Feedback about a product or a service or both is very important aspect of customer satisfaction for any firm. This application crawls Twitter to find and analyse references to any keyword(which is to be analysed) and categorizes the feedback given into three categories i.e, positive, negative and neutral.
Not just classifying, implemented features which helps firm to grasp as much information in less than a minute.
Sometimes known as “opinion mining,” sentiment analysis can let you know if there has been a change in public opinion toward any aspect of your business. Peaks or valleys in sentiment scores give you a place to start if you want to make product improvements, train sales or customer care agents, or create new marketing campaigns.
Languages and Modules Used: Python - Numpy, Pandas, Tweepy, Matplotlib, Seaborn, Scikit-learn, NLTK, Beautiful Soup, Collections, RE, Flask, Highcharts. HTML, Bootstrap, JavaScript, AJAX
Features of the tool: • Save time by viewing results in descending order of polarity • Handling emoticons • Emphasis handling • Location from where the user expressed their views • Preview the popularity of the tweeted user • Access to the followers of users for social connectivity • Can view the results in your preferred language • Efficient and easy data visualisation