Word sense disambiguation of opinionated words using extended gloss overlap
The increasing use of digital technology and social media has prompted government organizations to take advantage of these in order to gather feedback and opinions from the general public on policies and laws. Since people’s opinions vary, there is a need to present these in an orderly manner for fa...
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| Format: | text |
| Language: | English |
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Animo Repository
2011
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| Online Access: | https://animorepository.dlsu.edu.ph/etd_masteral/4009 |
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| Institution: | De La Salle University |
| Language: | English |
| Summary: | The increasing use of digital technology and social media has prompted government organizations to take advantage of these in order to gather feedback and opinions from the general public on policies and laws. Since people’s opinions vary, there is a need to present these in an orderly manner for faster and more efficient decision and policy making. This is where opinion classification comes in. Existing systems such as Vox Pop are able to classify texts according to polarity with the help of SentiWordNet, which assigns subjectivity and polarity scores to WordNet synsets. However, the current algorithm that Vox Pop uses yields an accuracy rate of only 50.5%. The research integrated a word sense disambiguation algorithm may be the key to improving the task of polarity classification. The extended gloss overlap algorithm was be used, which compares two synsets and scores the relatedness between them by looking for phrasal matches between all their glosses. However, the accuracy only increased to 60%. This shows that integrating WSD is not enough in improving the opinion classification task. |
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