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The primary goal of this research is to study the quality of the sentiment analysis (SA) of impressions about Saudi cruises, as a first event, by creating datasets from three selected social media platforms (Instagram, Snapchat, and Twitter). The outcome of this study will help in understanding opinions of passengers and viewers about their first Saudi cruise experiences by analyzing their feelings from social media posts. After cleaning, this experiment contains 1200 samples. The data was classified into positive or negative classes using the choice of machine learning algorithms, such as multilayer perceptron (MLP), na\u0131ve bayes (NB), random forest (RF), support vector machine (SVM), and voting. The results show the highest classification accuracy for the RF algorithm, as it achieved 100% accuracy with over-sampled data from Snapchat using both test options. The algorithms were compared among the three different datasets. All algorithms achieved a high level of accuracy. Hence, the results show that 80% of the sentiments were positive while 20% were negative.<\/jats:p>","DOI":"10.1186\/s40537-022-00568-5","type":"journal-article","created":{"date-parts":[[2022,2,19]],"date-time":"2022-02-19T03:12:26Z","timestamp":1645240346000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Sentiment analysis for cruises in Saudi Arabia on social media platforms using machine learning algorithms"],"prefix":"10.1186","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0421-4981","authenticated-orcid":false,"given":"Bador","family":"Al sari","sequence":"first","affiliation":[]},{"given":"Rawan","family":"Alkhaldi","sequence":"additional","affiliation":[]},{"given":"Dalia","family":"Alsaffar","sequence":"additional","affiliation":[]},{"given":"Tahani","family":"Alkhaldi","sequence":"additional","affiliation":[]},{"given":"Hanan","family":"Almaymuni","sequence":"additional","affiliation":[]},{"given":"Norah","family":"Alnaim","sequence":"additional","affiliation":[]},{"given":"Najwa","family":"Alghamdi","sequence":"additional","affiliation":[]},{"given":"Sunday O.","family":"Olatunji","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,2,18]]},"reference":[{"key":"568_CR1","doi-asserted-by":"crossref","unstructured":"Aquino PA, L\u00f3pez VF, Moreno MN, Mu\u00f1oz MD, Rodr\u00edguez S. 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This research does not involve any human participants, human data, or human tissue. Data is obtained from Instagram, Snapchat, and Twitter. The data is extracted using Python script.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"21"}}