Abstract:
Sentiment analysis, the automated extraction of
expressions of positive or negative attitudes from text has
received considerable attention from researchers during the past
decade. In addition, the popularity of internet users has been
growing fast parallel to emerging technologies; that actively use
online review sites, social networks and personal blogs to express
their opinions. They harbor positive and negative attitudes about
people, organizations, places, events, and ideas. The tools
provided by natural language processing and machine learning
along with other approaches to work with large volumes of text,
makes it possible to begin extracting sentiments from social
media. In this paper we discuss some of the challenges in
sentiment extraction, some of the approaches that have been
taken to address these challenges and our approach that
analyses sentiments from Twitter social media which gives the
output beyond just the polarity but use those polarities in
product profiling, trend analysis and forecasting. Promising
results has shown that the approach can be further developed to
cater business environment needs through sentiment analysis in
social media.
