Sentiment analysis on twitter data using term frequency-inverse document frequency

HIGHLIGHTS

• who: Akash Addiga and Sikha Bagui from the Department of Computer Science, University of West Florida, Pensacola, FL, USA have published the research: Sentiment Analysis on Twitter Data Using Term Frequency-Inverse Document Frequency, in the Journal: (JOURNAL)
• what: The results of this work show that calculating the TF-IDF score of the corpus allows for a more accurate representation of the overall polarity since terms are given a weight based on their uniqueness and relevance rather than just the frequency at which they appear in the corpus. The focus of this study is on . . .
  

   

  

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