Mining social Media Data for Understanding Different views of News

Abstract

Recently, social media is playing a vital role in social networking and sharing of data. Social media
is favored by many users as it is available to millions of people without any limitations to share their opinions, people
share experience and concerns via their status.
Twitter API, twitter4j, is processed to search for the tweets based on the geo location. People’s posts on social
network gives us a better concern to take decision about the particular system. Evaluating such data in social network is
quite a challenging process.
In the proposed system, there will be a workflow to mine the data which integrates both qualitative analysis and
large scale data mining technique. Based on the different prominent themes tweets will be categorized into different
groups. It uses multi label classification technique as each label falls into different categories and all the attributes are
independent to each other. Label based measures will be taken to analyze the results and comparing them with the
existing sentiment analysis technique.