5 research outputs found
Unraveling the Origin of Social Bursts in Collective Attention
In the era of social media, every day billions of individuals produce content
in socio-technical systems resulting in a deluge of information. However, human
attention is a limited resource and it is increasingly challenging to consume
the most suitable content for one's interests. In fact, the complex interplay
between individual and social activities in social systems overwhelmed by
information results in bursty activity of collective attention which are still
poorly understood. Here, we tackle this challenge by analyzing the online
activity of millions of users in a popular microblogging platform during
exceptional events, from NBA Finals to the elections of Pope Francis and the
discovery of gravitational waves. We observe extreme fluctuations in collective
attention that we are able to characterize and explain by considering the
co-occurrence of two fundamental factors: the heterogeneity of social
interactions and the preferential attention towards influential users. Our
findings demonstrate how combining simple mechanisms provides a route towards
complex social phenomena.Comment: 14 pages, 10 figure
Assessing the risks of "infodemics" in response to COVID-19 epidemics
Our society is built on a complex web of interdependencies whose effects
become manifest during extraordinary events such as the COVID-19 pandemic, with
shocks in one system propagating to the others to an exceptional extent. We
analyzed more than 100 millions Twitter messages posted worldwide in 64
languages during the epidemic emergency due to SARS-CoV-2 and classified the
reliability of news diffused. We found that waves of unreliable and low-quality
information anticipate the epidemic ones, exposing entire countries to
irrational social behavior and serious threats for public health. When the
epidemics hit the same area, reliable information is quickly inoculated, like
antibodies, and the system shifts focus towards certified informational
sources. Contrary to mainstream beliefs, we show that human response to
falsehood exhibits early-warning signals that might be mitigated with adequate
communication strategies.Comment: The dataset analyzed in this paper can be interactively visualized
and accessed at https://covid19obs.fbk.eu
The shocklet transform: a decomposition method for the identification of local, mechanism-driven dynamics in sociotechnical time series
We introduce a qualitative, shape-based, timescale-independent time-domain transform used to extract local dynamics from sociotechnical time series—termed the Discrete Shocklet Transform (DST)—and an associated similarity search routine, the Shocklet Transform And Ranking (STAR) algorithm, that indicates time windows during which panels of time series display qualitatively-similar anomalous behavior. After distinguishing our algorithms from other methods used in anomaly detection and time series similarity search, such as the matrix profile, seasonal-hybrid ESD, and discrete wavelet transform-based procedures, we demonstrate the DST’s ability to identify mechanism-driven dynamics at a wide range of timescales and its relative insensitivity to functional parameterization. As an application, we analyze a sociotechnical data source (usage frequencies for a subset of words on Twitter) and highlight our algorithms’ utility by using them to extract both a typology of mechanistic local dynamics and a data-driven narrative of socially-important events as perceived by English-language Twitter
Artificial Intelligence and International Conflict in Cyberspace
This edited volume explores how artificial intelligence (AI) is transforming international conflict in cyberspace. Over the past three decades, cyberspace developed into a crucial frontier and issue of international conflict. However, scholarly work on the relationship between AI and conflict in cyberspace has been produced along somewhat rigid disciplinary boundaries and an even more rigid sociotechnical divide – wherein technical and social scholarship are seldomly brought into a conversation. This is the first volume to address these themes through a comprehensive and cross-disciplinary approach. With the intent of exploring the question ‘what is at stake with the use of automation in international conflict in cyberspace through AI?’, the chapters in the volume focus on three broad themes, namely: (1) technical and operational, (2) strategic and geopolitical and (3) normative and legal. These also constitute the three parts in which the chapters of this volume are organised, although these thematic sections should not be considered as an analytical or a disciplinary demarcation
Unraveling the Origin of Social Bursts in Collective Attention
In the era of social media, every day billions of individuals produce content in socio-technical systems resulting in a deluge of information. However, human attention is a limited resource and it is increasingly challenging to consume the most suitable content for one's interests. In fact, the complex interplay between individual and social activities in social systems overwhelmed by information results in bursty activity of collective attention which are still poorly understood. Here, we tackle this challenge by analyzing the online activity of millions of users in a popular microblogging platform during exceptional events, from NBA Finals to the elections of Pope Francis and the discovery of gravitational waves. We observe extreme fluctuations in collective attention that we are able to characterize and explain by considering the co-occurrence of two fundamental factors: the heterogeneity of social interactions and the preferential attention towards influential users. Our findings demonstrate how combining simple mechanisms provides a route towards understanding complex social phenomena