This includes:
- Finding the most influential node in the tree of tweets
- and seeing if a users follower count impact the level of influence
- checking if there is a correlation
- Finding the most common time tweets are sent
- looking at time difference between tweets and replies
- Conducting simple sentiment analysis to see if most replies to brand campaigns are positive or negative
- Seeing if location has any influence
- what countries tweet about a specific brand campaign the most.
We have divided up the tasks above to equally work on during the week to have completed for our meeting with our supervisor on Friday morning.
We will conduct testing and finishing up documentation and video walkthrough next week.
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