Emotion and Sentiments analysis in Social Media Communication (Text)

People when they speak, interact and write convey emotions. The life is an emotion. Emotions play a key role in any kind of decision in affective, social or business area. The emotions are manifested in verbal, facial expressions but also in written texts. Nowadays, with the growth of internet and social media like facebook twitter , many humans interact, in textual manner with each other in large , and exchange ideas, opinions in the web channel or web communities. Emotions in text are very important if we consider that textual interface with the computer is one of the most used. Emotions are treated largely in affective computing that focuses on improving the interaction between user and computer. People express emotions as part of everyday communication. Emotions can be judged by a combination of cues such as facial expressions, prosodies, gestures, and actions. Emotions are also articulated by written texts. Inspired by works in sentiment analysis, this paper explores approaches to automatic detection of emotions in text. I draw from emotion theories in the fields of psychology and linguistics, and use natural language processing and machine learning techniques for automatic emotion detection. In this paper, I describe studies and experiments in manual and automatic recognition of expressions of the six basic emotions (Ekman, 1992) – happiness, sadness, anger, disgust, surprise, and fear – in text form.