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We are using YouTube videos to analyze and predict tags associated with each video using Machine Learning techniques and find interesting trends by performing sentiment analysis using Natural Language Processing on the top 10 trending videos in YouTube using title, description and comments.

pengyangwu.github.io/cs1951a/
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webapp
webapp
 
 
README.md
README.md
 
 
accuracy_data.csv
accuracy_data.csv
 
 
accuracy_measure.ipynb
accuracy_measure.ipynb
 
 
actual_predict_tags.ipynb
actual_predict_tags.ipynb
 
 
actual_sentiment_analysis.ipynb
actual_sentiment_analysis.ipynb
 
 
clean.py
clean.py
 
 
commentsFile.csv
commentsFile.csv
 
 
condense.py
condense.py
 
 
condensedStats.csv
condensedStats.csv
 
 
english_condensedStats.csv
english_condensedStats.csv
 
 
features.py
features.py
 
 
final_predicted_data.csv
final_predicted_data.csv
 
 
grabber.py
grabber.py
 
 
mapreduce.py
mapreduce.py
 
 
mostCommonTags.csv
mostCommonTags.csv
 
 
new_predict_tags.ipynb
new_predict_tags.ipynb
 
 
new_sentiment_analysis.ipynb
new_sentiment_analysis.ipynb
 
 
oldCommentsFile.csv
oldCommentsFile.csv
 
 
predicted_data.csv
predicted_data.csv
 
 
predicted_data_sentiment_analysis.ipynb
predicted_data_sentiment_analysis.ipynb
 
 
preprocessed_data.csv
preprocessed_data.csv
 
 
preprocessing.ipynb
preprocessing.ipynb
 
 
raw.json
raw.json
 
 
remove_special_chars_and_foreign_lang.ipynb
remove_special_chars_and_foreign_lang.ipynb
 
 
sentiment_analysis_comments_per_day.ipynb
sentiment_analysis_comments_per_day.ipynb
 
 
sentiment_analysis_of_comments_over_time.csv
sentiment_analysis_of_comments_over_time.csv
 
 
sentiment_analysis_of_predicted_tags.csv
sentiment_analysis_of_predicted_tags.csv
 
 
sentiment_analysis_of_top50_videos.csv
sentiment_analysis_of_top50_videos.csv
 
 
separateComments.py
separateComments.py
 
 
separatedCommentsFile.csv
separatedCommentsFile.csv
 
 
shuffled_preprocessed_data.csv
shuffled_preprocessed_data.csv
 
 
syns.txt
syns.txt
 
 
tempList.txt
tempList.txt
 
 
temp_preprocessed_data.csv
temp_preprocessed_data.csv
 
 
test.json
test.json
 
 
without_duplicates_condensedStats.csv
without_duplicates_condensedStats.csv
 
 
without_duplicates_final_predicted_data.csv
without_duplicates_final_predicted_data.csv
 
 

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youtube_tag_predictor_sentiment_analysis

We are using YouTube videos to analyze and predict tags associated with each video using Machine Learning techniques and find interesting trends by performing sentiment analysis using Natural Language Processing on the top 10 trending videos in YouTube using title, description and comments.

Back end (Part 2): Prepocessing (Extraction, Cleaning and Condensing), Machine Learning and Sentiment Analysis Model

Back end <---

Files: ipython notebook/python

This is the Data Science (CS1951a) Final Project Website [Click Here]

Front end

Front-end source code is here:

https://github.com/pengyangwu/CS1951a

Files: html/css/js

Back end (Part 1): Data Grabbing by YouTube API

Back-end source code is here:

https://github.com/PrestonLaw/CSCI1951AProject/tree/master

About

We are using YouTube videos to analyze and predict tags associated with each video using Machine Learning techniques and find interesting trends by performing sentiment analysis using Natural Language Processing on the top 10 trending videos in YouTube using title, description and comments.

pengyangwu.github.io/CS1951a/

Topics

machine-learning natural-language-processing youtube video sentiment-analysis youtube-video youtube-api nltk recommendation-system trends alert-messages prediction-algorithm prediction-model sentiment-classification alert-plugin performing-sentiment-analysis

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