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ABSTRACT
Recently, social media is playing a vital role in social networking and sharing of data. Social media is favoured by many users as it is available to millions of people without any limitations to share their opinions, educational learning experience and concerns via their status. Twitter API is processed to search
for the tweets based on the geo-location. 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 machine learning technique. Based on the different prominent theme’s tweets will be categorized into different groups. Machine learning classifier will be implemented on mined data for qualitative analysis purpose to get the deeper understanding of the data. 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.
