  Social media is increasingly used by humans to express their feelings and
opinions in the form of short text messages. Detecting sentiments in the text
has a wide range of applications including identifying anxiety or depression of
individuals and measuring well-being or mood of a community. Sentiments can be
expressed in many ways that can be seen such as facial expression and gestures,
speech and by written text. Sentiment Analysis in text documents is essentially
a content-based classification problem involving concepts from the domains of
Natural Language Processing as well as Machine Learning. In this paper,
sentiment recognition based on textual data and the techniques used in
sentiment analysis are discussed.
