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Found 19 papers, 10 papers with code
Data-driven generation of spatio-temporal routines in human mobility
DITRAS operates in two steps: the generation of a mobility diary and the translation of the mobility diary into a mobility trajectory.
Quantifying the relation between performance and success in soccer
The availability of massive data about sports activities offers nowadays the opportunity to quantify the relation between performance and success.
Effective injury forecasting in soccer with GPS training data and machine learning
Injuries have a great impact on professional soccer, due to their large influence on team performance and the considerable costs of rehabilitation for players.
Human Perception of Performance
Humans are routinely asked to evaluate the performance of other individuals, separating success from failure and affecting outcomes from science to education and sports.
PlayeRank: data-driven performance evaluation and player ranking in soccer via a machine learning approach
The problem of evaluating the performance of soccer players is attracting the interest of many companies and the scientific community, thanks to the availability of massive data capturing all the events generated during a match (e. g., tackles, passes, shots, etc.).
Open the Black Box Data-Driven Explanation of Black Box Decision Systems
We introduce the local-to-global framework for black box explanation, a novel approach with promising early results, which paves the road for a wide spectrum of future developments along three dimensions: (i) the language for expressing explanations in terms of highly expressive logic-based rules, with a statistical and causal interpretation; (ii) the inference of local explanations aimed at revealing the logic of the decision adopted for a specific instance by querying and auditing the black box in the vicinity of the target instance; (iii), the bottom-up generalization of the many local explanations into simple global ones, with algorithms that optimize the quality and comprehensibility of explanations.
Scikit-mobility: a Python library for the analysis, generation and risk assessment of mobility data
The last decade has witnessed the emergence of massive mobility data sets, such as tracks generated by GPS devices, call detail records, and geo-tagged posts from social media platforms.
Physics and Society
Automatic Pass Annotation from Soccer VideoStreams Based on Object Detection and LSTM
In this paper, we describe PassNet, a method to recognize the most frequent events in soccer, i. e., passes, from video streams.
An individual-level ground truth dataset for home location detection
Home detection, assigning a phone device to its home antenna, is a ubiquitous part of most studies in the literature on mobile phone data.
Computers and Society Physics and Society
Deep Gravity: enhancing mobility flows generation with deep neural networks and geographic information
The movements of individuals within and among cities influence critical aspects of our society, such as well-being, the spreading of epidemics, and the quality of the environment.
A Survey on Deep Learning for Human Mobility
The study of human mobility is crucial due to its impact on several aspects of our society, such as disease spreading, urban planning, well-being, pollution, and more.
Explaining the difference between men's and women's football
Women's football is gaining supporters and practitioners worldwide, raising questions about what the differences are with men's football.
Applications
An interactive dashboard for searching and comparing soccer performance scores
The performance of soccer players is one of most discussed aspects by many actors in the soccer industry: from supporters to journalists, from coaches to talent scouts.
Understanding peacefulness through the world news
Thus, its measurement has drawn the attention of researchers, policymakers, and peacekeepers.
Coach2vec: autoencoding the playing style of soccer coaches
Capturing the playing style of professional soccer coaches is a complex, and yet barely explored, task in sports analytics.
Generating Synthetic Mobility Networks with Generative Adversarial Networks
We conduct extensive experiments on public datasets of bike and taxi rides to show that MoGAN outperforms the classical Gravity and Radiation models regarding the realism of the generated networks.
Trajectory Test-Train Overlap in Next-Location Prediction Datasets
Next-location prediction, consisting of forecasting a user's location given their historical trajectories, has important implications in several fields, such as urban planning, geo-marketing, and disease spreading.
Enhancing crowd flow prediction in various spatial and temporal granularities
We propose CrowdNet, a solution to crowd flow prediction based on graph convolutional networks.
Social AI and the Challenges of the Human-AI Ecosystem
In order to understand the impact of AI on socio-technical systems and design next-generation AIs that team with humans to help overcome societal problems rather than exacerbate them, we propose to build the foundations of Social AI at the intersection of Complex Systems, Network Science and AI.
