Ana Valdivia

University of Oxford | OX · Oxford Internet Institute

The proliferation of biometric systems in our societies is shaping public debates around its political, social and ethical implications. Yet, whilst concerns towards the racialised use of this technology have been on the rise, the field of biometrics remains unperturbed by these debates. Despite the lack of critical analysis, algorithmic fairness h...

In 2020, the European Union announced the award of the contract for the biometric part of the new database for border control, the Entry Exit System, to two companies: IDEMIA and Sopra Steria. Both companies had been previously involved in the development of databases for border and migration management. While there has been a growing amount of pub...

On the 13th of January 2022, a Spanish Administrative court ruled in favour of algorithmic opacity. Fundación Civio, an independent foundation that monitors and accounts public authorities, reported that an algorithm used by the government was committing errors.1) BOSCO, the name of the application which contained the algorithm, was implemented by...

Since 2010, the output of a risk assessment tool that predicts how likely an individual is to commit severe violence against their partner has been integrated within the Basque country courtrooms. The EPV-R, the tool developed to assist police officers during the assessment of gender-based violence cases, was also incorporated to assist the decisio...

In 2019, the UK's Immigration and Asylum Chamber of the Upper Tribunal dismissed an asylum appeal basing the decision on the output of a biometric system, alongside other discrepancies. The fingerprints of the asylum seeker were found in a biometric database which contradicted the appellant's account. The Tribunal found this evidence unequivocal an...

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists' gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instanc...

Fair machine learning has been focusing on the development of equitable algorithms that address discrimination. Yet, many of these fairness‐aware approaches aim to obtain a unique solution to the problem, which leads to a poor understanding of the statistical limits of bias mitigation interventions. In this study, a novel methodology is presented t...

Fair machine learning works have been focusing on the development of equitable algorithms that address discrimination of certain groups. Yet, many of these fairness-aware approaches aim to obtain a unique solution to the problem, which leads to a poor understanding of the statistical limits of bias mitigation interventions. We present the first met...

Aspect-based sentiment analysis enables the extraction of fine-grained information, as it connects specific aspects that appear in reviews with a polarity. Although we detect that the information from these algorithms is very accurate at local level, it does not contribute to obtain an overall understanding of reviews. To fill this gap, we propose...

Currently, a plethora of industrial and academic sentiment analysis methods for classifying the opinion polarity of a text are available and ready to use. However, each of those methods have their strengths and weaknesses, due mainly to the approach followed in their design (supervised/unsupervised) or the domain of text used in their development....

A particular challenge in Natural Language Processing is the disambiguation of polysemic words. The great availability, diversity and the speed of changing of the data from on-line sources force the development of disambiguation systems with a reduced dependency on linguistic resources. We argue that the contextual neural encoding of a specific ent...

TripAdvisor is an opinion source frequently used in Sentiment Analysis. On this social network, users explain their experiences in hotels, restaurants or touristic attractions. They write texts of 200 character minimum and score the overall of their review with a numeric scale that ranks from 1 (Terrible) to 5 (Excellent). In this work, we aim that...

Problem definition: Attendance at a museum fluctuates over time and is largely dependent on the exhibitions on display. Schedules can be adjusted to maximize the museum's objectives. Academic/practical relevance: In this paper, we build a model to study and manage the impact of exhibitions on the number of museum visitors. Methodology: We first est...

Recently, interest in sentiment analysis has grown exponentially. Many studies have developed a wide variety of algorithms capable of classifying texts according to the sentiment conveyed in them. Such sentiment is usually expressed as positive, neutral or negative. However, neutral reviews are often ignored in many sentiment analysis problems beca...

The number of online reviews has grown exponentially over the last years. As a result, several Sentiment Analysis Methods (SAMs) have been developed in order to extract automatically sentiments from text. In this work, we study polarity coherencies between reviewers and SAMs. To do so, we compare the polarity of the document evaluated by the user a...

Web platforms such as TripAdvisor allow tourists to describe their experiences with hotels, restaurants, and other tourist attractions. This article proposes TripAdvisor as a source of data for sentiment analysis tasks. The authors develop an analysis for studying the matching between users’ sentiments and automatic sentiment-detection algorithms....