Related papers: From Social Data Mining to Forecasting Socio-Econo…
Social media have the potential to provide timely information about emergency situations and sudden events. However, finding relevant information among millions of posts being posted every day can be difficult, and developing a data…
Machine learning systems require representations of the real world for training and testing - they require data, and lots of it. Collecting data at scale has logistical and ethical challenges, and synthetic data promises a solution to these…
Social networks have been widely studied over the last century from multiple disciplines to understand societal issues such as inequality in employment rates, managerial performance, and epidemic spread. Today, these and many more issues…
A multidimensional financial system could provide benefits for individuals, companies, and states. Instead of top-down control, which is destined to eventually fail in a hyperconnected world, a bottom-up creation of value can unleash…
There is considerable interest in developing techniques for predicting human behavior, for instance to enable emerging contentious situations to be forecast or the nature of ongoing but hidden activities to be inferred. A promising approach…
Technological progress has led to powerful computers and communication technologies that penetrate nowadays all areas of science, industry and our private lives. As a consequence, all these areas are generating digital traces of data…
Context: Data mining techniques have demonstrated to be a powerful technique for discovering insights hidden in data from a domain. However, these techniques demand very specialised skills. People willing to analyse data often lack these…
Small and Medium Enterprises (SMEs) now generate digital data at an unprecedented rate from online transactions, social media marketing and associated customer interactions, online product or service reviews and feedback, clinical…
Calls for heightened consideration of fairness and accountability in algorithmically-informed public decisions---like taxation, justice, and child protection---are now commonplace. How might designers support such human values? We…
The modeling of complex systems such as ecological or socio-economic systems can be very challenging. Although various modeling approaches exist, they are generally not compatible and mutually consistent, and empirical data often do not…
Synthetic datasets have long been thought of as second-rate, to be used only when "real" data collected directly from the real world is unavailable. But this perspective assumes that raw data is clean, unbiased, and trustworthy, which it…
The change-point detection problem seeks to identify distributional changes in streams of data. Increasingly, tools for change-point detection are applied in settings where data may be highly sensitive and formal privacy guarantees are…
The exponential increase of availability of digital data and the necessity to process it in business and scientific fields has literally forced upon us the need to analyze and mine useful knowledge from it. Traditionally data mining has…
Data Science research is undergoing a revolution fueled by the transformative power of technology, the Internet, and an ever increasing computational capacity. The rate at which sophisticated algorithms can be developed is unprecedented,…
In today's business landscape, organizations need to find the right balance between using their customers' data ethically to power AI solutions and being compliant regarding data privacy and data usage regulations. In this paper, we discuss…
The information age is also an era of escalating social problems. The digital transformation of society and the economy is already underway in all countries, although the progress in this transformation can vary widely. There are more…
Cloud computing can and does mean different things to different people. The common characteristics most shares are on-demand secure access to metered services from nearly anywhere and dislocation of data from inside to outside the…
Disaster management demands a near real-time information dissemina-tion so that the emergency services can be provided to the right people at the right time. Recent advances in information and communication technologies enable collection of…
Artificial intelligence (AI) is advancing exponentially and is likely to have profound impacts on human wellbeing, social equity, and environmental sustainability. Here we argue that the "alignment problem" in AI research is also an…
The idea of an open data market envisions the creation of a data trading model to facilitate exchange of data between different parties in the Internet of Things (IoT) domain. The data collected by IoT products and solutions are expected to…