Mixtures of biased sentiment analysers

DOI10.1007/s11634-013-0150-6zbMath1474.62245OpenAlexW1975225015MaRDI QIDQ2009040

Michael Salter-Townshend, Thomas Brendan Murphy

Publication date: 27 November 2019

Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10197/10877

zbMATH Keywords

EM algorithmmixture modelcrowdsourcingsentiment analysisbias modelling

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (1)

Monitoring rare categories in sentiment and opinion analysis: a Milan mega event on Twitter platform

Cites Work

• Block clustering with Bernoulli mixture models: comparison of different approaches
• Another interpretation of the EM algorithm for mixture distributions
• An entropy criterion for assessing the number of clusters in a mixture model
• Consistent estimation of a mixing distribution
• Estimating the dimension of a model
• On the optimality of the simple Bayesian classifier under zero-one loss
• An improvement of the NEC criterion for assessing the number of clusters in a mixture model
• Model-Based Clustering, Discriminant Analysis, and Density Estimation
• Finite mixture models
• Bayes Factors
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Mixtures of biased sentiment analysers