Twitter Feeds Sentiment Analysis and Visualization
Arlene R. Caballero, TJPRC · International journal of educational science and research · 2017
Twitter contains enormous amount of data whether structured, semi-structured or unstructured which analysts and decision makers in an institution hardly interpret and describe (Sheela, 2016).The study explored the Twitter profile of a select institution in terms of frequency of posts, number of user interaction, and intensity of trending topics.It focused on Twitter sentiment analysis which classifies the polarity of the twitter comments into negative, positive, and neutral categories.Sentiments were visualized using Sentiment Visualizer as a tool which represents opinion in an emotional scatter diagram mapped with pleasure and stimulation.The methods applied include the use of various twitter analytics and twitter sentiment analysis tools such as Twitonomy, Rapid Miner and Tweet Viz.These tools were performed to over 1,500 tweeter feeds from a select institution user from year end of 2011, until mid of year 2016.It reveals that the intensity of trending topics becomes higher, because other users considered the select institution tweets as a basis of information.The twitter sentiments of the select institution in terms of sentiment polarity turned out to be majority positive while the estimated sentiments were generally visualized as pleasant and acceptable.