Analyzing a Literary Representation of the Wilmington Massacre of 1898 Through Natural Language Processing Using Sentiment Analysis

The purpose of this Natural Language Processing (NLP) paper is to discover, learn, and help others to better understand and disclose the sentiment of a fictional and blended, non-fictional story during the period of the Wilmington Riots of 1898 utilizing the literature Hanover; or the Persecution of the Lowly. In addition, the goal of the project is to process the events and sentiments of the characters to derive feeling from the story. We analyzed each sentence and designated a specific sentiment (neutral, positive, negative) and emotion to it. After processing those sentences, we conducted several machine learning processes to try and predict and/or classify the sentiment of a sentence from the text. Although NLP balancing techniques were attempted, our models were not able to predict the sentiment of the sentences at a decent accuracy level. Future work may involve conducting a sentiment analysis on Hanover at a document-level or phrase-level analysis.