Abstract

Sentiment detection is software for automatically extracting opinions, emotions and sentiments in text. It allows us to track attitudes and feelings on the web. Due to the increased availability of online reviews, comments and opinions in digital form, the sentiment detection of texts has been witnessed a booming interest in recent years for ensuing need to organize them. Sentiment Detection application areas range from financial news, where information about sentiments can be used to predict stock movements, to social media, where user recommendations can determine success or failure of a product. Sentiment detection automatically analyzes user generated content. The aim of this paper is to present an outline for discussion upon a new Research Challenge on Sentiment Analysis. The Researcher also tends to throw light on various aspects of sentiment detection like its scope, advantages disadvantages and practical implications in different sectors.