An Effective Framework for design of Dataset Using Twitter.

The rapid expansion of internet usage and related services like social media and blogs has increased people level of expressiveness in day to day life. Social media platforms like Twitter and Facebook facilitate people to interact and exchange opinions about people, products, and services. As a result, a vast amount of data is available online, in form of views, tweets, messages, audio, and videos. An interface is needed to collect gain knowledge and insights from the various tweets, views, and comments. Thus we have proposed the Twitter API-based Interface, able to perform Hashtag search and extract tweets from Twitter along with the ample number of fields related to the Twitter object. Using the interface, the 55 properties of each tweet is collect which uses for further investigations. The python-based library called Tweepy is use to interact with the Twitter API. Due to the availability of real-world data, various issues related to text analysis can be address. The problems such as Sentiment Analysis, Opinion Mining, Implicit and Explicit detection, genuineness of views and Opinion Spam detection can be address using the dataset availability. [ABSTRACT FROM AUTHOR]