Sentiment Classification of Tourist's Opinion on Tourist Places of Interest in South India using Tweet Reviews

The emergent technology has been increasingly incorporated with the tourism industry. In the digital world, social media plays an important role in identifying the most visited tourist places. More than 80% of people commonly used the social media platform called 'Twitter'. By using tweet reviews, tourists around the world know about the feelings, suggestions and opinions of most visited tourist places in the selected region. This paper recommends an approach for the development of trip planning in South India based on tourist's preferences. For the research, we use Twitter Application Programming Interface to collect information about the most visited tourist places in South India by using tweets reviews and store it as South India Tourism Tweet reviews database. This paper mainly focuses on analyzing Twitter reviews, which are very helpful to locate the most visited tourist place. In the tweets where reviews are mostly unstructured and heterogeneous, which are then classified into positive tweets, negative tweets and neutral tweets by using the preprocessing technique and machine learning algorithm called support vector machine. Performance measures are calculated by using the classification results. Finally, the results are plotted by using the classification results and performance measures as a wordcloud. This can be very useful for tourists to select the most visited tourist locations. The proposed system can satisfy individual tourist needs.