Analyzing the Role of Negativity in Brazilian Reddit Discussions
Resumo
Online discussions are increasingly organized as discussion cascades, where users interact through sequences of replies that can grow into large, complex conversational structures. While prior work has studied sentiment, toxicity, and user behavior in online communities, less is known about how negativity relates simultaneously to discussion structure, user interaction, and language. We investigate the role of negativity in Brazilian Reddit discussion cascades, analyzing over one million comments from 20 subreddits. Using a transformer-based sentiment classifier, we group cascades and users into quartiles by the proportion of negative comments, and examine structural, interactional, and linguistic patterns across negativity levels. Negativity is associated with multiple dimensions of discussion dynamics, but its effects are consistently non-monotonic: cascades grow larger, deeper, and more viral as negativity rises up to moderately high levels, then contract sharply at the highest levels. Homophily follows the same pattern, peaking among moderately negative users, who occupy a central position in the interaction network, while the most negative users show low homophily and interact mainly with moderately negative peers. Linguistically, negative discussions show a steady rise in angerrelated and conflict-oriented language, while thematic diversity peaks at moderate negativity and declines at both extremes. These findings indicate that negativity is not a simple linear driver of engagement: moderate negativity sustains the largest, most cohesive, and most diverse discussions, whereas extreme negativity is reflected mainly in hostile language rather than structural or social amplification. This distinction has direct implications for content moderation and community health monitoring, as platforms that focus exclusively on the most extreme content may overlook the moderately negative, high-engagement core that sustains much of the conversational activity.
Palavras-chave:
Negativity, Reddit, Sentiment Analysis, Discussion Cascades, Homophily, Thematic Diversity
Referências
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Pedro Bento, Yan Aquino, Arthur Buzelin, Pedro Robles Dutenhefner, Arthur Chagas, Victoria Estanislau, Lucas Dayrell, Samira Malaquias, Caio Santana, Marcelo Sartori Locatelli, Gisele L. Pappa,Wagner Meira Jr., and Virgilio Almeida. 2025. Mapping Hate and Extremism: How Brazilian Reddit Communities Spread Toxic Discourse. In Proceedings of the International AAAI Conference on Web and Social Media (ICWSM ’25). AAAI. DOI: 10.36190/2025.18
Carmela Bernardo, Dora Ricci, and Francesco Vasca. 2026. Homophily Detection in Opinion Dynamics from Reddit Discussions. In Advances in Social Networks Analysis and Mining, I-Hsien Ting, Panagiotis Karampelas, Min-Yuh Day, and Reda Alhajj (Eds.). Springer Nature Switzerland, Cham, 251–262.
Josemar A. Caetano, Hélder S. Lima, Mateus F. Santos, and Humberto T. Marques-Neto. 2018. Using sentiment analysis to define twitter political users’ classes and their homophily during the 2016 American presidential election. Journal of Internet Services and Applications 9, 1 (2018), 18. DOI: 10.1186/s13174-018-0089-0
Josemar Alves Caetano, Gabriel Magno, Marcos Gonçalves, Jussara Almeida, Humberto T. Marques-Neto, and Virgílio Almeida. 2019. Characterizing Attention Cascades in WhatsApp Groups. In Proceedings of the 10th ACM Conference on Web Science (WebSci ’19). Association for Computing Machinery, New York, NY, USA, 27–36. DOI: 10.1145/3292522.3326018
Flavio Carvalho, Rafael Rodrigues, Gabriel Santos, Pedro Cruz, Lilian Ferrari, and Gustavo Guedes. 2019. Avaliação da versão em português do LIWC Lexicon 2015 com análise de sentimentos em redes sociais. In Anais do VIII Brazilian Workshop on Social Network Analysis and Mining (Belém). SBC, Porto Alegre, RS, Brasil, 24–34. DOI: 10.5753/brasnam.2019.6545
Baitong Chen, Satoshi Tsutsui, Ying Ding, and Feicheng Ma. 2017. Understanding the topic evolution in a scientific domain: An exploratory study for the field of information retrieval. Journal of Informetrics 11, 4 (2017), 1175–1189. DOI: 10.1016/j.joi.2017.10.003
Matteo Cinelli, Gianmarco De Francisci Morales, Alessandro Galeazzi, Walter Quattrociocchi, and Michele Starnini. 2021. The echo chamber effect on social media. Proceedings of the National Academy of Sciences 118, 9 (2021), e2023301118. DOI: 10.1073/pnas.2023301118
Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Jiatao Ji, Guillaume Agrawal, Francisco Guzman, Rahul Goyal, Ritesh Kumar, Myle Ott, et al. 2019. Unsupervised cross-lingual representation learning at scale. arXiv preprint arXiv:1911.02116 (2019).
Ringki Das and Thoudam Doren Singh. 2023. Multimodal sentiment analysis: A survey of methods, trends, and challenges. Comput. Surveys 55, 13s (2023), 1–38.
Antônio Pereira De Souza Júnior, Pablo Cecilio, Felipe Viegas,Washington Cunha, Elisa Tuler De Albergaria, and Leonardo Chaves Dutra Da Rocha. 2022. Evaluating Topic Modeling Pre-processing Pipelines for Portuguese Texts. In Proceedings of the Brazilian Symposium on Multimedia and the Web (Curitiba, Brazil) (WebMedia ’22). Association for Computing Machinery, New York, NY, USA, 191–201. DOI: 10.1145/3539637.3557052
Sharad Goel, Ashton Anderson, Jake Hofman, and Duncan J. Watts. 2016. The Structural Virality of Online Diffusion. Management Science (2016). DOI: 10.1287/mnsc.2015.2158
Maarten Grootendorst. 2022. BERTopic: Neural topic modeling with a class-based TF-IDF procedure. DOI: 10.48550/ARXIV.2203.05794
Winston Haynes. 2013. Bonferroni Correction. Springer New York, New York, NY, 154–154. DOI: 10.1007/978-1-4419-9863-7_1213
Jack Hessel, Lillian Lee, and David Mimno. 2017. Cats and Captions vs. Creators and the Clock: Comparing Multimodal Content to Context in Predicting Relative Popularity. In Proceedings of the 26th International Conference on World Wide Web (WWW ’17). International World Wide Web Conferences Steering Committee, 927–936. DOI: 10.1145/3038912.3052684
Abbas K. Rizi, Riccardo Michielan, Clara Stegehuis, and Mikko Kivelä. 2025. Homophily within and across groups. Nature Communications 16, 1 (Dec. 2025). DOI: 10.1038/s41467-025-66415-2
Jordan K. Kobellarz and Thiago H. Silva. 2022. Should We Translate? Evaluating Toxicity in Online Comments when Translating from Portuguese to English. In Proceedings of the Brazilian Symposium on Multimedia and the Web (Curitiba, Brazil) (WebMedia ’22). Association for Computing Machinery, New York, NY, USA, 89–98. DOI: 10.1145/3539637.3556892
William H. Kruskal and W. Allen Wallis. 1952. Use of Ranks in One-Criterion Variance Analysis. J. Amer. Statist. Assoc. 47, 260 (1952), 583–621. DOI: 10.1080/01621459.1952.10483441
Srijan Kumar, William L. Hamilton, Jure Leskovec, and Dan Jurafsky. 2018. Community Interaction and Conflict on theWeb. In Proceedings of the 2018World Wide Web Conference (WWW ’18). ACM Press, 933–943. DOI: 10.1145/3178876.3186141
Luiz Henrique Quevedo Lima, Adriana Silvina Pagano, and Ana Paula Couto da Silva. 2024. Toxic Content Detection in online social networks: a new dataset from Brazilian Reddit Communities. In Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1, Pablo Gamallo, Daniela Claro, António Teixeira, Livy Real, Marcos Garcia, Hugo Gonçalo Oliveira, and Raquel Amaro (Eds.). Association for Computational Linguistics, Santiago de Compostela, Galicia/Spain, 472–482. [link]
Frank J. Massey. 1951. The Kolmogorov-Smirnov Test for Goodness of Fit. J. Amer. Statist. Assoc. 46, 253 (1951), 68–78. [link]
Alexey N. Medvedev, Renaud Lambiotte, and Jean-Charles Delvenne. 2019. The Anatomy of Reddit: An Overview of Academic Research. In Dynamics On and Of Complex Networks III. Springer International Publishing, 183–204. DOI: 10.1007/978-3-030-14683-2_9
Gabriel Melo and Flavio Figueredo. 2025. What makes a sentence toxic? A critical analysis of specialist models for toxicity detection. In Proceedings of the 31st Brazilian Symposium on Multimedia and the Web (Rio de Janeiro/RJ). SBC, Porto Alegre, RS, Brasil, 376–384. DOI: 10.5753/webmedia.2025.15684
Corrado Monti, Jacopo D’Ignazi, Michele Starnini, and Gianmarco De Francisci Morales. 2023. Evidence of Demographic rather than Ideological Segregation in News Discussion on Reddit. In Proceedings of the ACM Web Conference 2023 (WWW ’23). Association for Computing Machinery, New York, NY, USA, 2777–2786. DOI: 10.1145/3543507.3583468
Nic Newman, Richard Fletcher, Antonis Kalogeropoulos, David AL Levy, and Rasmus Kleis Nielsen. 2025. Reuters Institute Digital News Report 2025. Retrieved June 27, 2026 from [link]
James W. Pennebaker, Ryan L. Boyd, Kayla Jordan, and Kate G. Blackburn. 2015. The Development and Psychometric Properties of LIWC2015. [link]
Giovana Piorino, Luiz Henrique Quevedo Lima, Adriana Silvina Pagano, and Ana Paula Couto da Silva. 2025. Toxicidade e Gatilhos: Um Estudo de Caso em Comunidades do Reddit no Brasil. In Proceedings of the 31st Brazilian Symposium on Multimedia and the Web (Rio de Janeiro/RJ). SBC, Porto Alegre, RS, Brasil, 575–579. DOI: 10.5753/webmedia.2025.15984
Giovana Piorino, Vitor Moreira, Luiz Henrique Quevedo Lima, Ana Clara Souza Pagano, Adriana Silvina Pagano, and Ana Paula Couto da Silva. 2025. Sentiment Analysis of Shared Content in Brazilian Reddit Communities. Journal on Interactive Systems 16, 1 (Aug. 2025), 666–686. DOI: 10.5753/jis.2025.5564
Steve Rathje, Jay J. Van Bavel, and Sander van der Linden. 2021. Out-group animosity drives engagement on social media. Proceedings of the National Academy of Sciences 118, 26 (2021), e2024292118. DOI: 10.1073/pnas.2024292118
Francisco Ricarte Neto, Rafael Anchiêta, Raimundo Moura, Pedro Santos Neto, and Andre Santana. 2025. Investigating Contextual Word Embeddings in Semi-Supervised Learning for Toxic Comment Detection. In Proceedings of the 31st Brazilian Symposium on Multimedia and the Web (Rio de Janeiro/RJ). SBC, Porto Alegre, RS, Brasil, 330–339. DOI: 10.5753/webmedia.2025.15994
Martin Saveski, Brandon Roy, and Deb Roy. 2021. The Structure of Toxic Conversations on Twitter. In Proceedings of the Web Conference 2021 (WWW ’21). Association for Computing Machinery, New York, NY, USA, 1086–1097. DOI: 10.1145/3442381.3449861
Mohammad Soleymani, David Garcia, Brendan Jou, Björn Schuller, Shih-Fu Chang, and Maja Pantic. 2017. A Survey of Multimodal Sentiment Analysis. Image and Vision Computing 65 (2017), 3–14.
Fábio Souza, Rodrigo Nogueira, and Roberto Lotufo. 2020. BERTimbau: Pretrained BERT Models for Brazilian Portuguese. In Intelligent Systems, Ricardo Cerri and Ronaldo C. Prati (Eds.). Springer International Publishing, Cham, 403–417.
Fernanda Luiza Tobias and Ana Paula Couto da Silva. 2025. Linguistic Analysis of Human and Language Model Comments on Posts in Brazilian Reddit Communities. In Proceedings of the 31st Brazilian Symposium on Multimedia and the Web (Rio de Janeiro/RJ). SBC, Porto Alegre, RS, Brasil, 521–525. DOI: 10.5753/webmedia.2025.15908
Lanqin Yuan, Philipp J. Schneider, and Marian-Andrei Rizoiu. 2025. Behavioral Homophily in Social Media via Inverse Reinforcement Learning: A Reddit Case Study. In Proceedings of the ACM onWeb Conference 2025 (WWW’25). Association for Computing Machinery, New York, NY, USA, 576–589. DOI: 10.1145/3696410.3714618
Yiming Zhu, Gareth Tyson, and Pan Hui. 2026. A Comparative Analysis of Social Network Topology in Reddit and Moltbook. arXiv:2602.13920 [cs.SI] [link]
Francesco Barbieri, Luis Espinosa Anke, and Jose Camacho-Collados. 2022. XLMT: Multilingual Language Models in Twitter for Sentiment Analysis and Beyond. In Proceedings of the Thirteenth Language Resources and Evaluation Conference. European Language Resources Association, Marseille, France.
Pedro Bento, Yan Aquino, Arthur Buzelin, Pedro Robles Dutenhefner, Arthur Chagas, Victoria Estanislau, Lucas Dayrell, Samira Malaquias, Caio Santana, Marcelo Sartori Locatelli, Gisele L. Pappa,Wagner Meira Jr., and Virgilio Almeida. 2025. Mapping Hate and Extremism: How Brazilian Reddit Communities Spread Toxic Discourse. In Proceedings of the International AAAI Conference on Web and Social Media (ICWSM ’25). AAAI. DOI: 10.36190/2025.18
Carmela Bernardo, Dora Ricci, and Francesco Vasca. 2026. Homophily Detection in Opinion Dynamics from Reddit Discussions. In Advances in Social Networks Analysis and Mining, I-Hsien Ting, Panagiotis Karampelas, Min-Yuh Day, and Reda Alhajj (Eds.). Springer Nature Switzerland, Cham, 251–262.
Josemar A. Caetano, Hélder S. Lima, Mateus F. Santos, and Humberto T. Marques-Neto. 2018. Using sentiment analysis to define twitter political users’ classes and their homophily during the 2016 American presidential election. Journal of Internet Services and Applications 9, 1 (2018), 18. DOI: 10.1186/s13174-018-0089-0
Josemar Alves Caetano, Gabriel Magno, Marcos Gonçalves, Jussara Almeida, Humberto T. Marques-Neto, and Virgílio Almeida. 2019. Characterizing Attention Cascades in WhatsApp Groups. In Proceedings of the 10th ACM Conference on Web Science (WebSci ’19). Association for Computing Machinery, New York, NY, USA, 27–36. DOI: 10.1145/3292522.3326018
Flavio Carvalho, Rafael Rodrigues, Gabriel Santos, Pedro Cruz, Lilian Ferrari, and Gustavo Guedes. 2019. Avaliação da versão em português do LIWC Lexicon 2015 com análise de sentimentos em redes sociais. In Anais do VIII Brazilian Workshop on Social Network Analysis and Mining (Belém). SBC, Porto Alegre, RS, Brasil, 24–34. DOI: 10.5753/brasnam.2019.6545
Baitong Chen, Satoshi Tsutsui, Ying Ding, and Feicheng Ma. 2017. Understanding the topic evolution in a scientific domain: An exploratory study for the field of information retrieval. Journal of Informetrics 11, 4 (2017), 1175–1189. DOI: 10.1016/j.joi.2017.10.003
Matteo Cinelli, Gianmarco De Francisci Morales, Alessandro Galeazzi, Walter Quattrociocchi, and Michele Starnini. 2021. The echo chamber effect on social media. Proceedings of the National Academy of Sciences 118, 9 (2021), e2023301118. DOI: 10.1073/pnas.2023301118
Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Jiatao Ji, Guillaume Agrawal, Francisco Guzman, Rahul Goyal, Ritesh Kumar, Myle Ott, et al. 2019. Unsupervised cross-lingual representation learning at scale. arXiv preprint arXiv:1911.02116 (2019).
Ringki Das and Thoudam Doren Singh. 2023. Multimodal sentiment analysis: A survey of methods, trends, and challenges. Comput. Surveys 55, 13s (2023), 1–38.
Antônio Pereira De Souza Júnior, Pablo Cecilio, Felipe Viegas,Washington Cunha, Elisa Tuler De Albergaria, and Leonardo Chaves Dutra Da Rocha. 2022. Evaluating Topic Modeling Pre-processing Pipelines for Portuguese Texts. In Proceedings of the Brazilian Symposium on Multimedia and the Web (Curitiba, Brazil) (WebMedia ’22). Association for Computing Machinery, New York, NY, USA, 191–201. DOI: 10.1145/3539637.3557052
Sharad Goel, Ashton Anderson, Jake Hofman, and Duncan J. Watts. 2016. The Structural Virality of Online Diffusion. Management Science (2016). DOI: 10.1287/mnsc.2015.2158
Maarten Grootendorst. 2022. BERTopic: Neural topic modeling with a class-based TF-IDF procedure. DOI: 10.48550/ARXIV.2203.05794
Winston Haynes. 2013. Bonferroni Correction. Springer New York, New York, NY, 154–154. DOI: 10.1007/978-1-4419-9863-7_1213
Jack Hessel, Lillian Lee, and David Mimno. 2017. Cats and Captions vs. Creators and the Clock: Comparing Multimodal Content to Context in Predicting Relative Popularity. In Proceedings of the 26th International Conference on World Wide Web (WWW ’17). International World Wide Web Conferences Steering Committee, 927–936. DOI: 10.1145/3038912.3052684
Abbas K. Rizi, Riccardo Michielan, Clara Stegehuis, and Mikko Kivelä. 2025. Homophily within and across groups. Nature Communications 16, 1 (Dec. 2025). DOI: 10.1038/s41467-025-66415-2
Jordan K. Kobellarz and Thiago H. Silva. 2022. Should We Translate? Evaluating Toxicity in Online Comments when Translating from Portuguese to English. In Proceedings of the Brazilian Symposium on Multimedia and the Web (Curitiba, Brazil) (WebMedia ’22). Association for Computing Machinery, New York, NY, USA, 89–98. DOI: 10.1145/3539637.3556892
William H. Kruskal and W. Allen Wallis. 1952. Use of Ranks in One-Criterion Variance Analysis. J. Amer. Statist. Assoc. 47, 260 (1952), 583–621. DOI: 10.1080/01621459.1952.10483441
Srijan Kumar, William L. Hamilton, Jure Leskovec, and Dan Jurafsky. 2018. Community Interaction and Conflict on theWeb. In Proceedings of the 2018World Wide Web Conference (WWW ’18). ACM Press, 933–943. DOI: 10.1145/3178876.3186141
Luiz Henrique Quevedo Lima, Adriana Silvina Pagano, and Ana Paula Couto da Silva. 2024. Toxic Content Detection in online social networks: a new dataset from Brazilian Reddit Communities. In Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1, Pablo Gamallo, Daniela Claro, António Teixeira, Livy Real, Marcos Garcia, Hugo Gonçalo Oliveira, and Raquel Amaro (Eds.). Association for Computational Linguistics, Santiago de Compostela, Galicia/Spain, 472–482. [link]
Frank J. Massey. 1951. The Kolmogorov-Smirnov Test for Goodness of Fit. J. Amer. Statist. Assoc. 46, 253 (1951), 68–78. [link]
Alexey N. Medvedev, Renaud Lambiotte, and Jean-Charles Delvenne. 2019. The Anatomy of Reddit: An Overview of Academic Research. In Dynamics On and Of Complex Networks III. Springer International Publishing, 183–204. DOI: 10.1007/978-3-030-14683-2_9
Gabriel Melo and Flavio Figueredo. 2025. What makes a sentence toxic? A critical analysis of specialist models for toxicity detection. In Proceedings of the 31st Brazilian Symposium on Multimedia and the Web (Rio de Janeiro/RJ). SBC, Porto Alegre, RS, Brasil, 376–384. DOI: 10.5753/webmedia.2025.15684
Corrado Monti, Jacopo D’Ignazi, Michele Starnini, and Gianmarco De Francisci Morales. 2023. Evidence of Demographic rather than Ideological Segregation in News Discussion on Reddit. In Proceedings of the ACM Web Conference 2023 (WWW ’23). Association for Computing Machinery, New York, NY, USA, 2777–2786. DOI: 10.1145/3543507.3583468
Nic Newman, Richard Fletcher, Antonis Kalogeropoulos, David AL Levy, and Rasmus Kleis Nielsen. 2025. Reuters Institute Digital News Report 2025. Retrieved June 27, 2026 from [link]
James W. Pennebaker, Ryan L. Boyd, Kayla Jordan, and Kate G. Blackburn. 2015. The Development and Psychometric Properties of LIWC2015. [link]
Giovana Piorino, Luiz Henrique Quevedo Lima, Adriana Silvina Pagano, and Ana Paula Couto da Silva. 2025. Toxicidade e Gatilhos: Um Estudo de Caso em Comunidades do Reddit no Brasil. In Proceedings of the 31st Brazilian Symposium on Multimedia and the Web (Rio de Janeiro/RJ). SBC, Porto Alegre, RS, Brasil, 575–579. DOI: 10.5753/webmedia.2025.15984
Giovana Piorino, Vitor Moreira, Luiz Henrique Quevedo Lima, Ana Clara Souza Pagano, Adriana Silvina Pagano, and Ana Paula Couto da Silva. 2025. Sentiment Analysis of Shared Content in Brazilian Reddit Communities. Journal on Interactive Systems 16, 1 (Aug. 2025), 666–686. DOI: 10.5753/jis.2025.5564
Steve Rathje, Jay J. Van Bavel, and Sander van der Linden. 2021. Out-group animosity drives engagement on social media. Proceedings of the National Academy of Sciences 118, 26 (2021), e2024292118. DOI: 10.1073/pnas.2024292118
Francisco Ricarte Neto, Rafael Anchiêta, Raimundo Moura, Pedro Santos Neto, and Andre Santana. 2025. Investigating Contextual Word Embeddings in Semi-Supervised Learning for Toxic Comment Detection. In Proceedings of the 31st Brazilian Symposium on Multimedia and the Web (Rio de Janeiro/RJ). SBC, Porto Alegre, RS, Brasil, 330–339. DOI: 10.5753/webmedia.2025.15994
Martin Saveski, Brandon Roy, and Deb Roy. 2021. The Structure of Toxic Conversations on Twitter. In Proceedings of the Web Conference 2021 (WWW ’21). Association for Computing Machinery, New York, NY, USA, 1086–1097. DOI: 10.1145/3442381.3449861
Mohammad Soleymani, David Garcia, Brendan Jou, Björn Schuller, Shih-Fu Chang, and Maja Pantic. 2017. A Survey of Multimodal Sentiment Analysis. Image and Vision Computing 65 (2017), 3–14.
Fábio Souza, Rodrigo Nogueira, and Roberto Lotufo. 2020. BERTimbau: Pretrained BERT Models for Brazilian Portuguese. In Intelligent Systems, Ricardo Cerri and Ronaldo C. Prati (Eds.). Springer International Publishing, Cham, 403–417.
Fernanda Luiza Tobias and Ana Paula Couto da Silva. 2025. Linguistic Analysis of Human and Language Model Comments on Posts in Brazilian Reddit Communities. In Proceedings of the 31st Brazilian Symposium on Multimedia and the Web (Rio de Janeiro/RJ). SBC, Porto Alegre, RS, Brasil, 521–525. DOI: 10.5753/webmedia.2025.15908
Lanqin Yuan, Philipp J. Schneider, and Marian-Andrei Rizoiu. 2025. Behavioral Homophily in Social Media via Inverse Reinforcement Learning: A Reddit Case Study. In Proceedings of the ACM onWeb Conference 2025 (WWW’25). Association for Computing Machinery, New York, NY, USA, 576–589. DOI: 10.1145/3696410.3714618
Yiming Zhu, Gareth Tyson, and Pan Hui. 2026. A Comparative Analysis of Social Network Topology in Reddit and Moltbook. arXiv:2602.13920 [cs.SI] [link]
Publicado
27/10/2026
Como Citar
KRETLI, Jonas Elias Santos; CAETANO, Josemar Alves.
Analyzing the Role of Negativity in Brazilian Reddit Discussions. In: BRAZILIAN SYMPOSIUM ON MULTIMEDIA AND THE WEB (WEBMEDIA), 32. , 2026, Lavras/MG.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 94-103.
DOI: https://doi.org/10.5753/webmedia.2026.30754.
