Aspect-based sentiment analysis using smart government review data
Digital resources such as smart applications reviews and online feedback information are important sources to seek customers’ feedback and input. This paper aims to help government entities gain insights on the needs and expectations of their customers. Towards this end, we propose an aspect-based s...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , |
| منشور في: |
2019
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://bspace.buid.ac.ae/handle/1234/2786 https://doi.org/10.1016/j.aci.2019.11.003. |
| الوسوم: |
إضافة وسم
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| _version_ | 1862980616889303040 |
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| author | Alqaryouti , Omar |
| author2 | Siyam, Nur Abdel Monem, Azza Shaalan, Khaled |
| author2_role | author author author |
| author_facet | Alqaryouti , Omar Siyam, Nur Abdel Monem, Azza Shaalan, Khaled |
| author_role | author |
| dc.creator.none.fl_str_mv | Alqaryouti , Omar Siyam, Nur Abdel Monem, Azza Shaalan, Khaled |
| dc.date.none.fl_str_mv | 2019 2025-02-10T05:35:05Z 2025-02-10T05:35:05Z |
| dc.identifier.none.fl_str_mv | Alqaryouti, O. et al. (2024) “Aspect-based sentiment analysis using smart government review data,” Applied Computing and Informatics, 20(1/2), pp. 142–161. 2634-1964, 2210-8327 https://bspace.buid.ac.ae/handle/1234/2786 https://doi.org/10.1016/j.aci.2019.11.003. |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | Emerald Publishing Limited |
| dc.relation.none.fl_str_mv | Applied Computing and Informaticsv20 n1/2 (2024): 142-161 |
| dc.subject.none.fl_str_mv | Sentiment analysis, Aspect extraction, Aspect-based sentiment analysis, Lexicon approach, Rule-based approach, Government smart apps |
| dc.title.none.fl_str_mv | Aspect-based sentiment analysis using smart government review data |
| dc.type.none.fl_str_mv | Article |
| description | Digital resources such as smart applications reviews and online feedback information are important sources to seek customers’ feedback and input. This paper aims to help government entities gain insights on the needs and expectations of their customers. Towards this end, we propose an aspect-based sentiment analysis hybrid approach that integrates domain lexicons and rules to analyse the entities smart apps reviews. The proposed model aims to extract the important aspects from the reviews and classify the corresponding sentiments. This approach adopts language processing techniques, rules, and lexicons to address several sentiment analysis challenges, and produce summarized results. According to the reported results, the aspect extraction accuracy improves significantly when the implicit aspects are considered. Also, the integrated classification model outperforms the lexicon-based baseline and the other rules combinations by 5% in terms of Accuracy on average. Also, when using the same dataset, the proposed approach outperforms machine learning approaches that uses support vector machine (SVM). However, using these lexicons and rules as input features to the SVM model has achieved higher accuracy than other SVM models. |
| id | budr_84b92082029b2a2c64df6d7ba8821c36 |
| identifier_str_mv | Alqaryouti, O. et al. (2024) “Aspect-based sentiment analysis using smart government review data,” Applied Computing and Informatics, 20(1/2), pp. 142–161. 2634-1964, 2210-8327 |
| language_invalid_str_mv | en |
| network_acronym_str | budr |
| network_name_str | The British University in Dubai repository |
| oai_identifier_str | oai:bspace.buid.ac.ae:1234/2786 |
| publishDate | 2019 |
| publisher.none.fl_str_mv | Emerald Publishing Limited |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Aspect-based sentiment analysis using smart government review dataAlqaryouti , OmarSiyam, NurAbdel Monem, AzzaShaalan, KhaledSentiment analysis, Aspect extraction, Aspect-based sentiment analysis, Lexicon approach, Rule-based approach, Government smart appsDigital resources such as smart applications reviews and online feedback information are important sources to seek customers’ feedback and input. This paper aims to help government entities gain insights on the needs and expectations of their customers. Towards this end, we propose an aspect-based sentiment analysis hybrid approach that integrates domain lexicons and rules to analyse the entities smart apps reviews. The proposed model aims to extract the important aspects from the reviews and classify the corresponding sentiments. This approach adopts language processing techniques, rules, and lexicons to address several sentiment analysis challenges, and produce summarized results. According to the reported results, the aspect extraction accuracy improves significantly when the implicit aspects are considered. Also, the integrated classification model outperforms the lexicon-based baseline and the other rules combinations by 5% in terms of Accuracy on average. Also, when using the same dataset, the proposed approach outperforms machine learning approaches that uses support vector machine (SVM). However, using these lexicons and rules as input features to the SVM model has achieved higher accuracy than other SVM models.Emerald Publishing Limited2025-02-10T05:35:05Z2025-02-10T05:35:05Z2019ArticleAlqaryouti, O. et al. (2024) “Aspect-based sentiment analysis using smart government review data,” Applied Computing and Informatics, 20(1/2), pp. 142–161.2634-1964, 2210-8327https://bspace.buid.ac.ae/handle/1234/2786https://doi.org/10.1016/j.aci.2019.11.003.enApplied Computing and Informaticsv20 n1/2 (2024): 142-161oai:bspace.buid.ac.ae:1234/27862026-01-29T15:04:56Z |
| spellingShingle | Aspect-based sentiment analysis using smart government review data Alqaryouti , Omar Sentiment analysis, Aspect extraction, Aspect-based sentiment analysis, Lexicon approach, Rule-based approach, Government smart apps |
| title | Aspect-based sentiment analysis using smart government review data |
| title_full | Aspect-based sentiment analysis using smart government review data |
| title_fullStr | Aspect-based sentiment analysis using smart government review data |
| title_full_unstemmed | Aspect-based sentiment analysis using smart government review data |
| title_short | Aspect-based sentiment analysis using smart government review data |
| title_sort | Aspect-based sentiment analysis using smart government review data |
| topic | Sentiment analysis, Aspect extraction, Aspect-based sentiment analysis, Lexicon approach, Rule-based approach, Government smart apps |
| url | https://bspace.buid.ac.ae/handle/1234/2786 https://doi.org/10.1016/j.aci.2019.11.003. |