EDBT 2026 Demo / reviewers in the wild / expert
Patricia Takako Endo
dblp:18/8101
· DBLP profile ↗
4ranked-venue papers in the field
0as first author
4since 2021 · last 2024
0000-0002-9163-5583ORCID · verified
Domains — venue-derived; a paper can count in several
Data Mining & Knowledge Discovery · 2Information Retrieval & Web Search · 1Business Process & Enterprise Data · 1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Categorising Corruption in the Vaccine Discourse: A General Taxonomy, Data Set, and Evaluation of LLMs for Classifying Corruption Dialogue in Social Media
Vitor Gaboardi Dos Santos, Guto Leoni Santos, Antonia Egli, Estatira Kahvazadeh, Bill Doolin, Patricia Takako Endo, Theo Lynn |
ASONAM (1) | 6 |
| 2024 | Detecting Homophobic Speech in Soccer Tweets Using Large Language Models and Explainable AI
Guto Leoni Santos, Vitor Gaboardi Dos Santos, Colm Kearns, Gary Sinclair, Jack Black, Mark Doidge, Thomas Fletcher, Dan Kilvington, Katie Liston, Patricia Takako Endo, Theo Lynn |
ASONAM (1) | 10 |
| 2024 | Kicking Prejudice: Large Language Models for Racism Classification in Soccer Discourse on Social Media
Guto Leoni Santos, Vitor Gaboardi Dos Santos, Colm Kearns, Gary Sinclair, Jack Black, Mark Doidge, Thomas Fletcher, Dan Kilvington, Patricia Takako Endo, Katie Liston, Theo Lynn |
CAiSE | 9 |
| 2022 | Examining the determinants of acceptance and use of mobile contact tracing applications in Brazil: An extended privacy calculus perspectiveabstractAbstract Mobile contact tracing applications have emerged as a potential solution to track and reduce the transmission of viruses such as Covid‐19. These applications require the disclosure of potentially sensitive personal information thus generating understandable implications for personal privacy. This research aims to determine the factors driving acceptance of these applications, with acceptance represented by three distinct variables, namely usage intentions, willingness to disclose personal data, and willingness to rely on health advice. The study examines the influence of perceived privacy, social influence, and benefits on acceptance of contact tracing applications among a sample of 1,114 Brazilian citizens. The study leverages social contract theory to demonstrate the importance of perceived control and perceived surveillance in the formation of individuals' perceptions of privacy. Integrating privacy calculus theory with social contract theory to include reciprocity and social influence, our findings suggest that perceived privacy, reciprocal benefits, and social influence all positively influence individuals' intentions to download or continue the use of contact tracing applications, while intentions to disclose information are influenced by adoption intentions, perceived privacy, and reciprocal benefits and individuals' willingness to rely on contact tracing applications for health advice is influenced by reciprocal benefits and disclosure intentions. Grace Fox, Lisa van der Werff, Pierangelo Rosati, Patricia Takako Endo, Theo Lynn |
J. Assoc. Inf. Sci. Technol. | 4 |