<![CDATA[The rise of social media has transformed how information spreads, creating an invaluable resource for analyzing market trends. In the creative industry, where consumer preferences shift rapidly, understanding social media sentiment is critical for businesses aiming to stay ahead of trends. Previous research on sentiment analysis has shown its potential in various fields, but its specific application in the creative industry remains underexplored. This research aims to investigate how social media sentiment analysis can predict market trends in the creative industry. By analyzing social media posts, reviews, and discussions, the study seeks to explore how positive, negative, and neutral sentiments influence market behavior and creative products’ success. The study employs a combination of data mining and sentiment analysis techniques to analyze social media content related to key creative products. Using machine learning algorithms, the research categorizes posts into sentiment categories and correlates them with market trends, such as sales and consumer behavior. A dataset consisting of social media content from multiple platforms over the past year was utilized for analysis. The results show that positive social media sentiment correlates with increased consumer engagement and sales in the creative industry, while negative sentiment predicts a decline in product success.]]>
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