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Social media quality follows better than quanitty?


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In this post you can easily run the following code to either parse words from a file in Python or crawl a website to grab and tokenize all of the key words.Here is where we got the play text: was using the Pycharm IDE and needed to download the following libraries by entering the following code into a terminal. pip install nltkpip install beautifulsoup4 import nltk# urllib.request#response = urllib.request.urlopen('')#html = bs4 import BeautifulSoup#soup = BeautifulSoup(html, "lxml")#text = soup.get_text(strip=True)# print(text)f = open("file.txt", "r")text = = [t for t in text.split()]# print(tokens)from nltk.corpus import stopwordssr = stopwords.words('english')clean_tokens =...

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BY: Richard Socher, Alex Perelygin, Jean Y. Wu, Jason Chuang, Christopher D. Manning, Andrew Y. Ng and Christopher Potts Abstract Semantic word spaces have been very useful but cannot express the meaning of longer phrases in a principled way. Further progress towards understanding compositionality in tasks such as sentiment detection requires richer supervised training and evaluation resources and more powerful models of composition. To remedy this, we introduce a Sentiment Treebank. It includes fine grained sentiment labels for 215,154 phrases in the parse trees of 11,855 sentences and presents new challenges for sentiment compositionality. To address them, we introduce the...

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