Twitter sentiment analysis Based on Ordinal Regression project on Python

Python ideas     podila sai    2021-02-19

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Twitter sentiment analysis Based on Ordinal Regression project abstract

Twitter sentiment analysis Based on Ordinal Regression project description

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The proposed approach consists of first pre-processing tweets and using a feature extraction method that creates an efficient feature. Then, under several classes, these features scoring and balancing. Multinomial logistic regression (SoftMax), Support Vector Regression (SVR), Decision Trees (DTs), and Random Forest (RF) algorithms are used for sentiment analysis classification in the proposed framework. The last module is applying different machine learning classifiers that classify the tweets into high positive, moderate positive, neutral, moderate negative, and high negative. Figure 1 shows the various steps performed for sentiment analysis using machine learning algorithms the proposed model can detect ordinal regression in Twitter using machine learning methods with a good accuracy result. The performance of the model is measured using accuracy, Mean Absolute Error, and Mean Squared Error

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