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Published in:
2014 | OriginalPaper | Chapter
Improving Event Recognition Using Sparse PCA in the Context of London Twitter Data
Authors : Theo Pavlakou, Arta Babaee, Moez Draief
Published in: Information Sciences and Systems 2014
Publisher: Springer International Publishing
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Abstract
Motivated by some of the recent work based on using sparse principal component analysis to analyse social media, we propose an improvement which involves altering the input data matrices by considering what relationships they represent. Accordingly, we confirm our result by using Twitter data from London in the year 2012 as a medium to demonstrate on. Various alterations are made to the data matrix obtained from this data and the resulting matrices are then passed through a sparse principal component analysis algorithm. The resulting outputs are then analysed and it is shown that indeed the results do differ, with one particular variation consistently outperforming the rest. Our results are especially of interest when the data to be analysed can be represented by a binary matrix of some sort, e.g. in document analysis.