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Gustavo Resende

dblp:227/0558 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 2 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 2 · 1 first-authorHuman-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational social science and digital humanities · 100%
Databases, data mining, and information retrieval
1 paper
Web and social media mining · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational social science and digital humanities › misinformation
misinformation spread
0.412019
(Mis)Information Dissemination in WhatsApp: Gathering, Analyzing and Countermeasures · WWW 2019
Web and social media mining
information diffusion
0.412019
(Mis)Information Dissemination in WhatsApp: Gathering, Analyzing and Countermeasures · WWW 2019

Methods — techniques the papers use, named apart from their topics

google search-based verification · 0.8automatic image labeling · 0.8
YearPublicationVenuePosition
2019 WhatsApp Monitor: A Fact-Checking System for WhatsApp
Philipe F. Melo, Johnnatan Messias, Gustavo Resende, Venkata Rama Kiran Garimella, Jussara M. Almeida, Fabrício Benevenuto
ICWSM3
2019 (Mis)Information Dissemination in WhatsApp: Gathering, Analyzing and Countermeasures
abstract
WhatsApp has revolutionized the way people communicate and interact. It is not only cheaper than the traditional Short Message Service (SMS) communication but it also brings a new form of mobile communication: the group chats. Such groups are great forums for collective discussions on a variety of topics. In particular, in events of great social mobilization, such as strikes and electoral campaigns, WhatsApp group chats are very attractive as they facilitate information exchange among interested people. Yet, recent events have raised concerns about the spreading of misinformation in WhatsApp. In this work, we analyze information dissemination within WhatsApp, focusing on publicly accessible political-oriented groups, collecting all shared messages during major social events in Brazil: a national truck drivers' strike and the Brazilian presidential campaign. We analyze the types of content shared within such groups as well as the network structures that emerge from user interactions within and cross-groups. We then deepen our analysis by identifying the presence of misinformation among the shared images using labels provided by journalists and by a proposed automatic procedure based on Google searches. We identify the most important sources of the fake images and analyze how they propagate across WhatsApp groups and from/to other Web platforms.
Gustavo Resende, Philipe F. Melo, Hugo Sousa, Johnnatan Messias, Marisa A. Vasconcelos, Jussara M. Almeida, Fabrício Benevenuto
WWW1