University of Chicago Astrophysicists, Megan Mansfield, a Ph.D., and Darryl Seligman have configured an algorithm to detect the mood of Taylor Swift within her music.  They analyzed over 149 Taylor Swift songs to decode Swift’s emotions and compiled their results in a research paper called, “I Knew You Were Trouble: Emotional Trends in the Repertoire of Taylor Swift.” Mansfield and Seligman combed through nine hours, 43 minutes, and six seconds of music with the algorithm analyzing Taylor’s feelings toward, “the Male in Question” or “MIQ.” The “MIQ” isn’t always male, it could be New York, Selena Gomez, or even her former rival, Katy Perry. Swift’s level of happiness was graded on how Swift feels about herself in a song, her outlook on life in the song, how happy or sad she is in a song, and the beats per minute. Some of the researcher’s findings included, Swift is happier in stronger relationships, she’s unhappier with partners who have blue eyes, and a tool was developed called, “taylorswift” in Python where users can enter their current mood and relationship status and a list of five Taylor Swift songs will be given to match their mood.