Predicting the popularity of tweets using internal and external knowledge: an empirical Bayes type approach
Author
Abstract
Suggested Citation
DOI: 10.1007/s10182-021-00390-z
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Zongyang Ma & Aixin Sun & Gao Cong, 2013. "On predicting the popularity of newly emerging hashtags in Twitter," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(7), pages 1399-1410, July.
- Min-ge Xie & Kesar Singh, 2013. "Confidence Distribution, the Frequentist Distribution Estimator of a Parameter: A Review," International Statistical Review, International Statistical Institute, vol. 81(1), pages 3-39, April.
- Zongyang Ma & Aixin Sun & Gao Cong, 2013. "On predicting the popularity of newly emerging hashtags in Twitter," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(7), pages 1399-1410, July.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Jabłońska-Sabuka, Matylda & Sitarz, Robert & Kraslawski, Andrzej, 2014. "Forecasting research trends using population dynamics model with Burgers’ type interaction," Journal of Informetrics, Elsevier, vol. 8(1), pages 111-122.
- Ali Daud & Muhammad Ahmad & M. S. I. Malik & Dunren Che, 2015. "Using machine learning techniques for rising star prediction in co-author network," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1687-1711, February.
- Zhao, Qihang & Feng, Xiaodong, 2022. "Utilizing citation network structure to predict paper citation counts: A Deep learning approach," Journal of Informetrics, Elsevier, vol. 16(1).
- Sharad Goel & Ashton Anderson & Jake Hofman & Duncan J. Watts, 2016. "The Structural Virality of Online Diffusion," Management Science, INFORMS, vol. 62(1), pages 180-196, January.
- Arora, Anuja & Bansal, Shivam & Kandpal, Chandrashekhar & Aswani, Reema & Dwivedi, Yogesh, 2019. "Measuring social media influencer index- insights from facebook, Twitter and Instagram," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 86-101.
- António Fonseca & Jorge Louçã, 2018. "Explaining the emergence of online popularity through a model of information diffusion," Computational and Mathematical Organization Theory, Springer, vol. 24(2), pages 169-187, June.
- Cui, Hao & Kertész, János, 2023. "“Born in Rome” or “Sleeping Beauty”: Emergence of hashtag popularity on the Chinese microblog Sina Weibo," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
- Jaebong Son & Jintae Lee & Kai R. Larsen & Jiyoung Woo, 2020. "Understanding the uncertainty of disaster tweets and its effect on retweeting: The perspectives of uncertainty reduction theory and information entropy," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(10), pages 1145-1161, October.
- Paige Brown Jarreau & Imogene A Cancellare & Becky J Carmichael & Lance Porter & Daniel Toker & Samantha Z Yammine, 2019. "Using selfies to challenge public stereotypes of scientists," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-23, May.
- Son, Jaebong & Lee, Hyung Koo & Jin, Sung & Lee, Jintae, 2019. "Content features of tweets for effective communication during disasters: A media synchronicity theory perspective," International Journal of Information Management, Elsevier, vol. 45(C), pages 56-68.
- repec:plo:pone00:0179630 is not listed on IDEAS
- Guang Yang & Dungang Liu & Junyuan Wang & Min‐ge Xie, 2016. "Meta‐analysis framework for exact inferences with application to the analysis of rare events," Biometrics, The International Biometric Society, vol. 72(4), pages 1378-1386, December.
- Jonas Beck & Arne C. Bathke, 2024. "A unifying framework for rank and pseudo-rank based inference using nonparametric confidence distributions," Statistical Papers, Springer, vol. 65(3), pages 1233-1257, May.
- La Vecchia, Davide & Moor, Alban & Scaillet, Olivier, 2023.
"A higher-order correct fast moving-average bootstrap for dependent data,"
Journal of Econometrics, Elsevier, vol. 235(1), pages 65-81.
- Davide La Vecchia & Alban Moor & Olivier Scaillet, 2020. "A Higher-Order Correct Fast Moving-Average Bootstrap for Dependent Data," Papers 2001.04867, arXiv.org, revised Jan 2022.
- Davide La Vecchia & Alban Moor & O. Scaillet, 2020. "A Higher-Order Correct Fast Moving-Average Bootstrap for Dependent Data," Swiss Finance Institute Research Paper Series 20-01, Swiss Finance Institute.
- La Vecchia, Davide & Moor, Alban & Scaillet, Olivier, 2020. "A higher-order correct fast moving-average bootstrap for dependent data," Working Papers unige:129395, University of Geneva, Geneva School of Economics and Management.
- Zhao, Xiujie & Chen, Piao & Gaudoin, Olivier & Doyen, Laurent, 2021. "Accelerated degradation tests with inspection effects," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1099-1114.
- Veronese, Piero & Melilli, Eugenio, 2018. "Some asymptotic results for fiducial and confidence distributions," Statistics & Probability Letters, Elsevier, vol. 134(C), pages 98-105.
- Elise Coudin & Jean-Marie Dufour, 2017.
"Finite-sample generalized confidence distributions and sign-based robust estimators in median regressions with heterogenous dependent errors,"
CIRANO Working Papers
2017s-06, CIRANO.
- Élise, COUDIN & Jean-Marie DUFOUR, 2017. "Finite-Sample Generalized Confidence Distributions and Sign-Based Robust Estimators in Median Regressions with Heterogeneous Dependent Errors," Cahiers de recherche 01-2017, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Xuhua Liu & Xingzhong Xu, 2016. "Confidence distribution inferences in one-way random effects model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 59-74, March.
- David R. Bickel, 2014. "Small-scale Inference: Empirical Bayes and Confidence Methods for as Few as a Single Comparison," International Statistical Review, International Statistical Institute, vol. 82(3), pages 457-476, December.
- Lee Youngjo & Gwangsu Kim, 2020. "Properties of h‐Likelihood Estimators in Clustered Data," International Statistical Review, International Statistical Institute, vol. 88(2), pages 380-395, August.
- Hector, Emily C. & Luo, Lan & Song, Peter X.-K., 2023. "Parallel-and-stream accelerator for computationally fast supervised learning," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
More about this item
Keywords
Empirical Bayes; Kernel smoothing; Maximum a posteriori (MAP) estimation; Nonparametric regression;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:alstar:v:105:y:2021:i:2:d:10.1007_s10182-021-00390-z. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.