Temporal Sentiment Analysis Using Temporal Synset and Metadata

Abstract

Natural language processing is a most common area of research that probe how computer understand and manipulate natural language text or speech to do useful things. Sentiment analysis is one of the active research area in natural language processing. Sentiment analysis is process of determining the emotional tone behind a series of words, distinguishing and classifying opinions expressed in an article, in order to achieve whether the writer’s attitude towards a areas in natural language processing. Sentiment analysis based on temporality is gaining much attention in many real time applications. This manuscript highlights the key concepts of various state-of-art temporal sentiment analysis along with the research gaps. It also put focus on the normalization of various temporal expressions. It covers different temporal expressions and the methods for normalization of these expressions. The main focus is to find the temporal tagging of data. To facilitate the future work, a discussion of state-of-art resources and methods for temporal sentiment analysis is also provided.