Changes between Version 30 and Version 31 of private/AdvancedNlpCourse/OpinionSentiment


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Timestamp:
Sep 16, 2019, 4:59:56 PM (12 months ago)
Author:
Zuzana Nevěřilová
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  • private/AdvancedNlpCourse/OpinionSentiment

    v30 v31  
    2222== Practical Session ==
    2323
    24 === Czech Sentiment Analysis ===
     24=== Sentiment Analysis ===
    2525
    26 In this workshop, we try two methods for opinion mining: we use the automatic translation of Liu's Opinion Lexion. Next, we try to compensate drawbacks of the translated lexicon by computing word vectors in a simple way.
     26In this workshop, we try two methods for opinion mining.
     27We use the Liu's Opinion Lexion. For Czech SA, we use the automatically translated version. Next, we try to compensate drawbacks of the lexicon by computing word vectors in a simple way.
    2728
    2829Requirements: python 3, jupyter notebook, modules NLTK, scipy, numpy, pandas, sklearn
    2930
    30 Files: [raw-attachment:cestina20.csv cestina20.csv], [raw-attachment:cestina20_annotation.csv cestina20_annotation.csv], [raw-attachment:Word_Vectors_and_Sentiment.ipynb Word_Vectors_and_Sentiment.ipynb], [raw-attachment:negative-words.txt negative-words.txt], [raw-attachment:negative-words.txt negative-words-cs.txt], [raw-attachment:negative-words.txt positive-words.txt], [raw-attachment:negative-words.txt positive-words-cs.txt]
     31Files: [raw-attachment:cestina20.csv cestina20.csv], [raw-attachment:cestina20_annotation.csv cestina20_annotation.csv],
     32[raw-attachment:urbandictionary.csv urbandictionary.csv], [raw-attachment:urbandictionary_annotation.csv urbandictionary_annotation.csv]
     33 [raw-attachment:Word_Vectors_and_Sentiment.ipynb Word_Vectors_and_Sentiment.ipynb], [raw-attachment:negative-words.txt negative-words.txt], [raw-attachment:negative-words.txt negative-words-cs.txt], [raw-attachment:negative-words.txt positive-words.txt], [raw-attachment:negative-words.txt positive-words-cs.txt]
    3134
    32351. Create `<YOUR_FILE>`, a text file named ia161-UCO-01.txt where UCO is your university ID.
     361. Enter the name of the dataset you were working on.
    33371. Do tasks marked in the python notebook as TASK X. You don't have to do optional tasks.
    3438