การวิเคราะห์โครงข่ายสังคมออนไลน์ที่มีผลต่อการตัดสินใจในการเลือกใช้สารออกฤทธิ์ในผลิตภัณฑ์ให้ความชุ่มชื้นบนผิวหน้า

Abstract

This independent study aims to analyze an online social network in a famous website called "Pantip" by presenting the trend of customer interest on choosing the active ingredients in facial moisturizer products. The investigation was done by collecting customers' opinions on the active ingredients from threads in beauty forum of Pantip website by using Python syntax. The data collecting were analyzed by using tokenization and word count. It was found that the top three most popular active ingredients are collagen, retinol, and niacinamide respectively. By collecting keywords referring to these active ingredients, the customers mentioned collagen in terms of moisture, brightness, and resilience similarly, retinol was mentioned with related to anti-aging, pore firming, and moisture. Lastly, niacinamide was commented about moisture, resilience, and pore firming. When data were plotted and presented by word cloud technique. It can be implied that the top five most popular key words showed similarity in term of types but difference in order. However, the statistical analysis by Friedman test showed that the rank of the key words of the active ingredients showed no considerable difference. Therefore, it can be summarized that the customers commented about the top three active ingredients with no significant difference.