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What Makes a Song Catchy: Insights from a Museum Study, AI, and Professional DJs

What Makes a Song Catchy: Insights from a Museum Study, AI, and Professional DJs
A recent look at what makes a song stick in listeners' heads combines a 2014 museum survey, lists generated by AI tools like ChatGPT, Gemini and Microsoft Copilot, and the perspectives of veteran New Jersey DJ Mark Pomeroy and Atlanta DJ Sloan Lee. While the museum study ranked tracks like the Spice Girls' "Wannabe" as the most recognizable, AI models produced overlapping but varied selections. DJs emphasize beat tempo, crowd vibe, and social media trends such as TikTok as key drivers of catchiness. Together, these viewpoints illustrate that earworms are shaped by rhythm, cultural context, and evolving listener habits. Read more →

What Makes a Song Catchy: Insights from AI, DJs and a Museum Study

What Makes a Song Catchy: Insights from AI, DJs and a Museum Study
A recent look at the factors that make a song stick in listeners' heads combines three perspectives: a 2014 museum survey that identified the most quickly recognized tracks, AI models such as ChatGPT, Gemini and Copilot that list their own "catchiest" songs and professional DJs from New Jersey and Atlanta who share real‑world criteria. The AI answers point to simple melodies, strong beats and tempos that match natural rhythms, while DJs emphasize emotional connection, beats per minute and cultural trends like TikTok. Together these sources reveal a shifting but recognizable set of constants behind ear‑worms. Read more →

What Makes a Song Catchy: Insights from a Museum Study, AI, and Professional DJs

What Makes a Song Catchy: Insights from a Museum Study, AI, and Professional DJs
A recent look at what makes a song stick in listeners' heads combines a 2014 museum survey, lists generated by AI tools like ChatGPT, Gemini and Microsoft Copilot, and the perspectives of veteran New Jersey DJ Mark Pomeroy and Atlanta DJ Sloan Lee. While the museum study ranked tracks like the Spice Girls' "Wannabe" as the most recognizable, AI models produced overlapping but varied selections. DJs emphasize beat tempo, crowd vibe, and social media trends such as TikTok as key drivers of catchiness. Together, these viewpoints illustrate that earworms are shaped by rhythm, cultural context, and evolving listener habits. Read more →

What Makes a Song Catchy: Insights from a Museum Study, AI, and Professional DJs

What Makes a Song Catchy: Insights from a Museum Study, AI, and Professional DJs
A recent look at what makes a song stick in listeners' heads combines a 2014 museum survey, lists generated by AI tools like ChatGPT, Gemini and Microsoft Copilot, and the perspectives of veteran New Jersey DJ Mark Pomeroy and Atlanta DJ Sloan Lee. While the museum study ranked tracks like the Spice Girls' "Wannabe" as the most recognizable, AI models produced overlapping but varied selections. DJs emphasize beat tempo, crowd vibe, and social media trends such as TikTok as key drivers of catchiness. Together, these viewpoints illustrate that earworms are shaped by rhythm, cultural context, and evolving listener habits. Read more →

What Makes a Song Catchy: Insights from AI, DJs and a Museum Study

What Makes a Song Catchy: Insights from AI, DJs and a Museum Study
A recent look at the factors that make a song stick in listeners' heads combines three perspectives: a 2014 museum survey that identified the most quickly recognized tracks, AI models such as ChatGPT, Gemini and Copilot that list their own "catchiest" songs and professional DJs from New Jersey and Atlanta who share real‑world criteria. The AI answers point to simple melodies, strong beats and tempos that match natural rhythms, while DJs emphasize emotional connection, beats per minute and cultural trends like TikTok. Together these sources reveal a shifting but recognizable set of constants behind ear‑worms. Read more →

What Makes a Song Catchy: Insights from AI, DJs and a Museum Study

What Makes a Song Catchy: Insights from AI, DJs and a Museum Study
A recent look at the factors that make a song stick in listeners' heads combines three perspectives: a 2014 museum survey that identified the most quickly recognized tracks, AI models such as ChatGPT, Gemini and Copilot that list their own "catchiest" songs and professional DJs from New Jersey and Atlanta who share real‑world criteria. The AI answers point to simple melodies, strong beats and tempos that match natural rhythms, while DJs emphasize emotional connection, beats per minute and cultural trends like TikTok. Together these sources reveal a shifting but recognizable set of constants behind ear‑worms. Read more →

What Makes a Song Catchy: Insights from a Museum Study, AI, and Professional DJs

What Makes a Song Catchy: Insights from a Museum Study, AI, and Professional DJs
A recent look at what makes a song stick in listeners' heads combines a 2014 museum survey, lists generated by AI tools like ChatGPT, Gemini and Microsoft Copilot, and the perspectives of veteran New Jersey DJ Mark Pomeroy and Atlanta DJ Sloan Lee. While the museum study ranked tracks like the Spice Girls' "Wannabe" as the most recognizable, AI models produced overlapping but varied selections. DJs emphasize beat tempo, crowd vibe, and social media trends such as TikTok as key drivers of catchiness. Together, these viewpoints illustrate that earworms are shaped by rhythm, cultural context, and evolving listener habits. Read more →

What Makes a Song Catchy: Insights from AI, DJs and a Museum Study

What Makes a Song Catchy: Insights from AI, DJs and a Museum Study
A recent look at the factors that make a song stick in listeners' heads combines three perspectives: a 2014 museum survey that identified the most quickly recognized tracks, AI models such as ChatGPT, Gemini and Copilot that list their own "catchiest" songs and professional DJs from New Jersey and Atlanta who share real‑world criteria. The AI answers point to simple melodies, strong beats and tempos that match natural rhythms, while DJs emphasize emotional connection, beats per minute and cultural trends like TikTok. Together these sources reveal a shifting but recognizable set of constants behind ear‑worms. Read more →

What Makes a Song Catchy: Insights from AI, DJs and a Museum Study

What Makes a Song Catchy: Insights from AI, DJs and a Museum Study
A recent look at the factors that make a song stick in listeners' heads combines three perspectives: a 2014 museum survey that identified the most quickly recognized tracks, AI models such as ChatGPT, Gemini and Copilot that list their own "catchiest" songs and professional DJs from New Jersey and Atlanta who share real‑world criteria. The AI answers point to simple melodies, strong beats and tempos that match natural rhythms, while DJs emphasize emotional connection, beats per minute and cultural trends like TikTok. Together these sources reveal a shifting but recognizable set of constants behind ear‑worms. Read more →

What Makes a Song Catchy: Insights from a Museum Study, AI, and Professional DJs

What Makes a Song Catchy: Insights from a Museum Study, AI, and Professional DJs
A recent look at what makes a song stick in listeners' heads combines a 2014 museum survey, lists generated by AI tools like ChatGPT, Gemini and Microsoft Copilot, and the perspectives of veteran New Jersey DJ Mark Pomeroy and Atlanta DJ Sloan Lee. While the museum study ranked tracks like the Spice Girls' "Wannabe" as the most recognizable, AI models produced overlapping but varied selections. DJs emphasize beat tempo, crowd vibe, and social media trends such as TikTok as key drivers of catchiness. Together, these viewpoints illustrate that earworms are shaped by rhythm, cultural context, and evolving listener habits. Read more →