Abstract
In this paper, we identify unique textual patterns from popular songs in iGeneration in which people feel comfortable with the Internet and mobile technology to make contact with friends and family through social media sites. To this end, we calibrate data-driven classifiers using terms and their frequencies in the lyrics of Billboard’s Year-End Hot 100 songs between 1965 and 2015. We find that iGeneration shows several contrasting characteristics in terms of long lyrics and frequent emotional terms related to aspiration, self-focus, negation, and curse.
Recommended Citation
Kim, Yong Seog, "Peeking Into Minds of iGeneration via Lyrics of Most Popular Songs over 50 Years" (2019). AMCIS 2019 Proceedings. 1.
https://aisel.aisnet.org/amcis2019/data_science_analytics_for_decision_support/data_science_analytics_for_decision_support/1
Peeking Into Minds of iGeneration via Lyrics of Most Popular Songs over 50 Years
In this paper, we identify unique textual patterns from popular songs in iGeneration in which people feel comfortable with the Internet and mobile technology to make contact with friends and family through social media sites. To this end, we calibrate data-driven classifiers using terms and their frequencies in the lyrics of Billboard’s Year-End Hot 100 songs between 1965 and 2015. We find that iGeneration shows several contrasting characteristics in terms of long lyrics and frequent emotional terms related to aspiration, self-focus, negation, and curse.