{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T01:37:04Z","timestamp":1777599424356,"version":"3.51.4"},"reference-count":83,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2022,4,29]],"date-time":"2022-04-29T00:00:00Z","timestamp":1651190400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BDCC"],"abstract":"<jats:p>Arabic sentiment analysis is a process that aims to extract the subjective opinions of different users about different subjects since these opinions and sentiments are used to recognize their perspectives and judgments in a particular domain. Few research studies addressed semantic-oriented approaches for Arabic sentiment analysis based on domain ontologies and features\u2019 importance. In this paper, we built a semantic orientation approach for calculating overall polarity from the Arabic subjective texts based on built domain ontology and the available sentiment lexicon. We used the ontology concepts to extract and weight the semantic domain features by considering their levels in the ontology tree and their frequencies in the dataset to compute the overall polarity of a given textual review based on the importance of each domain feature. For evaluation, an Arabic dataset from the hotels\u2019 domain was selected to build the domain ontology and to test the proposed approach. The overall accuracy and f-measure reach 79.20% and 78.75%, respectively. Results showed that the approach outperformed the other semantic orientation approaches, and it is an appealing approach to be used for Arabic sentiment analysis.<\/jats:p>","DOI":"10.3390\/bdcc6020048","type":"journal-article","created":{"date-parts":[[2022,4,29]],"date-time":"2022-04-29T16:49:57Z","timestamp":1651250997000},"page":"48","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["A New Ontology-Based Method for Arabic Sentiment Analysis"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6860-7023","authenticated-orcid":false,"given":"Safaa M.","family":"Khabour","sequence":"first","affiliation":[{"name":"Department of Information Systems, Faculty of Information Technology and Computer Sciences, Yarmouk University, Irbid 21163, Jordan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3406-0867","authenticated-orcid":false,"given":"Qasem A.","family":"Al-Radaideh","sequence":"additional","affiliation":[{"name":"Department of Information Systems, Faculty of Information Technology and Computer Sciences, Yarmouk University, Irbid 21163, Jordan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1456-7377","authenticated-orcid":false,"given":"Dheya","family":"Mustafa","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Faculty of Engineering, The Hashemite University, Zarqa 13133, Jordan"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,29]]},"reference":[{"key":"ref_1","unstructured":"Farha, I.A., and Magdy, W. 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