Pemodelan Topik dan Analisis Sentimen pada 'Voices of History: 50 Iconic Speeches' Menggunakan Pendekatan Natural Language Processing

Juniana Husna, Margareth Dyah Anggraini Widirahayu


This study examines various iconic speeches throughout history using Natural Language Processing (NLP) approaches. The selected speeches address a wide range of historical and social issues, ranging from the struggle for civil rights upto the calls for peace.. This analysis is carried out to reveal the sentiments, themes and emotions expressed in each speech, as well as to understand how orators use language to influence and inspire their audience. This study identifies common patterns and themes in these speeches by utilizing text vectorization methods, topic extraction using Latent Dirichlet Allocation (LDA), as well as sentiment and emotion analysis. The findings of this analysis show that the most influential speeches mostly include strong themes such as social justice, freedom, and unity. Furthermore, good thoughts and powerful emotions such as optimism and courage are frequently featured in the most motivating speeches. This research provides valuable insight for historians, researchers, and oratory enthusiasts into how iconic speeches have shaped public opinion and influenced social change.


Natural Language Processing, Sentiment Analysis, Topic Extraction, Text Clustering


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