Title :
Persona Analysis with Text Topic Modelling
Author :
Dong-mei Yang ; Hui Zheng ; Ji-kun Yan ; Ye Jin
Author_Institution :
Science and Technology on Blind Signal Processing Laboratory, Mail Box No.666, Chengdu, China, 610041
Abstract :
We present a new way called Persona Analysis with Text Topic Modelling (PATTM), which tries to learn the role of personae according to the literal descriptions. It is similar to Latent Dirichlet Allocation (LDA) and Author Topic (AT) model, with the attribute of allowing all text to join in the topic modelling process, even when there is no persona in the text. We experiment on the “Libya Event” data set which contains more than 4,000 texts collected from the Internet. The PATTM gives lower perplexity than LDA and AT model on the data set.
Keywords :
Gibbs sampling; machine learning; natual language process; topic model;
Conference_Titel :
Automatic Control and Artificial Intelligence (ACAI 2012), International Conference on
Conference_Location :
Xiamen
Electronic_ISBN :
978-1-84919-537-9
DOI :
10.1049/cp.2012.1280