Applying Clustering Techniques for Efficient Text Mining in Twitter Data
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Date
2015
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Abstract
BCnowledge is the ultimate output of decisions on a
dataset. The revolution of the Internet has made the global
distance closer with the touch on the hand held electronic
devices. Usage of social media sites have increased in the past
decades. One of the most popular social media micro blog is
Twitter. Twitter has millions of users in the world.^In this
paper the analysis of Twitter data is performed through the text
contained in hash tags. After Preprocessing clustering
algorithms are applied on text data. The different clusters igjj compared through various parameters.
alization techniques are used to portray the results from
which inferences like time series and topic flow can be easily
made. The observed results show that the hierarchical
clustering algorithm performs better than other algorithms.