Characterizing engagement dynamics across topics on Facebook

Social media platforms heavily changed how users consume and digest information and, thus, how the popularity of topics evolves. In this paper, we explore the interplay between the virality of controversial topics and how they may trigger heated discussions and eventually increase users’ polarizatio...

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Vydáno v:	PloS one Ročník 18; číslo 6; s. e0286150
Hlavní autoři:	Etta, Gabriele, Sangiorgio, Emanuele, Di Marco, Niccolò, Avalle, Michele, Scala, Antonio, Cinelli, Matteo, Quattrociocchi, Walter
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Public Library of Science 28.06.2023 Public Library of Science (PLoS)
Témata:	Algorithms Biology and Life Sciences Computer and Information Sciences Consumption Data collection Data mining Evaluation Humans Information management Keywords Quantitative analysis Research and Analysis Methods Social Media Social Networking Social networks Social Sciences Italy
ISSN:	1932-6203, 1932-6203
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Abstract	Social media platforms heavily changed how users consume and digest information and, thus, how the popularity of topics evolves. In this paper, we explore the interplay between the virality of controversial topics and how they may trigger heated discussions and eventually increase users’ polarization. We perform a quantitative analysis on Facebook by collecting ∼57 M posts from ∼2 M pages and groups between 2018 and 2022, focusing on engaging topics involving scandals, tragedies, and social and political issues. Using logistic functions, we quantitatively assess the evolution of these topics finding similar patterns in their engagement dynamics. Finally, we show that initial burstiness may predict the rise of users’ future adverse reactions regardless of the discussed topic.
AbstractList	Social media platforms heavily changed how users consume and digest information and, thus, how the popularity of topics evolves. In this paper, we explore the interplay between the virality of controversial topics and how they may trigger heated discussions and eventually increase users' polarization. We perform a quantitative analysis on Facebook by collecting ∼57M posts from ∼2M pages and groups between 2018 and 2022, focusing on engaging topics involving scandals, tragedies, and social and political issues. Using logistic functions, we quantitatively assess the evolution of these topics finding similar patterns in their engagement dynamics. Finally, we show that initial burstiness may predict the rise of users' future adverse reactions regardless of the discussed topic.Social media platforms heavily changed how users consume and digest information and, thus, how the popularity of topics evolves. In this paper, we explore the interplay between the virality of controversial topics and how they may trigger heated discussions and eventually increase users' polarization. We perform a quantitative analysis on Facebook by collecting ∼57M posts from ∼2M pages and groups between 2018 and 2022, focusing on engaging topics involving scandals, tragedies, and social and political issues. Using logistic functions, we quantitatively assess the evolution of these topics finding similar patterns in their engagement dynamics. Finally, we show that initial burstiness may predict the rise of users' future adverse reactions regardless of the discussed topic. Social media platforms heavily changed how users consume and digest information and, thus, how the popularity of topics evolves. In this paper, we explore the interplay between the virality of controversial topics and how they may trigger heated discussions and eventually increase users' polarization. We perform a quantitative analysis on Facebook by collecting ~57M posts from ~2M pages and groups between 2018 and 2022, focusing on engaging topics involving scandals, tragedies, and social and political issues. Using logistic functions, we quantitatively assess the evolution of these topics finding similar patterns in their engagement dynamics. Finally, we show that initial burstiness may predict the rise of users' future adverse reactions regardless of the discussed topic. Social media platforms heavily changed how users consume and digest information and, thus, how the popularity of topics evolves. In this paper, we explore the interplay between the virality of controversial topics and how they may trigger heated discussions and eventually increase users’ polarization. We perform a quantitative analysis on Facebook by collecting ∼57 M posts from ∼2 M pages and groups between 2018 and 2022, focusing on engaging topics involving scandals, tragedies, and social and political issues. Using logistic functions, we quantitatively assess the evolution of these topics finding similar patterns in their engagement dynamics. Finally, we show that initial burstiness may predict the rise of users’ future adverse reactions regardless of the discussed topic. Social media platforms heavily changed how users consume and digest information and, thus, how the popularity of topics evolves. In this paper, we explore the interplay between the virality of controversial topics and how they may trigger heated discussions and eventually increase users’ polarization. We perform a quantitative analysis on Facebook by collecting ∼57 M posts from ∼2 M pages and groups between 2018 and 2022, focusing on engaging topics involving scandals, tragedies, and social and political issues. Using logistic functions, we quantitatively assess the evolution of these topics finding similar patterns in their engagement dynamics. Finally, we show that initial burstiness may predict the rise of users’ future adverse reactions regardless of the discussed topic. Social media platforms heavily changed how users consume and digest information and, thus, how the popularity of topics evolves. In this paper, we explore the interplay between the virality of controversial topics and how they may trigger heated discussions and eventually increase users’ polarization. We perform a quantitative analysis on Facebook by collecting ∼57M posts from ∼2M pages and groups between 2018 and 2022, focusing on engaging topics involving scandals, tragedies, and social and political issues. Using logistic functions, we quantitatively assess the evolution of these topics finding similar patterns in their engagement dynamics. Finally, we show that initial burstiness may predict the rise of users’ future adverse reactions regardless of the discussed topic.
Audience	Academic
Author	Sangiorgio, Emanuele Etta, Gabriele Cinelli, Matteo Avalle, Michele Quattrociocchi, Walter Di Marco, Niccolò Scala, Antonio
AuthorAffiliation	1 Center of Data Science and Complexity for Society, Department of Computer Science, Sapienza Università di Roma, Roma, Italy Leiden University: Universiteit Leiden, NETHERLANDS 2 Department of Social Sciences and Economics, Sapienza Università di Roma, Roma, Italy 3 Department of Mathematics and Computer Science, University of Florence, Firenze FI, Italy 4 ISC-CNR UoS Sapienza, Rome, Italy
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BackLink	https://www.ncbi.nlm.nih.gov/pubmed/37379268$$D View this record in MEDLINE/PubMed
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SubjectTerms	Algorithms Biology and Life Sciences Computer and Information Sciences Consumption Data collection Data mining Evaluation Humans Information management Keywords Quantitative analysis Research and Analysis Methods Social Media Social Networking Social networks Social Sciences
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Title	Characterizing engagement dynamics across topics on Facebook
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