51.5SOC-PHMay 18
The NetMob26 Dataset: A High-Resolution Multi-Source View of Public Bus Mobility in NiteróiFelipe Domingos, Humberto T. Marques-Neto, Bruno Pereira et al.
The NetMob Data Challenge releases a comprehensive public transportation dataset from Niterói, addressing the lack of high-quality mobility and passenger demand data. Based on operational records from March 2026, the dataset combines four main sources: GPS telemetry from buses, approximately 7.2 million ticketing transactions, auxiliary transit data (routes, stops, and weather), and urban infrastructure and socio-demographic information. Together, these sources provide a detailed view of both transit supply and passenger demand. The data were preprocessed, cleaned, and anonymized to preserve privacy and improve reliability, including the removal of operational inconsistencies and anonymization of passenger identifiers. Access is restricted to challenge participants who accept the Terms and Conditions and sign an NDA. The paper describes the data collection and preprocessing pipeline, dataset organization, and mobility patterns observed in the system. The dataset supports research on topics such as public transportation efficiency, demand forecasting, accessibility analysis, service reliability, and the influence of external factors like weather on urban mobility.
SIAug 17, 2018
Characterizing the public perception of WhatsApp through the lens of mediaJosemar Alves Caetano, Gabriel Magno, Evandro Cunha et al.
WhatsApp is, as of 2018, a significant component of the global information and communication infrastructure, especially in developing countries. However, probably due to its strong end-to-end encryption, WhatsApp became an attractive place for the dissemination of misinformation, extremism and other forms of undesirable behavior. In this paper, we investigate the public perception of WhatsApp through the lens of media. We analyze two large datasets of news and show the kind of content that is being associated with WhatsApp in different regions of the world and over time. Our analyses include the examination of named entities, general vocabulary, and topics addressed in news articles that mention WhatsApp, as well as the polarity of these texts. Among other results, we demonstrate that the vocabulary and topics around the term "whatsapp" in the media have been changing over the years and in 2018 concentrate on matters related to misinformation, politics and criminal scams. More generally, our findings are useful to understand the impact that tools like WhatsApp play in the contemporary society and how they are seen by the communities themselves.