GitHub - tmandelz/MaKEathonPostFinance: Sentiment & Semantic Analysis for PostFinance Twitter Data

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Sentiment & Semantic Analysis for PostFinance Twitter Data

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Name		Name	Last commit message	Last commit date
Latest commit History 34 Commits
MaKEathon_EDA		MaKEathon_EDA
__pycache__		__pycache__
data		data
ReadMe.txt		ReadMe.txt
build_notes.txt		build_notes.txt
concate_tweets.ipynb		concate_tweets.ipynb
dataframe.py		dataframe.py
english_sentimental_analysis_twitter.ipynb		english_sentimental_analysis_twitter.ipynb
german_sentimental_analyses_twitter.ipynb		german_sentimental_analyses_twitter.ipynb
keywordextraction.py		keywordextraction.py
language.py		language.py
language_distribution.png		language_distribution.png
mlr_train_test_data.ipynb		mlr_train_test_data.ipynb
pull_data.ipynb		pull_data.ipynb
read_cached_data.ipynb		read_cached_data.ipynb
timeseries.py		timeseries.py
timeseries_plot.ipynb		timeseries_plot.ipynb
wordcloud_stores.png		wordcloud_stores.png
wordcloud_tweets_hashtags.png		wordcloud_tweets_hashtags.png
wordcloud_twitter.png		wordcloud_twitter.png
wordcloud_twitter_hashtag.png		wordcloud_twitter_hashtag.png
wordcount.ipynb		wordcount.ipynb

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# Reading App Reviews

Here are a few example scripts to get started. It runs in an azure notebook.

These short examples show how to pull data, save it locally, and do some very basic processing.