Is there a rule for deciding dictionary size for sentiment analysis with massive datasets?












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I will be performing sentiment analysis on fiction. I'll be working with around 300 books of 350 pages. Before performing word2vec, can I limit the dictionary size by ignoring less frequent words? If so, what is the rule for defining the size?









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    $begingroup$


    I will be performing sentiment analysis on fiction. I'll be working with around 300 books of 350 pages. Before performing word2vec, can I limit the dictionary size by ignoring less frequent words? If so, what is the rule for defining the size?









    share







    New contributor




    Archan Lagoo is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







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      $begingroup$


      I will be performing sentiment analysis on fiction. I'll be working with around 300 books of 350 pages. Before performing word2vec, can I limit the dictionary size by ignoring less frequent words? If so, what is the rule for defining the size?









      share







      New contributor




      Archan Lagoo is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      I will be performing sentiment analysis on fiction. I'll be working with around 300 books of 350 pages. Before performing word2vec, can I limit the dictionary size by ignoring less frequent words? If so, what is the rule for defining the size?







      nlp word2vec





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      asked 7 mins ago









      Archan LagooArchan Lagoo

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