Social Media Sentiment Analysis - Twitter

This project gives a method for sentiment analysis specifically aimed to work with
Twitter data (tweets), to consider their length, structure and specific language. The
method employed makes it able to process tweets in near real time. A large amount of
online data, rich web resources are highly unstructured plus such natural language are
not resolvable via machine straightforwardly. The increased demand to capture
opinions of the public concerning sales of a product has led to study of the field
sentiment analysis and opinion mining. Opinion refers to the extraction of lines in raw
data which expresses an opinion. Sentiment analysis classifies polarity of extracted
sentiments into positive, negative and neutral. This type of analysis commonly applies
to analyze the service or product reviews, voice of the purchaser, survey responses
from social media feeds and online to analyze the attitude of the client. A dashboard
has been created to know the opinion regarding sales of the product whether it has
more positive, negative or neutral number. This project will help the product owner to
know opinion and thoughts of the social media user about their product.