Dita Pramesti

Mental Health Symptom Analysis: A Combined Word2Vec, PCA, and K-Means Clustering Study of Indonesian Facebook Narratives

Mental health problems are increasingly expressed through social media narratives, including Indonesian Facebook communities. However, previous clustering studies often focus on broad discourse themes, user-risk detection, or community-level patterns rather than symptom-oriented mental health expressions. This study pr...

Comparative Performance Analysis of Sentiment-Based and Baseline LSTM for Forecasting Indonesian Banking Stocks

The retail investor base in Indonesia has been expanding at a quick clip with a growing influence of social media conversations and has made public sentiment a possible predictive signal for stock movements. However, the existing studies on Indonesian banking stocks are highly dependent on single-platform sentiment and...

A Transformer-Based Approach to Valence–Arousal Prediction in Mental Health-Related Social Media Texts

Understanding linguistic patterns of depression and anxiety in Indonesian social media text using machine learning classification and topic modeling

This study explores the linguistic markers of depression and anxiety in Indonesian social media text through an integrated model of machine learning classification and topic modeling to suggest that combining classification with topic modeling offers a practical foundation for developing early detection tools and Indon...