<![CDATA[Abstract— In recent years, micro-blogs on the Internet have become a popular way of expressing feelings, thoughts, and even communicating opinions about products and services that are common among its users. Collecting user opinions can be an expensive and time-consuming task using conventional methods such as surveys. The sentiment analysis of the customer opinions makes it easier for businesses to understand their competitive value in a changing market and to understand their customer views about their products and services. In this research, Lexicon-Based approach especially AFINN lexicon is implemented to classify user twitter sentiment, throughout which, twitter Micro-blogs data has been collected, pre-processed analyzed, and classified. The results of this research is an android application that could classify users' perspective via tweets into positive and negative, which is represented in a pie chart for Monthly report. Index Terms— Sentiment Analysis, Brand Analysis, Twitter, Android Application]]>
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