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This report presents text mining data analyses in Python on 3 million tweets associated with a Russian Internet Research Agency. Python libraries(nltk, bs4 and re) is applied to clean the text content in tweets. Moreover, word2vector is also used to explore the similarity of words in tweets mentioning Trump and Clinton.

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JennyYu2017/NLP-and-Visualization-Sentiment-Analysis-with-300MM-Russsian-Troll-Tweets

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NLP and Word Similarity Analysis with Word2Vec on 300MM Russian Troll Tweets

This report presents text mining data analyses in Python on 3 million tweets associated with a Russian Internet Research Agency. The topic of investigation is the attitude of these tweets towards Trump and Clinton.

Python libraries(nltk, bs4 and re) is applied to clean the text content in tweets. Moreover, word2vector is also used to explore similarity of words in tweets mentioning Trump and Clinton.

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This report presents text mining data analyses in Python on 3 million tweets associated with a Russian Internet Research Agency. Python libraries(nltk, bs4 and re) is applied to clean the text content in tweets. Moreover, word2vector is also used to explore the similarity of words in tweets mentioning Trump and Clinton.

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