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Disease Twitter Dataset
This Twitter dataset covers two recent outbreaks: Ebola and Zika. About 60 million tweets were collected through a query-based access to the Twitter Streaming API, covering... -
Food consumption data at the canteens of University of Pisa
A dataset storing all the meals consumed by students at the canteen of University of Pisa during a six years-long period. -
Retail Market Data
This dataset contains Retail Market Data about food products, from 2007, for about 130 shops of an Italian Distribution chain. Data are of about 1 M of Active Clients, and... -
European Banks Asset Class exposures
This is a curated dataset, where the Original data are taken from European Banking Authority (EBA), who collects banks' data to perform stress-test systemic risk analysis....-
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UNI Fake Giveaway Dataset
Dataset and study related to a scam originated on Twitter that lured users into sending their Uniswap (UNI) tokens to a fake giveaway.-
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Russell 3000 stock prices
This dataset contains the price and volume of the 3000 stocks belonging to the Russell 3000 Index, roughly corresponding to the 3000 more capitalized stocks. Traded volume and... -
Formal network of Estonian companies and board members
This dataset consists of managed and continuously updated data about Estonian companies and board members since 1994. Technical documentation of data structures and the REST API... -
Estonian public sector electronic services and service providers and consumers
The dataset contains records of electronic services (aka X-Road services), service providers and consumers harvested in April 2014 from RIHA (https://riha.eesti.ee). The data... -
Estimating countries' peace index with GDELT
We use news media attention from the Global Data of Events, Location and Tone (GDELT) database, as a proxy for estimating Global Peace Index (GPI), to complement the knowledge... -
Ground truth evaluation of home location detection algorithms
Inferring mobile phone users' home location, i.e., assigning a location in space to a user based on data generated by the mobile phone network, is a central task in leveraging... -
TARS based prediction for Next Basket
Nowadays, a hot challenge for supermarket chains is to offer personalized services to their customers. Market basket prediction, i.e., supplying the customer a shopping list... -
DebtRank Systemic Risk Estimation Method
The DebtRank algorithm is used to estimate the impact of shocks in financial networks, as it overcomes the limitations of the traditional default-cascade approaches.The method... -
Estimating Collective Wellbeing
This method estimates the wellbeing of a country by using an alternative measure to GDP. The proposed measure is the average sophistication of the satisfiable needs of a...-
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Influence of missing RR-Intervals caused by motion artifacts on HRV features ...
Wearable physiological monitors have become increasingly popular, often worn during people’s daily life, collecting data 24 hours a day, 7 days a week. In the last decade,... -
Nowcasting well-being with human mobility data
This method describes an analytical framework to nowcast well-being by using mobility measures extracted from mobile phone data. -
Why Are Learned Indexes So Effective
A recent trend in algorithm design consists of augmenting classic data structures with machine learning models, which are better suited to reveal and exploit patterns and trends... -
Estimating countries’ peace index through the lens of the world news as monit...
Peacefulness is a principal dimension of well-being, and its measurement has lately drawn the attention of researchers and policy-makers. During the last years, novel digital...-
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Measuring objective and subjective well-being dimensions and data sources
Well-being is an important value for people’s lives, and it could be considered as an index of societal progress. Researchers have suggested two main approaches for the...-
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