Topic modeling using Word2Vec and LDA algorithm with Python
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Updated
Jul 10, 2022 - Jupyter Notebook
Topic modeling using Word2Vec and LDA algorithm with Python
Unsupervised machine learning exploration of NBA topics on Twitter.
This project includes Twitter Social Media Analytics, Facebook Graph Analysis and News API Data Analysis. See the final report for full understanding.
Extracting Themes and Sentiments in Birth Control Drug Reviews with DistilBert and LDA Topic Modeling
Topic-modeling on large data (1.85M tweets written in Spanish, ~1M "Spain geolocated", about 'coronavirus' between 2019 to 2020-04-20). Forked from ShuaiW/twitter-analysis (adapted for Python3 to use a discriminative score), mainly for Twitter LDA (Latent Dirichlet allocation using Gibbs sampling, https://lda.readthedocs.io/)
Using the provided dataset which includes various book features, in order to predict the price of books, using various proposed methods and models.
A Case Study On The Rising Omicron Cases and Public Sentiment Analysis using Twitter Data
Using the foundation and understanding of my first approach to song sentiment analysis using lyrics, created a more robust and better approach to this problem.
Scrape Steam/Metacritic reviews and perform LDA topic and sentiment analysis
Text clustering in spark with scala using LDA Model on a TF-IDF matrix
Code Repository for the assignments required for the Natural Language Processing master's course at PSUT.
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