ITU Copenhagen Denmark
Coloring Social Relationships
Social relationships are the key determinant of crucial societal outcomes, including diffusion of innovation, productivity, happiness, and life expectancy. To better attain such outcomes at scale, it is therefore paramount to have technologies that can effectively capture the type of social relationships from digital data. NLP researchers have tried to do so from conversational text but mostly focusing on sentiment or topic mining, techniques that fall short on either conciseness or exhaustiveness. We propose a theoretical model of 10 dimensions (colors) of social relationships that is backed by decades of research in social sciences and that captures most of the common relationship types. We trained a deep-learning model to accurately classify text along these ten dimensions. By applying this tool on large-scale conversational data, we show that the combination of the predicted dimensions suggests both the types of relationships people entertain and the types of real-world communities they shape. We believe that the ability of capturing interpretable social dimensions from language using AI will help closing the gap between the oversimplified social constructs that existing social network analysis methods can measure and the multifaceted understanding of social dynamics that has been developed by decades of theoretical research.Short bio
Queen Mary University UK
The dynamics of higher-order networks: the effect of topology and triadic interactions
Higher-order networks capture the interactions among two or more nodes in complex systems ranging from the brain, to chemical reaction networks. Here we show that higher-order interactions are responsible for new dynamical processes that cannot be observed in pairwise networks.
We will cover how topology is key to define synchronization of topological signals, i.e. dynamical signals defined not only on nodes but also on links, triangles and higher-dimensional simplices in simplicial complexes. Interesting topological synchronization dictated by the Dirac operator can lead to the spontaneous emergence of a rhythmic phase where the synchronization order parameter displays low frequency oscillations which might shed light on possible topological mechanisms for the emergence of brain rhythms.
We will also reveal how triadic interactions can turn percolation into a fully-fledged dynamical process in which nodes can turn on and off intermittently in a periodic fashion or even chaotically leading to period doubling and a route to chaos of the percolation order parameter.
Maastricht University Netherlands
Taming the Wild West of Social Media: The Digital Services Act and its Effects on Computational Social Science
The surge in social media use over the last decade brought a host of unintended and unanticipated complications, such as disinformation, polarization, and undisclosed content monetization. Some of these problems can be traced back to the lack of regulation governing the digital interactions, algorithmic decisions, monetization, and business strategies that shape the social media landscape. In an effort to address these issues, the European Union has recently approved the Digital Services Act (DSA), aiming to better regulate online spaces, including social media platforms. This talk will delve into challenges and opportunities that the implementation and enforcement of the DSA may bring for computational social scientists.Short bio
Palermo University Italy
Social anatomy of a financial bubble
The study of financial bubbles is a highly controversial topics in economics and finance. Despite a large number of economic analyses, anecdotal evidence and increased theoretical attention, the quantitative monitoring and modeling of financial bubbles still miss standards broadly accepted by scholars. Our study focuses on the famous dotcom bubble that inflated financial markets during the period 1995-2000. Specifically, we investigate Nokia share ownership during the onset of the bubble and during its aftermath up to 2010 by investigating a unique database that tracks the financial ownership of all Finnish legal entities. We document a persistent flow of investment from foreign investors in the Nokia company during the inflation period of the bubble. This is a typical anecdotical scenario observed in the setting of financial bubbles. A second fundamental observation concerns the number of Finnish investors having an open investment position in Nokia at a given day. This number increased more than exponentially during the 1998-2000, reflecting a dramatic raise of attention at a country-wise level during bubble inflation. We exploit the unique combination of studying a multinational company that was among worldwide protagonists during dotcom bubble and a complete coverage of daily financial ownerships for all Finnish investors. The distribution of investment gains and losses was strongly inhomogeneous across different categories of investors. Financial professionals were better equipped to obtain gains during bubble inflation and limit losses when the bubble bursts. On the contrary, investors with limited financial expertise gained during bubble inflation but incurred in significant losses — or struggled to limit them — after the bubble burst.
Joint work with Federico Musciotto (University of Palermo, Italy) and Jyrki Piilo (University of Turku, Finland)