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A small package for sentiments analysis

Project description

Arasents : طھط­ظ„ظٹظ„ ط§ظ„ظ…ط´ط§ط¹ط± ظپظٹ ط§ظ„ظ†طµظˆطµ ط§ظ„ط¹ط±ط¨ظٹط©

Arasents ظ…ظƒطھط¨ط© ط¨ط³ظٹط·ط© ظ„ط§ط³طھظ†طھط§ط¬ ط§ظ„ظ…ط´ط§ط¹ط± ظ…ظ† ط§ظ„ظ†طµ ط§ظ„ط¹ط±ط¨ظٹ طŒ ظ„ط§ طھط³طھط®ط¯ظ… nltk ظˆظ„ط§ ط£ظٹط© ط®ظˆط§ط±ط²ظ…ظٹط© ظ„طھط­ظ„ظٹظ„ ط§ظ„ظ†طµظˆطµ .

ط£ظ†ظ…ط§ط· ط§ظ„ظ…ط´ط§ط¹ط± ط§ظ„طھظٹ ظٹطھظ… ط§ط³طھط®ط±ط§ط¬ظ‡ط§ :

  • Negative : ظ…ط´ط§ط¹ط± ط³ظ„ط¨ظٹط© .
  • positive : ظ…ط´ط§ط¹ط± ط§ظٹط¬ط§ط¨ظٹط©.
  • neutral : ظ…ط´ط§ط¹ط± ظ…ط­ط§ظٹط¯ط© .
  • ط·ط±ظٹظ‚ط© ط§ظ„ط§ط³طھط®ط¯ط§ظ… :

    import arasents
    my_text = arasents.text("ط£ظ†طھ ظ‚ط§ط±ط¦ ط¬ظٹط¯")
    print ( my_text.sentiments() )

    { 'positive': 100.0 , 'text': 'ط£ظ†طھ ظ‚ط§ط±ط¦ ط¬ظٹط¯' }

    import arasents
    my_text = arasents.text('ظ‡ظˆ ظƒط³ظˆظ„ ط¬ط¯ط§')
    print ( my_text.sentiments() )

    { 'negative': 100.0, 'text': 'ظ‡ظˆ ظƒط³ظˆظ„ ط¬ط¯ط§' }

    import arasents
    my_text = arasents.text('ط°ظƒط±ظٹط§طھ ..')
    print ( my_text.sentiments() )

    {'neutral': 100.0, 'text': 'ط°ظƒط±ظٹط§طھ ..'}

    import arasents
    my_text = arasents.text('ظ‡ظٹ ط¬ظ…ظٹظ„ط© ظˆظ„ظƒظ†ظ‡ط§ ط³ظٹط¦ط©')
    print ( my_text.sentiments() )

    {'positive': 50.0, 'negative': 50.0, 'text': 'ظ‡ظٹ ط¬ظ…ظٹظ„ط© ظˆظ„ظƒظ†ظ‡ط§ ط³ظٹط¦ط©'}

    ظ…ظ„ط§ط­ط¸ط§طھ ظ…ظ‡ظ…ط© :

    ط§ظ„ظ…ظƒطھط¨ط© طھط¬ط±ظٹط¨ظٹط© ظˆطھظ… ط§ظ†ط´ط§ط¦ظ‡ط§ ظپظٹ ظ…ط±ط­ظ„ط© ط§ظ„طھط¹ظ„ظ… طŒ ظپظٹ ط§ظ†طھط¸ط§ط± ط§ظ„طھط·ظˆظٹط± .

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