Hotelies & Co. 2950 Project

Preregistration of analyses

Analysis #1

Describe your first analysis here.

One of our key analyses of interest is the combination of a tweet’s sentiment (positive or negative on a scale from 1 to -1) and a congress member’s political affiliation. We are concerned with how these two interactive variables play into the engagement (in views, likes, retweets, comments, etc.) with a tweet, both in totality and in proportion to the congress member’s total follower count.

Analysis #2

Describe your second analysis here.

Another analysis of interest is the ability to predict whether a twitter user has a political leaning towards either more progressive or more conservative ideology. Using a database of buzzwords and their respective “bias” scores (which help indicate political leaning), we plan to analyze the relationship between these buzzwords (and their consequent bias score assignments) and the actual party affiliation of the congress members we’ve sampled tweets from. This will help us to learn if we can realistically predict an individual’s political ideologies based on the words they choose to write in their tweets.