Finally out our paper in Nature "Persistent Interaction Patterns across Social Media and Over Time". #Toxicity #OnlineSocialDynamics @a_baronca @matteo_cinelli @RicercaSapienza @SapienzaRoma

RT @lastknight: Oggi nuova puntata di "Intelligenze Artificiali - Luci e Ombre": sarà mio ospite @Walter4C , Professore Ordinario di Infor….

"Fact-checking fallito? Ne parlo su Login del Corriere: cosa non ha funzionato e perché dobbiamo ripensare il modello di business delle piattaforme social. #Disinformazione #DataDrivenPolicy

5/ 🚀 Takeaway:.Social media does not mirror political reality. Instead, it amplifies noise, distortion, and selective narratives. 📄 Read the full paper: DOI: #DataScience #Elections #SocialMedia.

4/ ✔️ Hashtags reveal polarization.Co-occurrence networks of hashtags clearly highlight online polarization. Yet, the impact of this polarization on broader political dynamics remains questionable.

3/ ✔️ Pre-election activity spikes, then collapses.User activity surges before Election Day but drops significantly afterward, especially for losing parties. Engagement fades fast.

2/ ✔️ More posts ≠ more engagement.The most active coalitions on social media did not receive the highest engagement. Attention favors winners, not volume.

1/ 🗳️ Social Media and Elections.Our latest paper analyzed social media dynamics during the 2022 Italian Elections. Key findings challenge some common assumptions. 📊👇

6/ Curious about the details?.Read the full paper here: We hope this sparks new conversations about the value of attention in the digital age. Let us know your thoughts! 💬.

5/ 💡 What does this mean?.In the attention economy, chasing virality is risky. Instead, building consistent, sustained engagement is key to forming lasting connections with users.

4/ Rapid viral effects fade quickly, while slower, gradual processes last longer. This suggests that collective attention is elastic and influenced by pre-existing engagement trends. A "like" or viral post is often fleeting—it doesn’t guarantee long-term impact.

3/ Key findings:. Viral events rarely lead to sustained growth in engagement. We identified two types of virality:.1️⃣ "Loaded" virality: The final burst after a growth phase, followed by a decline. 2️⃣ "Sudden" virality: Unexpected events that briefly reactivate user attention.

2/ 📊 We analyzed over 1000 European news outlets on Facebook & YouTube (2018-2023), using a Bayesian structural time series model. Our goal: Understand the impact of viral posts on user engagement, from short-term spikes to long-term trends.

1/ 🎉 First paper of 2025!. In the quantitative study of the attention economy, we asked a key question:.How much does a like—or a viral post—truly reverberate?.Our new study, published in Scientific Reports, dives into this crucial topic. 🧵

RT @meharpist: Is science informing policy? A @nature survey finds that most respondents don't think that there are good systems in place t….

Forza Juve.

7/ This raises important questions:. How do bottom-up dynamics in digital spaces reshape agenda-setting?.What are the implications for polarization, misinformation, and the diversity of viewpoints.

While this reflects the decentralization of influence in digital spaces, it also highlights persistent patterns of polarization. Users consistently align with the majority (mainstream) or minority (alternative) viewpoints across debates.

5/ Notably, we found no single type of actor (media, activists, etc.) consistently dominating engagement across topics. Instead, shared narratives within ideological communities seem to shape the flow of discussions.

4/ For example, users supporting climate action are likely to back COVID-19 vaccination and aid for Ukraine. Similarly, those skeptical about one topic often hold contrarian views on others.

3/ A central finding: Ideological alignment appears to play a larger role in structuring online discussions than the influence of specific categories of actors. Users tend to cluster into two polarized communities.