Posted on 12/03/2023 6:21:08 AM PST by FarCenter
...
The study involved an existing dataset of over 1,400 participants who completed psychometric questionnaires assessing their moral values and provided information about their favorite artists through Facebook Page Likes.
The researchers then extracted acoustic and lyrical features from the top five songs of each participant's preferred artists.
Using ML algorithms, the team analysed the extracted features to predict participants' moral values.
Various text processing techniques, including lexicon-based methods and BERT-based embeddings, were employed to analyze narrative, moral values, sentiment, and emotions in lyrics.
Additionally, low- and high-level audio features provided via Spotify's API were used to understand encoded information in participants' musical choices, enhancing moral inferences.
The results demonstrated that a combination of lyrical and audio features outperformed basic demographic information in predicting individuals' moral compass.
Specifically, musical elements like pitch and timbre emerged as crucial predictors for values of Care and Fairness, while sentiments and emotions expressed in lyrics were more effective in predicting traits of Loyalty, Authority, and Purity.
"Our findings reveal that music is not merely a source of entertainment or aesthetic pleasure; it is also a powerful medium that reflects and shapes our moral sensibilities," remarked Vjosa Preniqi, lead author of the study and a PhD student in Queen Mary's Centre for Doctoral Training in Data-informed Audience-centric Media Engineering.
"By understanding this connection, we can open up new avenues for music-based interventions that promote positive moral development."
The study's implications extend beyond mere academic curiosity, holding the potential to impact how we engage with and utilise music in diverse aspects of life.
"Our breakthrough can pave the way for applications ranging from personalised music experiences to innovative music therapy and communication campaigns," commented Dr Kyriaki Kalimeri, senior co-author of the study and researcher at ISI Foundation.
(Excerpt) Read more at sciencedaily.com ...
Using music to propagandize with the aid of AI, 101.
They really need a study for that???
I’m unimpressed with Spotify’s algorithm for music suggestions. I tried it in it’s early days and told it I like Petra, Mylon, Barren Cross, and Whitecross. From that it somehow decided I wanted to listen to Sandy Patti, Amy Grant, etc. LOL
I like listening to Led Zeppelin. Backwards.
Like many digital marketers it will get overused to the point of absurdity. Example, looking up an item on the web and suddenly getting ads everywhere for that item.
Second, who are these musicians - I’ve heard of only four of them?
I know, it’s only Rock and Roll but I like it.
I have been feeling “highway to hell” lately.
I’ve heard of Velvet Revolver and Richie Sambora
and I only know Cassie’s name cuz she was suing Sean Combs
never heard of any of the others
“We are excited to continue exploring this rich and uncharted territory.”
The re$ult of mo$t $tudie$: More $tudie$ needed.
England and Italy. No wonder I’d never heard of most of the bands.
Will kagaroo-prosecutor Jack Smith now see if your music choices match President Trump’s and put you under investigation if it does? Do you get extra time for listening to Rich Men North of Richmond more than once?
The premise is ridiculous. Depending on my mood I am as likely to listen to Bach, Miles Davis or Tool.
Does this mean my Social Credit Score will be downgraded because I enjoy DEVO, Social Distortion, Pixies, Talking Heads, Bob Marley and the Wailers, 50 Cent, etc?
What does listening to gangster rap say about someone?
Lol!
I would drive the algorithm nuts.
I like Judas Priest, Iron Maiden, and Nightwish. I also like the Carpenters.
why yes... yes it does... rofl.
Disclaimer: Opinions posted on Free Republic are those of the individual posters and do not necessarily represent the opinion of Free Republic or its management. All materials posted herein are protected by copyright law and the exemption for fair use of copyrighted works.