(untitled) (International Journal of Innovative Research in Engineering & Management, 2023)
The increasing use of Instagram as a plat form to share travel experiences has led to a vast amount of visual content related to destination images. This study pro poses a machine learning approach to cluster destination images on Instagram. The objective is to identify the under lying patterns and themes in travel images shared on Insta gram, which could provide useful insights for the tourism industry. The study uses a dataset of 10,000 Instagram imag es with destination tags and applies a deep learning approach to extract visual features from the images. K-means cluster ing is then applied to group images based on visual similari ties. The results show that machine learning techniques can be used to cluster destination images on Instagram into meaningful categories such as natural landscapes, cultural landmarks, food, and cityscapes. These insights can be used to develop targeted marketing strategies and improve tour ism experiences.