MwangiMwaniki/Kenya-Power-Sentiment-Analysis-Model-on-the-Twitter

# Kenya-Power-Sentiment-Analysis-Model-on-the-Twitter ## Defining the Question Kenya Power is the only supplier of Electricity in Kenya. As such,they receive a lot of feedback on their social media channels. One of those channels is Twitter. We will attempt to build a Sentiment Analysis Model on the Twitter feedback and interactions involving Kenya Power. ## Defining Metrics for Success A succesful model will be able to fetch/ scrape Twitter data involving Kenya Power, convert and import the text data into a Pandas DataFrame, pre-process the data by refining it into forms that Natural language Processing can be done. The model should also attach appropriate sentiments to individual tweets in the range of Positive, Neutral and Negative sentiments.A succesful model will also try to build a Neural Network classifier for future Sentiment analysis problems. ## Experimental Design For this project, we will first scrape the appropriate Twitter data before storing it in a Pandas DataFrame. We will then preprocess the data before attaching appropriate sentiments sing NLTK ( Natural Language Toolkit) libraries. We will then build a classifier model for future Sentiment Analysis. ## Contact For Inquiries