APPLICATION OF TEXT MINING AND SENTIMENT ANALYSIS ON 30 HOTELS/RESTAURANTS IN KAMALA THAILAND FROM THE TOURIST ACCOMMODATION REVIEWS DATASET

Text mining is based on a range of cutting-edge methods from linguistics, statistics, and machine learning. It is the process of transforming, exploring, and analysing unstructured text into structured text with the help of software and techniques that are able to identify concepts, patterns, stop words, keywords, and other qualities in a text data. Some of these techniques includes Naïve Bayes, Support Vector Machine, etc. It is used for different reasons like clustering, summarization, concept extraction and in our case in this study, sentiment analysis.

The opinions of the customers of a company can be tracked using the popular text mining tool called sentiment analysis. Sentiment analysis is the process of analysing a text to ascertain if the text has positive, neutral, or negative emotions. It uses natural language processing (a branch of artificial intelligence that enables computers to understand text and speech in a human like manner). It is widely used to analyse survey results, examine customers feedback, analyse reviews and so on. These insights can motivate companies to engage with customers, enhance workflows, and enhance user experiences.

In this study, text mining and sentiment analysis algorithm is used on the reviews on accommodations and restaurants gotten from tourists. There would be implemention of different pre-processing methods like tokenization, stemming and so on. The aim is to fully understand how sentiment analysis is used, the different pre-processing methods, generate wordclouds and how to plot frequency distribution plots.