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

Timestamp:

Sep 16, 2019, 4:59:56 PM (4 years ago)

Author:

Zuzana Nevěřilová

Comment:

--

private/NlpInPracticeCourse/OpinionSentiment

@@ -22 +22 @@
 == Practical Session ==
 
-=== Czech Sentiment Analysis === 
+=== Sentiment Analysis === 
 
-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.
+In this workshop, we try two methods for opinion mining.
+We 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.
 
 Requirements: python 3, jupyter notebook, modules NLTK, scipy, numpy, pandas, sklearn
 
-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]
+Files: [raw-attachment:cestina20.csv cestina20.csv], [raw-attachment:cestina20_annotation.csv cestina20_annotation.csv],
+[raw-attachment:urbandictionary.csv urbandictionary.csv], [raw-attachment:urbandictionary_annotation.csv urbandictionary_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]
 
 1. Create `<YOUR_FILE>`, a text file named ia161-UCO-01.txt where UCO is your university ID.
+1. Enter the name of the dataset you were working on.
 1. Do tasks marked in the python notebook as TASK X. You don't have to do optional tasks.