determine which keywords matter as the bitcoin pricing dynamic changes from one phase to another.

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

Project The project can be performed individually or in groups. The maximum number of students in each group will be three students. The projects will utilize a dataset and at least a total of 3 other concepts from the course to perform data analyses, and include: (1) analysis code, (2) a report, and (3) a final presentation. The provided dataset has more than 8 million Bitcoin cryptocurrency-related tweets, scrapped from 2016-01-01 to 2019-03-29, Collecting Tweets containing the keyword Bitcoin or BTC. The dataset has 30 features (columns) that represent different features from twitter object. Also, the second dataset has the daily BTC prices from Sept. 2013 to March 2021, the student can use it to corelate the tweets with the actual BTC prices. The students can utilize the provided datasets for their projects. They also have the option to pick the datasets that fit their own projects’ proposal (The students are strongly encouraged to discuss their ideas with the professor to make sure that their idea and selected datasets are good). Some ideas that can be figured out from this dataset: • Determine which keywords matter as the bitcoin pricing dynamic changes from one phase to another. • Determine the sentiment analysis of the tweets during specific time interval and corelate that with cumulative weekly stock transaction volume and between tweets and stock market moves. • Determine top n accounts (super spreaders) that post tweets and show the dynamic of those accounts through the time. • Determine the dynamic of top keywords posted during a specific time interval (e.g. weekly, monthly etc.) by super spreaders and correlate that stock market moves.

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