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LDA.html
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<!DOCTYPE HTML>
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<title>Twitter Topic Modeling</title>
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<a href="index.html" class="title">Shikhar Bharat Shah</a>
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<h1 class="major">Twitter Topic Modeling using LDA</h1>
<span class="image fit"><img src="images/wordcloud.png"/></span>
<p>The aim of this project was to gain a better understanding of the Data Science discussions taking place on Twitter. I first scraped Twitter data relevant to the search term ‘Data Science’ for a period of a day. Performing basic EDA, I analyzed the traffic produced by this search term over a day. Cleaning the text data, I analyzed it further to reveal frequent terms used in discussing 'Data Science' and generated a wordcloud. Furthermore, I used NLP techniques to reveal top 10 words used in the discussions by count. Finally, I used the LDA model to extract the most naturally discussed topics about the field.</p>
<p>The project files can be found <a href="https://github.com/shikhar96/twitter-topic-modeling">here</a>.</p>
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