Analyzing Consumer Purchase Decisions Toward Eyeshadow Products Through Sentiment Analysis and Social Network Analysis on X (Twitter)

Abstract

This study examined the consumers' decisions on how to purchase eyeshadow products from Twitter/X conversations using Sentiment Analysis and Social Network Analysis (SNA). The research aimed to investigate the sentiment of consumers, interaction, influence of influential people, and communication structures of eyeshadow products in the social media marketing and the social media communication. We employed data collected from Twitter/X through SocialX as a quantitative computational social science approach to the research. The dataset comprised 218 records between January 1, 2026, and April 30, 2026, with eyeshadow, e.g., eye-shadow, eye-shadow review, eye-shadow recommendation, and eye-shadow discussion. We combined sentiment analysis, emotion analysis, text network analysis, trend analysis, and social network analysis to investigate consumers’ interactions and information sharing. We find that Twitter/X discussions regarding eyeshadow products are dominated by suggestions, product reviews, and information sharing. As a result, the sentiment analysis showed that neutral and positive sentiment dominated the discussion and the emotional representation was the most dominant emotion. The Social Network Analysis identified several key actors who are in the network and were involved in connecting discussion clusters and communicating cosmetic information. The findings show that the social media interactions were a major factor in the understanding of consumers’ decision to purchase eyeshadow products. The recommendations, positive perception of the product, and the well-connected digital communication structures of Twitter/X have shown that Twitter/X is a very effective source to exchange product information and to shape cosmetic purchasing in beauty online communities.