Browsing by Subject "sentiment analysis"

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    A Bayesian Approach to Understanding Music Popularity
    (2015-05-08) Shapiro, Heather
    The Billboard Hot 100 has been the main record chart for popular music in the American music industry since its first official release in 1958. Today, this rank- ing is based upon the frequency of which a song is played on the radio, streamed online, and its sales. Over time, however, the limitations of the chart have become more pronounced and record labels have tried different strategies to maximize a song’s potential on the chart in order to increase sales and success. This paper intends to analyze metadata and audio analysis features from a random sample of one million popular tracks, dating back to 1922, and assess their potential on the Billboard Hot 100 list. We compare the results of Bayesian Additive Regression Trees (BART) to other decision tree methods for predictive accuracy. Through the use of such trees, we can determine the interaction and importance of differ- ent variables over time and their effects on a single’s success on the Billboard chart. With such knowledge, we can assess and identify past music trends, and provide producers with the steps to create the ‘perfect’ commercially successful song, ultimately removing the creative artistry from music making.
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    Shark Week and Public Perceptions of Sharks
    (2019-04-12) O'Donnell, Katie
    Perceptions of predators, and the type of language used when describing them, can influence a person’s decision whether or not to support wildlife conservation. Many shark species are important apex predators that are found in oceans worldwide, giving sharks a unique role in our society. This study investigated social conversations about sharks by using sentiment analysis of the social media platform, Twitter. We wanted to see if popular annual programming, such as Discovery Channel’s Shark Week, influences the language used in public social conversations and how that affects attitudes toward sharks. Sentiment and statistical analyses show that Shark Week affects the sentiment of language used in Twitter conversations about sharks from 2012-2017. This study builds on the growing literature that increases understanding of public sentiment of sharks, which can contribute to more informative and effective policies to better protect sharks.