Jump into this twitter related dataset and showcase some interesting insights based on the text of the tweet and the stock reference or tagged within the tweet itself.
The goal of this build is to analyze a dataset of tweets that mention a particular stock or stocks and to identify interesting insights based on the text of the tweets and the stock references or tags within the tweets. You will extract features such as the volume of tweets, sentiment of tweets, length of tweets, and time of tweets, and use these features to explore the data and look for trends and patterns. You will then visualize your findings and present your insights in a report or presentation.
This post is part of the Enterprise DNA platform initiative to provide information about the Builds | Tweeter Treads Analysis Category.
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Just stumbled upon this cool Twitter Threads Analysis category, and I’m super excited to dive in! Planning to explore a dataset of tweets about specific stocks—sounds like a fun challenge! Gonna play around with features like tweet volume, sentiment, length, and timing to hunt for those intriguing trends. Btw, I’m a newbie here, so if anyone has tips or insights, feel free to drop them my way! Also, spotted someone mentioning buying Twitter followers. Not really my thing, but hey, different strokes for different folks, right? Oh, and check out socialzinger.com if you’re into that sort of thing! Anyone tried it? Curious to hear your thoughts.