I am a behavioral economist and computational social scientist with a strong interest in the role of the digital media sphere and its capacity to connect economic and political domains through online discourse. At the core of my research is the investigation of how digital infrastructures and online information ecosystems mediate the emergence and diffusion of public concerns and uncertainty, as well as the decentralized, algorithm-mediated coordination of online behavior.

Drawing on economics, computational social science, and statistical modeling, I examine how individuals and groups form beliefs and expectations and act upon them in the digital public sphere. My work is grounded in behavioral economics, the sociology of communication, and social psychology, and combines social science theories with quantitative methods from econometrics, network science, information theory, natural language processing, machine learning, and computational semantics. Even though most of my work is computational, since my PhD I have also been committed to using qualitative methods—such as ethnography, diaries, and semi-structured interviews—which I often analyze using mixed-methods approaches.

With publications in international journals such as the Journal of the Royal Statistical Society – Statistics in Society, Finance Research Letters, PLOS One, and Economics Letters, I aim to contribute to a more empirically grounded understanding and theorization of how digital media and technologies influence the coordination of attention, expectations, and (market / political)  behavior. My research focuses specifically on how these dynamics unfold in response to expressed societal concerns—such as those related to referenda, elections, trade tensions, extreme events, and environmental crises—and their anticipated economic and political consequences.

A central objective of my research has been to understand how cross-domain issues and related narratives—at the intersection of politics and economics—are perceived, communicated, and acted upon. My doctoral dissertation (supervisors: Massimo Warglien & Michele Bernasconi), titled Talking About Uncertainty, defended at Ca’ Foscari University of Venice in 2018, laid the foundation for this agenda. It introduced new social media–based metrics to capture collective political and economic uncertainty and model its relationship with market dynamics, particularly financial market volatility.

In subsequent work, I have examined how digital platforms—like search engines and social media—mediate the formation and coordination of concerns, especially in response to complex events that cross national and institutional boundaries. I have developed models linking digital traces to expectation communication dynamics in cases such as Brexit and the COVID-19 pandemic, each offering insight into how public perceptions are formed, mediated by digital technologies, and hence translated into economic (e.g., market fluctuations) and/or political effects (e.g., political agenda setting). This line of inquiry has also extended to sustainability and climate-related risks, with attention to how these issues are constructed and contested in the digital public sphere.

From 2018 to 2023, I taught behavioral economics in the master's programmes in quantitative economics and sustainable finance at Ca’ Foscari University. This role also allowed me to develop an integrated research-led teaching approach, focused on decision-making under uncertainty and on the behavioral foundations of digital coordination. In parallel, I extended the work initiated in my dissertation to explore the role of media-amplified risk perception. As a postdoctoral researcher at the Venice School of Management, I analyzed Google and YouTube search data to measure public attention and concerns related to the COVID-19 pandemic and demonstrated its relationship with financial market capitalization across multiple countries. Published in Finance Research Letters, this study was the first to combine multimodal digital attention and concern metrics for non-economic phenomena, based on search engine data, to market-level outcomes.

In 2021, I also turned to the study of meme stocks as a paradigmatic case of decentralized digitally coordinated behavior. Employing a regime-switching cointegration model, together with Matteo Iacopini and Michele Costola, we identified a distinct attention-driven dynamic—termed “mementum”—that differentiates these assets from other high-volatility stocks, highlighting the influence of online subcultures and narratives on economic coordination and retail investors’ behavior.

From 2020 to 2024, I led a research team within the MUHAI project (Coordinator: Rainer Malaka; Scientific Director: Luc Steels) to develop an observatory on the perception of socio-economic inequalities. Together with Laura Spillner, Inés Blin, Lise Stork, Robert Porzel and other MUHAI researchers, we developed computational and AI tools to analyze and map online debates as networks of actors and themes, shedding light on how digital discourse shapes the representation, legitimization, and contestation of inequality.

Since June 2024, I have been conducting research at the Sciences Po médialab as part of the SoMe4Dem project. My current work continues this line of inquiry, focusing on online petitions and crowdfunding campaigns as forms of digitally mediated mobilisation. In particular, I investigate how socio-technical and framing factors—such as platform affordances to identity narratives—condition participation, influence information diffusion, and, through digital mobilisation, mediate the success of petitions and crowdfunding campaigns.