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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... -
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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Change of direction asymmetry across different age categories in youth soccer
Background: In youth, the development of change of direction (COD) and sprint performance is a key component for successfully competing in soccer across age. During a COD, the...-
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Error Estimation of Ultra-Short Heart Rate Variability Parameters: Effect of ...
Application of ultra–short Heart Rate Variability (HRV) is desirable in order to increase the applicability of HRV features to wrist-worn wearable devices equipped with heart...-
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Volleyball-Specific Skills and Cognitive Functions Can Discriminate Players o...
Formenti, D, Trecroci, A, Duca, M, Vanoni, M, Ciovati, M, Rossi, A, and Alberti, G. Volleyball-specific skills and cognitive functions can discriminate players of different...-
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Automatic pass annotation from soccer VideoStreams based on object detection ...
Soccer analytics is attracting increasing interest in academia and industry, thanks to the availability of data that describe all the spatio-temporal events that occur in each...-
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A dataset of journalists on Twitter
This dataset comprises the Twitter timelines of journalists belonging to 17 different countries from 8 different continental regions, downloaded in May 2018. We used the Twitter...-
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Polarizing opinion vectors with the Friedkin-Johnsen Model
This code contains two Mathematica notebooks to find the polarizing opinion vectors given the social graph and the nodes’ susceptibility. The notebooks have to be saved in the...-
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Dynamics of cascades on burstiness-controlled temporal networks
Burstiness, the tendency of interaction events to be heterogeneously distributed in time, is critical to information diffusion in physical and social systems. However, an...-
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The role of bot squads in the political propaganda on Twitter
Nowadays, Social Media are a privileged channel for news spreading, information exchange, and fact checking. Unexpectedly for many users, automated accounts, known as social...-
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A decade of social bot detection
Bots increasingly tamper with political elections and economic discussions. Tracing trends in detection strategies and key suggestions on how to win the fight.-
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Measuring the Impact of Readability Features in Fake News Detection
The proliferation of fake news is a current issue that influences a number of important areas of society, such as politics, economy and health. In the Natural Language...-
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Comparing Topic-Aware Neural Networks for Bias Detection of News
The commercial pressure on media has increasingly dominated the institutional rules of news media, and consequently, more and more sensational and dramatized frames and biases...-
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Grounds for Trust. Essential Epistemic Opacity and Computational Reliabilism
Several philosophical issues in connection with computer simulations rely on the assumption that results of simulations are trustworthy. Examples of these include the debate... -
How the machine thinks. Understanding opacity in machine learning algorithms
This article considers the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud... -
Evaluating local explanation methods on ground truth
Evaluating local explanation methods is a difficult task due to the lack of a shared and universally accepted definition of explanation. In the literature, one of the most...-
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Machine Learning Explainability Via Microaggregation and Shallow Decision Trees
Artificial intelligence (AI) is being deployed in missions that are increasingly critical for human life. To build trust in AI and avoid an algorithm-based authoritarian...