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Abstract
Social media are influencing human beings preferences by shaping their attitudes and behaviors.Social media have received more attention nowadays.Public and Private opinion about a wide variety of subjects are expressed and spread continually via numerous social media.Instagram is one of the social media that is gaining popularity and logical marketing.Instagram dominates the digital marketing space,followed closely by Facebook.Sentiment analysis relates to the problem of mining the sentiments from online available data and categorizing the sentiment expressed by a particular entity into at most three preset categories:positive,negative and netural. This Paper emphasized on Instagram posts to learn emotions in Instagrammers life as well as positive things occurred in their life. First conducted a qualitative analysis on sample posts related to human emotions. Human beings have different types of emotions.we calculate only the four type of emotions like Happy, Sad, Anger, Fear, Surprise, Beauty and Excitement. To classify posts reflecting Instagrammers emotions through multilabel classification algorithms is implemented. N Linear Support Vector Machine Learning algorithms are used. The performance of these algorithms is compared in terms of accuracy, precision, recall and F1-Measure. Support Vector Machine learning algorithm have more accuracy than Naïve Bayes Algorithm.