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Academic Paper


Title: A hierarchical approach to mood classification in blogs
Author: Fazel Keshtkar
Institution: University of Ottawa
Author: Diana Inkpen
Institution: University of Ottawa
Linguistic Field: Computational Linguistics; Text/Corpus Linguistics
Abstract: In this article, we explore the task of mood classification for blog postings. We propose a novel approach that uses the hierarchy of possible moods to achieve better results than a standard machine learning approach. We also show that using sentiment orientation features improves the performance of classification. We used the Livejournal blog corpus as a data set to train and evaluate our method. We present extensive error analysis and discuss the difficulty of the task.

CUP AT LINGUIST

This article appears IN Natural Language Engineering Vol. 18, Issue 1, which you can READ on Cambridge's site .



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