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Diogo Cortiz

Publications and source records attributed to Diogo Cortiz.

6 recordsLinked to original sources
arXiv2025

Who shapes Web standards? Uncovering the main topics of interest in the W3C

This paper identifies the primary topics of interest of organizations participating in the World Wide Web Consortium (W3C), the leading standards body for the Web. Using publicly available data from the W3C website, we analyze the participation of member organizations in W3C groups, treating the number of representatives allocated to each group as a proxy for their interests. By applying topic modeling and similarity analysis to these participation patterns, we uncover clusters of related groups and shared priorities among organizations. The results reveal five prominent areas of focus -- Web, Ads & Privacy; High Performance; Credentials & Web of Things; Accessibility; and Payments -- and show that large enterprises, particularly those based in the United States, dominate participation in core Web development and advertising-related topics, while Japanese organizations are more active in the Web of Things. These findings offer insights into how various stakeholders influence the standardization process and how the Web may evolve in the coming years.

cs.CY↗
arXiv2024

A Bayesian framework for measuring association and its application to emotional dynamics in Web discourse

This paper introduces a Bayesian framework designed to measure the degree of association between categorical random variables. The method is grounded in the formal definition of variable independence and is implemented using Markov Chain Monte Carlo (MCMC) techniques. Unlike commonly employed techniques in Association Rule Learning, this approach enables a clear and precise estimation of confidence intervals and the statistical significance of the measured degree of association. We applied the method to non-exclusive emotions identified by annotators in 4,613 tweets written in Portuguese. This analysis revealed pairs of emotions that exhibit associations and mutually opposed pairs. Moreover, the method identifies hierarchical relations between categories, a feature observed in our data, and is utilized to cluster emotions into basic-level groups.

stat.AP↗
arXiv2021

A Weakly Supervised Dataset of Fine-Grained Emotions in Portuguese

Affective Computing is the study of how computers can recognize, interpret and simulate human affects. Sentiment Analysis is a common task inNLP related to this topic, but it focuses only on emotion valence (positive, negative, neutral). An emerging approach in NLP is Emotion Recognition, which relies on fined-grained classification. This research describes an approach to create a lexical-based weakly supervised corpus for fine-grained emotion in Portuguese. We evaluated our dataset by fine-tuning a transformer-based language model (BERT) and validating it on a Gold Standard annotated validation set. Our results (F1-score=.64) suggest lexical-based weak supervision as an appropriate strategy for initial work in low resourced environment.

cs.CL↗
arXiv2021

Game Design for Blockchain Learning

Blockchain is a new technological approach that has gained popularity on the market due to its application in several areas such as education, health, security, and smart cities, among others. However, understanding how blockchain works is not easy at first, especially for non-technical people, because it relies on a non-trivial computational process. We have developed a game board - called Blocktrain - whose game mechanics are based on the blockchain processing model. This game gives people the opportunity to learn key blockchain concepts while playing. In this paper, we describe the game design process and assessment of the game as pedagogical instrument.

cs.HC↗