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Parallel Implementation of Big Data Pre-Processing Algorithms for Sentiment Analysis of Social Networking Data

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Table 1: List of common positive and negative emoticons used in Twitter effectively identify the words with positive and negative polarity
Figure 1: Architecture of the proposed pre-processing framework
Table 2: 61.792 Performance of Word Count
Figure 3: Sample scatter plot for IDF values dataset. The scatter plot shows TF/IDF values for words that occur frequently and those ascending order) out of the 785687 words obtained from the 1.6 million tweets in our that occur in-frequently and how TF/ID

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