| dc.description.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. |
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