A Study on Emotion Analysis from Blogosphere
Date Issued
2009
Date
2009
Author(s)
Yang, Changhua
Abstract
With the rapid emergence of WWW innovations, people are continuously improving their ways of processing information. To fulfill the information needs of WWW users, blog sites, encyclopedia sites, video-sharing sites emerge as powerful value-added platforms. These sites are referred to as social media that integrates web users’ publications, communications, and interactions. People can easily share their creations and emotions through this platform. mong different forms of social media, blog is the most representative and widely spread by internet. The blog space is traditionally regarded as useful corpora which provide tremendous amount of materials for language processing tasks. This dissertation studies on emotion analysis using blog as the dataset.e innovatively use Yahoo! Kimo Blog posts that contain emoticons as the analyzing corpora. We have analyzed the corpora in a huge volume that spans a period of one year as the training dataset and the posts spanning a period of one month as the testing dataset. We consider collection of blog articles as training and testing datasets for emotion classification. For a classification task on blog, the emotion ground truths are those emoticons that are brought in by bloggers when they want to share their feelings, emotions, or moods to the blog community.he blog datasets are first used to construct an emotion lexicon by collocation test methods and we have shown how this lexicon can facilitate the emotion analysis. Those terms in emotion lexicon are therefore regarded as features for learning machine learning-based classifiers. We have improved the performance of emotion analysis by incorporating the sequential information. Finally, the learnt classification kernel has been applied on a multi-perspective integration (writers and readers) and a multi-perceptive integration (blog and music). Knowledge on blog metadata inclusive of textual units, time stamps, and named entities also help construct a census and trend survey module. Other applications include implementation on emotion filtering for blog texts, a cross-lingual adaption of emotion analysis, and an authoring tool for the writes to predict the readers’ emotions. Written text is one of the media by which people convey their emotions. But do bloggers always share the traceable emotions? If not, are the appearances of emotion icons totally random, or are there recurring patterns? These are the original questions which direct our research. By knowing how emotions conveyed by texts, it is possible to build a system to provide users with language usage recommendations to assist uses in expressing appropriate emotions. The analyzing system on emotions can be integrated in other research fileds in the future.
Subjects
blog
emotion analysis
Type
thesis
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