #YSocial, a next-generation platform harnessing the power of LLM to create digital twins for social simulations. ysocialtwin.github.io 1/n

Home | Y Social

Where the Digital World Comes to Life - What is Y Social? Y Social is a cutting-edge Digital Twin of...

ysocialtwin.github.io

Excited to share our new work on #MachineLearning! We reimagine group evolution in temporal data with "archetypes" and "facets". Check out the paper for more👇 link.springer.com/article/10.1... W/ Rémy Cazabet, Giulio Rossetti & Salvatore Citraro #netsci #clustering #academicsky #science

Describing group evolution in temporal data using multi-faceted events - Machine Learning

Groups—such as clusters of points or communities of nodes—are fundamental when addressing various data mining tasks. In temporal data, the predominant approach for characterizing group evolution has b...

link.springer.com

How do our minds remember words? The answer: layers like an onion! A review by @massimost.bsky.social, Salvatore Citraro, Giulio Rossetti, Daniel Marinazzo, Yoed Kenett, & Mike V., shows why multilayer networks are best for modeling the mental lexicon. bit.ly/465obnv #psynomPBR Post by Daniel Pfaff

Mental lexicon as layers like an onion

Have you ever had a moment where a word was on the tip of your tongue, but you couldn’t quite remember it? For a bit of fun, here are two questions that might generate this feeling for you: What is th...

bit.ly