https://github.com/nero103/sentiment_analysis
This is an end-to-end project on a sentiment analysis for a movie, where a machine learning model was used to predict audience sentiment for the movie based on user reviews.
https://github.com/nero103/sentiment_analysis
logistic-regression machine-learning media movie python3 sentiment-analysis tableau tableau-dashboard wescraping
Last synced: 3 months ago
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This is an end-to-end project on a sentiment analysis for a movie, where a machine learning model was used to predict audience sentiment for the movie based on user reviews.
- Host: GitHub
- URL: https://github.com/nero103/sentiment_analysis
- Owner: Nero103
- Created: 2023-07-30T01:13:58.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-02-26T22:52:50.000Z (over 1 year ago)
- Last Synced: 2025-01-26T10:45:25.057Z (4 months ago)
- Topics: logistic-regression, machine-learning, media, movie, python3, sentiment-analysis, tableau, tableau-dashboard, wescraping
- Language: Python
- Homepage:
- Size: 6.4 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Sentiment_Analysis
This is an end-to-end project on sentiment analysis for a movie.
The data was collected from IMDB and Metacritic through the Chrome extension Listly. Four datasets were formatted, preprocessed, and pre-cleaned in Microsoft Excel Power Query. After the datasets were appended together into one dataset in Power Query, the dataset was uploaded into Jupyter Notebook for analysis and the construction of a machine learning algorithm to answer a classification problem. By the end of the analysis, the data was saved into three CSV files so that the data could be properly visualized in Tableau to create a dashboard of some of the findings.