Event feedback analytic and visualization through Twitter social platform / Muhammad Faiz Sharan

Sharan, Muhammad Faiz (2020) Event feedback analytic and visualization through Twitter social platform / Muhammad Faiz Sharan.

Abstract

Social media such as Twitter, Facebook and Instagram are the most used platform by people in creating and sharing content. Nowadays, it has been used widely not only by individual but also by businesses to enhance their business scale and optimize their marketing efforts as social media can generate a huge amount of information be it positive feedback or negative feedback. Currently, Twitter is one of famously used social media that it used by businesses around the globe as it provides important insight that is essential to their business. However, there are some businesses such as event planner and event organizer that still used traditional method in collecting feedback by using paper survey which tend to influence human error such as bias and random answers. Besides, it also difficult to analyses the feedback as the information collected need to be summarize manually one by one. Normally traditional method also does not promote real time analysis as feedback only collected after the end of the event. This project will help event organizer to collect, analyses and visualize the feedback from Twitter automatically without much technical effort. The sentiment of the feedback will be classify using machine learning algorithm in two categories which are positive and negative feedback. The feedback then will be analyzed and visualized in both real-time and historical manner. Functionality testing are also done to the system to ensure that there is no problem especially in the visualization component. Last, the findings of the usability testing show that this system is very suitable to be used in analyzing and visualizing events feedback from Twitter Social platform.

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