Nuria Oliver
Biographic Data
| ID | 4266908 |
|---|---|
| NAME | Nuria Oliver |
| GIVEN NAMES | Nuria |
| FAMILY NAME | Oliver |
| SIGNATURE | OLIVER N |
| AFFILIATIONS | ELLIS Alicante |
| ORCID | 0000-0001-5985-691X |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 7 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
Unconventional data, unprecedented insights: Leveraging non-traditional data during a pandemic
Introduction: The COVID-19 pandemic prompted new interest in non-traditional data sources to inform response efforts and mitigate knowledge gaps. While non-traditional data offers some advantages over traditional data, it also raises concerns related to biases, representativity, informed consent and security vulnerabilities. This study focuses on three specific types of non-traditional data: mobility, social media, and participatory surveillance …
Mirror, Mirror on the Wall, Who Is the Whitest of All? Racial Biases in Social Media Beauty Filters
Digital beauty filters are pervasive in social media platforms. Despite their popularity and relevance in the selfies culture, there is little research on their characteristics and potential biases. In this article, we study the existence of racial biases on the set of aesthetic canons embedded in social media beauty filters, which we refer to as the Beautyverse. First, we provide a historic contextualization of racial biases in beauty practices,…
Predicting Covid-19 pandemic waves including vaccination data with deep learning
Introduction: During the recent COVID-19 pandemics, many models were developed to predict the number of new infections. After almost a year, models had also the challenge to include information about the waning effect of vaccines and by infection, and also how this effect start to disappear. Methods: We present a deep learning-based approach to predict the number of daily COVID-19 cases in 30 countries, considering the non-pharmaceutical interven…
Covid-19 outbreaks analysis in the Valencian Region of Spain in the prelude of the third wave
Introduction: The COVID-19 pandemic has led to unprecedented social and mobility restrictions on a global scale. Since its start in the spring of 2020, numerous scientific papers have been published on the characteristics of the virus, and the healthcare, economic and social consequences of the pandemic. However, in-depth analyses of the evolution of single coronavirus outbreaks have been rarely reported. Methods: In this paper, we analyze the ma…
Give more data, awareness and control to individual citizens, and they will help Covid-19 containment
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the “phase 2” of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by…
Mobile phone data for informing public health actions across the Covid-19 pandemic life cycle
This paper describes how mobile phone data can guide government and public\nhealth authorities in determining the best course of action to control the\nCOVID-19 pandemic and in assessing the effectiveness of control measures such\nas physical distancing. It identifies key gaps and reasons why this kind of\ndata is only scarcely used, although their value in similar epidemics has\nproven in a number of use cases. It presents ways to overcome these…
Fair, Transparent, and Accountable Algorithmic Decision-making Processes: The Premise, the Proposed Solutions, and the Open Challenges
Mirror, Mirror on the Wall, Who Is the Whitest of All? Racial Biases in Social Media Beauty Filters
Digital beauty filters are pervasive in social media platforms. Despite their popularity and relevance in the selfies culture, there is little research on their characteristics and potential biases. In this article, we study the existence of racial biases on the set of aesthetic canons embedded in social media beauty filters, which we refer to as the Beautyverse. First, we provide a historic contextualization of racial biases in beauty practices,…
Fair, Transparent, and Accountable Algorithmic Decision-making Processes: The Premise, the Proposed Solutions, and the Open Challenges
Mobile phone data for informing public health actions across the Covid-19 pandemic life cycle
This paper describes how mobile phone data can guide government and public\nhealth authorities in determining the best course of action to control the\nCOVID-19 pandemic and in assessing the effectiveness of control measures such\nas physical distancing. It identifies key gaps and reasons why this kind of\ndata is only scarcely used, although their value in similar epidemics has\nproven in a number of use cases. It presents ways to overcome these…
Give more data, awareness and control to individual citizens, and they will help Covid-19 containment
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the “phase 2” of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by…
Covid-19 outbreaks analysis in the Valencian Region of Spain in the prelude of the third wave
Introduction: The COVID-19 pandemic has led to unprecedented social and mobility restrictions on a global scale. Since its start in the spring of 2020, numerous scientific papers have been published on the characteristics of the virus, and the healthcare, economic and social consequences of the pandemic. However, in-depth analyses of the evolution of single coronavirus outbreaks have been rarely reported. Methods: In this paper, we analyze the ma…
Predicting Covid-19 pandemic waves including vaccination data with deep learning
Introduction: During the recent COVID-19 pandemics, many models were developed to predict the number of new infections. After almost a year, models had also the challenge to include information about the waning effect of vaccines and by infection, and also how this effect start to disappear. Methods: We present a deep learning-based approach to predict the number of daily COVID-19 cases in 30 countries, considering the non-pharmaceutical interven…
Unconventional data, unprecedented insights: Leveraging non-traditional data during a pandemic
Introduction: The COVID-19 pandemic prompted new interest in non-traditional data sources to inform response efforts and mitigate knowledge gaps. While non-traditional data offers some advantages over traditional data, it also raises concerns related to biases, representativity, informed consent and security vulnerabilities. This study focuses on three specific types of non-traditional data: mobility, social media, and participatory surveillance …
Mirror, Mirror on the Wall, Who Is the Whitest of All? Racial Biases in Social Media Beauty Filters
Digital beauty filters are pervasive in social media platforms. Despite their popularity and relevance in the selfies culture, there is little research on their characteristics and potential biases. In this article, we study the existence of racial biases on the set of aesthetic canons embedded in social media beauty filters, which we refer to as the Beautyverse. First, we provide a historic contextualization of racial biases in beauty practices,…
Computer Science (7 works) · Business (4 works) · Medicine (4 works) · Pandemic (4 works) · COVID-19 Digital Contact Tracing (3 works) · COVID-19 epidemiological studies (3 works) · Political science (3 works) · Artificial Intelligence (2 works) · Computer security (2 works) · Data science (2 works)