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On the challenges of predicting microscopic dynamics of online conversations

Abstract To what extent can we predict the structure of online conversation trees? We present a generative model to predict the size and evolution of threaded conversations on social media by combining machine learning algorithms. The model is evaluated using datasets that span two topical domains (...

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Principais autores: John Bollenbacher, Diogo Pacheco, Pik-Mai Hui, Yong-Yeol Ahn, Alessandro Flammini, Filippo Menczer
Format: Artigo
Sprog:Inglês
Udgivet: SpringerOpen 2021-02-01
Serier:Applied Network Science
Fag:
Information cascades
Conversation trees
Prediction
Social media
Machine learning
Online adgang:https://doi.org/10.1007/s41109-021-00357-8
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