Weighted Summarization of Student Feedback using Sentiment Analysis

Every year massive amount of feedback is gathered from students regarding subjects and its respective faculty. The amount of time to analyze this data manually is a very tedious and time consuming. This is where the summarization feature comes into picture. It extracts important information found in every feedback document. Automatic summarization based on word frequency statistics takes comments and weights them to produce word frequency and then sentence frequency. Also, the sentiment information in these documents belongs to a wide spectrum ranging from positive to negative. SentiWordNet assigns sentiment numerical scores: positive or negative. Thus, providing clues for sentiment analysis. The spell-checker helps to rectify the incorrect words for proper implementation of those two concepts.