Election Sentimental Analysis using Swift

Abstract

The process of identifying and distributing opinions and views which are expressed in a piece of text, especially in order to decide whether the attitude of the user toward particular idea, product is positive, negative, or neutral is known as sentiment analysis. During election days , it's really necessary to determine the mindset of the people towards particular tweets or sentiment. In this project we used twitter API to fetch the data using the unique key provided by the twitter. An user interface is constructed in iOS platform which can be used to search tweet related to the election. These tweets are later classified using a machine learning model(text classifier) provided by CoreML2 which calculates the points with respect to the number of tweets according to its sentiment (Positive, Negative or Neutral). These points are used to determine the actual sentiment of the people towards that particular search. Later , this classified points are displayed in user's screen. Users also can make multiple searches as per their requirement.