Sentimental Analysis for Social Media Platform Based on Trend Analysis

Social media platform is one of the most preferable domains of the people of the society where people are primarily using it for the communication, digital marketing, exploring things, gaining knowledge and in some occasions, it stands as the means of taking decisions based on the information gained from it. The abundant information or data on the platform may strive towards right in certain scenarios but it stands as a faulty either in one or in many situations. Sentimental analysis is a difficult task due to the rise of informal and noisy data. There has been a wide and powerful word embedding techniques with large dataset of various categorized word embedding. In this paper we are trying to implement sentiment analysis on the data gained from any social media platform for example consider twitter whereas tweets are raised based on the specific event or topic we are trying to perform sentimental analysis on that data and we are giving the conclusion either as positive or negative based on the data which exists its updates as long as the specific topic is being discussed among the people .The trend favorability is the new feature we are implementing in this paper.