Text Data Annotator & Sentiment Classifier (AI-Driven Sentiment Analysis)
Engineered an end-to-end NLP pipeline leveraging RoBERTa and BERTopic for audio feedback transformation to sentiment insights. Labeled and categorized textual data extracted from feedback according to sentiment and thematic categories. Ensured high quality and relevance in sentiment classification to support institutional analysis. • Performed sentiment annotation of transcribed text data. • Classified features such as academic strength and infrastructure gaps. • Used Python NLP packages to automate labeling tasks where feasible. • Confirmed annotation accuracy before downstream model development.