giuseppebonaccorso/twitter_sentiment_analysis_word2vec_convnet
Twitter Sentiment Analysis with Gensim Word2Vec and Keras Convolutional Network
This project helps marketers, product managers, or public relations professionals understand public opinion about specific topics, brands, or events by analyzing tweets. It takes raw Twitter data and classifies each tweet as positive or negative, providing insights into general sentiment. This is ideal for anyone needing to quickly gauge public mood from social media conversations.
No commits in the last 6 months.
Use this if you need to automatically sort large volumes of tweets by sentiment (positive or negative) to understand public perception.
Not ideal if you require nuanced sentiment categories beyond positive/negative, such as neutral, mixed, or specific emotions like anger or joy.
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Jupyter Notebook
License
MIT
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Last pushed
Jul 05, 2018
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