<![CDATA[The development of artificial intelligence technology has introduced various tools that support digital design and product development processes, one of which is the Claude Design feature. The emergence of this technology has generated diverse user responses that can be analyzed through social media. This study aims to analyze the sentiment of users on the X platform toward the use of the Claude Design feature using the Support Vector Machine (SVM) method. The research data were obtained by scraping 2,000 posts using the keyword “Claude Design.” The data then underwent preprocessing stages, including cleaning, case folding, tokenization, stopword removal, and lemmatization. Sentiment labeling was performed using the Valence Aware Dictionary and sEntiment Reasoner (VADER) method. After removing neutral data, 1,438 posts remained, consisting of 1,152 positive and 286 negative sentiment posts. Subsequently, features were extracted using Term Frequency–Inverse Document Frequency (TF-IDF) and classified using the SVM algorithm. The evaluation results show that the SVM model achieved an accuracy of 82.29%, precision of 81%, recall of 82%, and an F1-score of 82%. The findings indicate that the majority of users expressed positive sentiment toward Claude Design and demonstrate that the combination of VADER, TF-IDF, and SVM can be effectively applied to sentiment analysis of social media data.]]>
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