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Assignment-11-Text-Mining-01-Elon-Musk, Perform sentimental analysis on the Elon-musk tweets (Exlon-musk.csv), Text Preprocessing: remove both the leading and the trailing characters, removes empty strings, because they are considered in Python as False, Joining the list into one string/text, Remove Twitter username handles from a given twitter text. (Removes @usernames), Again Joining the list into one string/text, Remove Punctuation, Remove https or url within text, Converting into Text Tokens, Tokenization, Remove Stopwords, Normalize the data, Stemming (Optional), Lemmatization, Feature Extraction, Using BoW CountVectorizer, CountVectorizer with N-grams (Bigrams & Trigrams), TF-IDF Vectorizer, Generate Word Cloud, Named Entity Recognition (NER), Emotion Mining - Sentiment Analysis.
Raw dataset having over 16000 tweets (including both sarcastic and non-sarcastic) for researchers aspiring to work on Sarcasm Detection in Hindi.
Preprocessing for tweets dataset using NLTK.
Resource for downloading data from social media sites like Twitter, Facebook,...
COVID19 Tweets 🌎 Geographical Analysis
Determining the correlation between the market value of company respect to the public opinion of that company. And to answer the question that "Does tweet volume have any effect on stock market trading volume?"