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Repository Details
Sentiment analysis on amazon product reviews using machine learning techniques and extracting the strongest positive, negative and neutral reviews using lambda architecture. Sentiment analysis fetches customer's feelings, emotions and attitudes towards the product. The need for this type of analysis has increased to a greater extent. Product manufacturers realized that sentiment analysis is the key to achieve success. The moment the company receives valuable information after sentiment analysis, they would dig deep about the issue. Companies can improve their product weakness and respond to the voice of the customer. Big data systems collect information from a variety of sources. Therefore, the need for Architecture that should deal with the huge amount of data at high velocity is a major requirement. Extracted data should be gathered in an effective database. Using Cassandra makes our data available to do visualization technique. Hence, lambda architecture helps in data-processing to manage massive quantities of data by utilizing both stream and batch processing. This big data system provides some solutions for solving sentiment analysis over massive amounts of data. The final data is gathered and forwarded to visualization in word cloud and text blob by displaying the strongest positive, negative and neutral words.
