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Human migration the big data perspective
How can big data help to understand the migration phenomenon? In this paper, we try to answer this question through an analysis of various phases of migration, comparing...-
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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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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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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... -
Explanation in artificial intelligence. Insights from the social sciences
There has been a recent resurgence in the area of explainable artificial intelligence as researchers and practitioners seek to provide more transparency to their algorithms.... -
Modeling Adversarial Behavior Against Mobility Data Privacy
Privacy risk assessment is a crucial issue in any privacy-aware analysis process. Traditional frameworks for privacy risk assessment systematically generate the assumed...-
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Seeing without knowing. Limitations of transparency and its application to al...
Models for understanding and holding systems accountable have long rested upon ideals and logics of transparency. Being able to see a system is sometimes equated with being able... -
Solving the Black Box Problem. A Normative Framework for Explainable Artifici...
Many of the computing systems programmed using Machine Learning are opaque: it is difficult to know why they do what they do or how they work. Explainable Artificial... -
Toward Accountable Discrimination Aware Data Mining
"Big Data" and data-mined inferences are affecting more and more of our lives, and concerns about their possible discriminatory effects are growing. Methods for... -
GLocalX-From Local to Global Explanations of Black Box AI Models
Artificial Intelligence (AI) has come to prominence as one of the major components of our society, with applications in most aspects of our lives. In this field, complex and...-
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Fair Prediction with Disparate Impact A Study of Bias in Recidivism Predictio...
Recidivism prediction instruments (RPIs) provide decision-makers with an assessment of the likelihood that a criminal defendant will reoffend at a future point in time....