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A study on topic models using LDA and Word2Vec in travel route recommendation: focus on convergence travel and tours reviews

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Abstract

At present, we live in prosperity contrary to the past times. As income increases, people enjoy wealth, but more people tend to pursue their own inner happiness: travel. People go to other places or visit foreign countries for business or journey. This study aims to identify the best tour route for foreign tourists in South Korea. Based on the review analysis results, this paper also aims to put forward techniques and methodologies required in practical affairs when developing a travel site or a travel application. On this note, it collected tourists’ reviews at the Tripadvisor official website and conducted text mining technique as well as network analysis using R and Tagxedo, which is a big data analytic tool. The analysis results displayed that there were differences in travel preference, and especially, individual travelers had difficulty traveling by public transportation and selecting travel destinations. Therefore, customized travel routes were suggested for convenient use among travelers.

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Authors and Affiliations

  1. Division of Software and Convergence, Sunmoon University, 70, Sunmoon-ro 221 beon-gil, Tangjeong-myeon, Asan, 31460, Chungnam, South Korea

    Seong-Taek Park

  2. School of Economics and Management, Taishan University, No. 525 Dongyue Street, Daiyue District, Taian, 271000, Shandong, China

    Chang Liu

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  1. Seong-Taek Park
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  2. Chang Liu
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Correspondence to Chang Liu.

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Park, ST., Liu, C. A study on topic models using LDA and Word2Vec in travel route recommendation: focus on convergence travel and tours reviews. Pers Ubiquit Comput 26, 429–445 (2022). https://doi.org/10.1007/s00779-020-01476-2

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