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images
images
 
 
analogy_test.py
analogy_test.py
 
 
datapreprocessing.py
datapreprocessing.py
 
 
doesnt_match_eval.txt
doesnt_match_eval.txt
 
 
emotionslist.py
emotionslist.py
 
 
evaluation_biased_dataset.py
evaluation_biased_dataset.py
 
 
evaluation_sents.csv
evaluation_sents.csv
 
 
evaluation_unbiased_dataset.py
evaluation_unbiased_dataset.py
 
 
extracthashtags.py
extracthashtags.py
 
 
extractlabeledtweets.py
extractlabeledtweets.py
 
 
generate_training_data.py
generate_training_data.py
 
 
global_paths.py
global_paths.py
 
 
hashtag_cloud.py
hashtag_cloud.py
 
 
modeltrainer.py
modeltrainer.py
 
 
opposite_eval.txt
opposite_eval.txt
 
 
readme.md
readme.md
 
 
semantic_eval.txt
semantic_eval.txt
 
 
swear_words_de.txt
swear_words_de.txt
 
 
tsneplots.py
tsneplots.py
 
 
vector_model_generation.py
vector_model_generation.py
 
 
word_relations.py
word_relations.py
 
 

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Study of word vectors

Study of word2vec and doc2vec models is experimented in this project. The wiki page https://github.com/sivu1/word2vec_study/wiki has a detailed documentation about the various steps followed in this study.

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Study of word2vec and doc2vec on classifying emotions

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machine-learning text-mining study word2vec gensim doc2vec

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