Using an LDA Topic Modelling algorithm and Twitter Scraper to draw social media insights from the 2020 explosions in Lebanon.
On the afternoon of 4 August 2020, Twitter was ablaze with people from all over the globe sharing their sentiments on the two explosions which occurred at the port of the city of Beirut, the capital of Lebanon leaving at least 135 people dead and some 5,000 more are injured.
I look at some ways in which we can extract twitter text linked to the event and apply a popular topic modelling algorithm, LDA ( Latent Dirichlet Allocation) to best extract insights from twitter users’ responses to the catastrophe. You can find all the code for this article here.
I also compare Tweepy vs TwitterScraper for extracting Tweepy vs TwitterScraper & seapk to Interpreting an LDA's topics