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For centuries quality of life was a subject of studies across different disciplines. However, only with the emergence of a digital era, it became possible to investigate this topic on a larger scale. Over time it became clear that quality…

Generating value from data requires the ability to find, access and make sense of datasets. There are many efforts underway to encourage data sharing and reuse, from scientific publishers asking authors to submit data alongside manuscripts…

As urban populations grow, the need for accessible urban design has become urgent. Traditional survey methods for assessing public perceptions of accessibility are often limited in scope. Crowdsourcing via online reviews offers a valuable…

Dengue is a major threat to public health in Brazil, the world's sixth biggest country by population, with over 1.5 million cases recorded in 2019 alone. Official data on dengue case counts is delivered incrementally and, for many reasons,…

Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data…

Gross domestic product (GDP) is an important economic indicator that aggregates useful information to assist economic agents and policymakers in their decision-making process. In this context, GDP forecasting becomes a powerful decision…

Dry eye disease (DED) affects approximately half of the United States population. DED is characterized by dryness on the corena surface due to a variety of causes. This study fills the spatiotemporal gaps in DED epidemiology by using Google…

Using the new data from the OECD-WTO world network of economic activities we construct the Google matrix $G$ of this directed network and perform its detailed analysis. The network contains 58 countries and 37 activity sectors for years…

We present three case studies of organizations using a data science competition to answer a pressing question. The first is in education where a nonprofit that creates smart school budgets wanted to automatically tag budget line items. The…

The paper considers an approach of using Google Search API and GPT-4o model for qualitative and quantitative analyses of news through retrieval-augmented generation (RAG). This approach was applied to analyze news about the 2024 US…

Search engine results often misalign with users' goals due to opaque algorithms, leading to unhelpful or detrimental information consumption. To address this, we developed a Google Chrome plugin that provides "content labels" for webpages…

Scientific studies of society increasingly rely on digital traces produced by various aspects of human activity. In this paper, we use a relatively unexplored source of data, anonymized records of bank card transactions collected in Spain…

We consider the problem of personalization of online services from the viewpoint of ad targeting, where we seek to find the best ad categories to be shown to each user, resulting in improved user experience and increased advertisers'…

The Internet of Things adoption in the manufacturing industry allows enterprises to monitor their electrical power consumption in real time and at machine level. In this paper, we follow up on such emerging opportunities for data…

Federated analytics has many applications in edge computing, its use can lead to better decision making for service provision, product development, and user experience. We propose a Bayesian approach to trend detection in which the…

Machine learning algorithms can now outperform classic economic models in predicting quantities ranging from bargaining outcomes, to choice under uncertainty, to an individual's future jobs and wages. Yet this predictive accuracy comes at a…

Prior work on personalized recommendations has focused on exploiting explicit signals from user-specific queries, clicks, likes, and ratings. This paper investigates tapping into a different source of implicit signals of interests and…

Using machine learning and alternative data for the prediction of financial markets has been a popular topic in recent years. Many financial variables such as stock price, historical volatility and trade volume have already been through…

Internet data has surfaced as a primary source for investigation of different aspects of human behavior. A crucial step in such studies is finding a suitable cohort (i.e., a set of users) that shares a common trait of interest to…

Today, web-based companies use user data to provide and enhance services to users, both individually and collectively. Some also analyze user data for other purposes, for example to select advertisements or price offers for users. Some even…