Spotify + the Machine (Learning): Tracking Song Audio Features

Overview

As the global music streaming industry grows at an increasing rate, with Spotify dominating the market, personalized playlists and recommended artists and songs curated for each user are often the reasons behind these popular streaming platforms. An advantage of Spotify is its API, which allows the researcher to look deeper into the differences between “Happy” and “Sad” music. With Spotify Audio Features, an in-depth analysis of danceability, energy, valence, and more can be used for machine learning. This researcher looked into supervised machine learning algorithms like Support Vector Machines to classify sad and happy music. With the potential in other machine learning algorithms, there is hope for more personalized playlists based on a user’s mood. How Sharing Seemingly Irrelevant Information May Prove to be a Vulnerability Anna Galeano Stuttgart High School, DoDEA Germany Operations Security (OPSEC) is a crucial procedure in the military to protect sensitive information. Compromise of this information is detrimental to the military and its families. Indicators provide clues as to what the critical information (CI) is and oftentimes indicators are present on open source platforms. The purpose of this study is to evaluate the vulnerability of current active duty service members on the social media platforms LinkedIn and Facebook. Both prompt the user to provide and publish their own personal information which may serve as indicators for an adversary. Through the means of a web scraper this data will be extracted and evaluated by a scoring system based on the OPSEC procedure. Organizational Risk Analyzer (ORA) is then used to identify the most influential accounts and establish social networks to be presented in a manner that is comprehensible. Which Freshmen High School Students Have a Higher Social Intelligence: Gamers or Non-gamers? A Quantitative Study Javier Harrington Ramstein High School, DoDEA The purpose of this quantitative study was to test the Social Intelligence of both: gamers and non-gamers freshmen high school students. The study had a sample that consisted of 86 participants. All participants completed an online Social Intelligence Test. In conclusion, the gamers got a higher Social Intelligence score in comparison to the non-gamers group.

Competition history

• JSHS 2023 Category not listed

Resources

• National JSHS abstract book ↗

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