Improving twitter aspect-based sentiment analysis using hybrid approach
Twitter sentiment analysis has emerged and become interesting in many field that involves social networks. Previous researches have assumed the problem as a tweet-level classification task where it only determines the general sentiment of a tweet. This paper proposed hybrid approach to analyze aspec...
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| Format: | Conference or Workshop Item |
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Springer Verlag
2016
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| _version_ | 1796862086705315840 |
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| author | Zainuddin, N. Selamat, A. Ibrahim, R. |
| author_facet | Zainuddin, N. Selamat, A. Ibrahim, R. |
| author_sort | Zainuddin, N. |
| collection | ePrints |
| description | Twitter sentiment analysis has emerged and become interesting in many field that involves social networks. Previous researches have assumed the problem as a tweet-level classification task where it only determines the general sentiment of a tweet. This paper proposed hybrid approach to analyze aspect-based sentiments for tweets. We conducted several experiments to identify explicit and implicit aspects which is crucial for aspect-based sentiment analysis. The hybrid approach between association rule mining, dependency parsing and Sentiwordnet is applied to solve this aspect-based sentiment analysis problem. The performance is evaluated using hate crime domain and other benchmark dataset in order to evaluate the results and the finding can be used to improve the accuracy for the aspect-based sentiment classification. |
| first_indexed | 2024-03-05T20:06:14Z |
| format | Conference or Workshop Item |
| id | utm.eprints-73483 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T20:06:14Z |
| publishDate | 2016 |
| publisher | Springer Verlag |
| record_format | dspace |
| spelling | utm.eprints-734832017-11-20T08:43:00Z http://eprints.utm.my/73483/ Improving twitter aspect-based sentiment analysis using hybrid approach Zainuddin, N. Selamat, A. Ibrahim, R. QA75 Electronic computers. Computer science Twitter sentiment analysis has emerged and become interesting in many field that involves social networks. Previous researches have assumed the problem as a tweet-level classification task where it only determines the general sentiment of a tweet. This paper proposed hybrid approach to analyze aspect-based sentiments for tweets. We conducted several experiments to identify explicit and implicit aspects which is crucial for aspect-based sentiment analysis. The hybrid approach between association rule mining, dependency parsing and Sentiwordnet is applied to solve this aspect-based sentiment analysis problem. The performance is evaluated using hate crime domain and other benchmark dataset in order to evaluate the results and the finding can be used to improve the accuracy for the aspect-based sentiment classification. Springer Verlag 2016 Conference or Workshop Item PeerReviewed Zainuddin, N. and Selamat, A. and Ibrahim, R. (2016) Improving twitter aspect-based sentiment analysis using hybrid approach. In: 8th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2016, 14 - 16 March 2016, Vietnam. https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961233698&doi=10.1007%2f978-3-662-49381-6_15&partnerID=40&md5=c3580552b45ec5c049120a1fbb97356c |
| spellingShingle | QA75 Electronic computers. Computer science Zainuddin, N. Selamat, A. Ibrahim, R. Improving twitter aspect-based sentiment analysis using hybrid approach |
| title | Improving twitter aspect-based sentiment analysis using hybrid approach |
| title_full | Improving twitter aspect-based sentiment analysis using hybrid approach |
| title_fullStr | Improving twitter aspect-based sentiment analysis using hybrid approach |
| title_full_unstemmed | Improving twitter aspect-based sentiment analysis using hybrid approach |
| title_short | Improving twitter aspect-based sentiment analysis using hybrid approach |
| title_sort | improving twitter aspect based sentiment analysis using hybrid approach |
| topic | QA75 Electronic computers. Computer science |
| work_keys_str_mv | AT zainuddinn improvingtwitteraspectbasedsentimentanalysisusinghybridapproach AT selamata improvingtwitteraspectbasedsentimentanalysisusinghybridapproach AT ibrahimr improvingtwitteraspectbasedsentimentanalysisusinghybridapproach |