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St. Mary's University School of Graduate Studies Department of Computer Science A Hybrid Sentiment Classification for Amharic Book Reviews By Must Shakur Guitar A Thesis Submitted to The Department

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How to fill out a hybrid sentiment classification

01

Gather a dataset with labeled sentiment data

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Preprocess the text data by removing stopwords, punctuation, and special characters

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Utilize both supervised and unsupervised learning techniques to classify sentiment

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Combine the output from both approaches to create a hybrid sentiment classification model

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Evaluate the performance of the model using metrics such as accuracy, precision, and recall

Who needs a hybrid sentiment classification?

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Researchers and practitioners in the field of sentiment analysis who aim to improve the accuracy and reliability of their sentiment classification models

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Companies in industries such as marketing, customer service, and social media monitoring that want to better understand customer sentiment and feedback

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What is a hybrid sentiment classification?

A hybrid sentiment classification combines both machine learning algorithms and rule-based systems to analyze and classify sentiments in text data.

Who is required to file a hybrid sentiment classification?

Companies or organizations that want to analyze and categorize sentiments in large amounts of text data may be required to file a hybrid sentiment classification.

How to fill out a hybrid sentiment classification?

To fill out a hybrid sentiment classification, one would need to input text data into a system that utilizes a combination of machine learning algorithms and rule-based systems for sentiment analysis.

What is the purpose of a hybrid sentiment classification?

The purpose of a hybrid sentiment classification is to accurately analyze and categorize sentiments expressed in text data for various purposes such as market research, customer feedback analysis, and social media monitoring.

What information must be reported on a hybrid sentiment classification?

The information reported on a hybrid sentiment classification typically includes the text data being analyzed, the sentiment categories being used, and the results of the sentiment analysis.

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