A Bayesian approach for predicting the popularity of tweets

DOI10.1214/14-AOAS741zbMath1304.62147arXiv1304.6777MaRDI QIDQ484024

Eric T. Bradlow, Tauhid Zaman, Emily B. Fox

Publication date: 17 December 2014

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1304.6777

zbMATH Keywords

time seriessocial networksforecastingBayesian inferenceTwitter

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Social networks; opinion dynamics (91D30) Applications of statistics to social sciences (62P25) Bayesian inference (62F15) Economic time series analysis (91B84) Graphical methods in statistics (62A09)

Related Items (3)

Marked self-exciting point process modelling of information diffusion on twitter ⋮ A Bayesian approach for predicting the popularity of tweets ⋮ Pairwise influences in dynamic choice: network-based model and application

Cites Work

• A Bayesian approach for predicting the popularity of tweets
• Information processing models generating lognormally distributed reaction times
• Inference from iterative simulation using multiple sequences
• Parallel information processing models compatible with lognormally distributed response times
• Bayesian Measures of Model Complexity and Fit
• Statistical Analysis of a Telephone Call Center

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