Danah Almuhaysin project - Sentiment analysis#12
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Danhh-zk wants to merge 1 commit intoGDSC-IAU:masterfrom
Open
Danah Almuhaysin project - Sentiment analysis#12Danhh-zk wants to merge 1 commit intoGDSC-IAU:masterfrom
Danhh-zk wants to merge 1 commit intoGDSC-IAU:masterfrom
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Project Description:
The goal of this project is to analyze a dataset of product reviews and sentiment text to identify positive and negative text.
Description of the dataset:
The data set used in this project consists of several characteristics, but the ones we no longer need have been deleted.
Name: Product name.
Brand: From which company the product was sold
Rating: Rating given by the user on a scale from 1 to 5.
Text title: The address for reviewing the text
Text review: which can be either “positive” or “negative”.
The dataset provides a valuable resource for investigating the correspondence between ratings and sentiment and identifying cases where the sentiment analysis model may have made errors.
To analyze the data, the following steps were carried out:
Data Loading: A set of data has been loaded into a Pandas DataFrame to facilitate data processing and analysis
Detecting the presence of errors or duplication in the data
Classifying data into positive, negative, and neutral
Description of results:
The analysis revealed the number of false positives and negatives in the data set. These values indicate instances where the sentiment analysis model misclassified reviews based on ratings. By examining these results, we can gain insight into the performance of the sentiment analysis model and identify areas for improvement.
By addressing false positives and negatives, we can enhance the accuracy of sentiment analysis, which is crucial for various applications such as customer feedback analysis, brand monitoring, and market research.