Big Data Analytics for Tourism: A Case Study from Ubon Ratchathani Province, Thailand
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Abstract
The objectives of this study can be divided into three parts as follows: 1) to collect and perform sentiment analysis of tourists who visited tourist attractions in Ubon Ratchathani province from the tourist comments posted on online social networking. 2) to study the performance of an algorithm for sentiment analysis using deep learning. 3) to develop a software using Python and to visualize data via a web browser using Microsoft Power BI Desktop. This research collected a total of 16,950 comments by the tourists who commented on 26 tourist attractions in Ubon Ratchathani province from the online social networking sources. The comments were separated into two parts. For the first part, there are 13,560 comments used for creating a classifier model. The second part used 3,390 comments for testing the performance of the algorithm. The result showed that by using the Convolutional Neural Network (CNN) algorithm, the accuracy rate of
2-levels classification is 98%. For 5-levels classification, the accuracy rate is 42%.
Article Details
Articles published in Journal of Industrial Technology Ubon Ratchathani Rajabhat University both hard copy and electronically are belonged to the Journal.
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