| Predicting misinformation and engagement in covid-19 twitter discourse in the first months of the outbreak M Silva, F Ceschin, P Shrestha, C Brant, J Fernandes, CS Silva, A Grégio, ... arXiv preprint arXiv:2012.02164, 2020 | 27 | 2020 |
| Predicting different types of subtle toxicity in unhealthy online conversations S Gilda, L Giovanini, M Silva, D Oliveira Procedia Computer Science 198, 360-366, 2022 | 20 | 2022 |
| What makes disinformation ads engaging? A case study of Facebook ads from the Russian active measures campaign M Silva, L Giovanini, J Fernandes, D Oliveira, CS Silva Journal of Interactive Advertising 23 (3), 221-240, 2023 | 7 | 2023 |
| Lumen: A machine learning framework to expose influence cues in texts H Shi, M Silva, L Giovanini, D Capecci, L Czech, J Fernandes, D Oliveira Frontiers in Computer Science 4, 929515, 2022 | 6 | 2022 |
| Facebook ad engagement in the russian active measures campaign of 2016 M Silva, L Giovanini, J Fernandes, D Oliveira, CS Silva arXiv preprint arXiv:2012.11690, 2020 | 5 | 2020 |
| Brazilian favela women: how your standard solutions for technology abuse might actually harm them M Silva, D Oliveira arXiv preprint arXiv:2101.09257, 2021 | 3 | 2021 |
| People Still Care About Facts: Twitter Users Engage More with Factual Discourse than Misinformation--A Comparison Between COVID and General Narratives on Twitter M Silva, F Ceschin, P Shrestha, C Brant, S Gilda, J Fernandes, CS Silva, ... arXiv preprint arXiv:2012.02164, 2020 | 1 | 2020 |
| Computer Users Have Unique Yet Temporally Inconsistent Computer Usage Profiles. L Giovanini, F Ceschin, M Silva, A Chen, R Kulkarni, S Banda, M Lysaght, ... CoRR, 2021 | | 2021 |
Luiz GiovaniniUniversity of Florida; PUCPRVerified email at ufl.edu
