Recent advances in multi-agentic systems (e.g. AutoGen, OpenAI Swarm) allow users to interact with a group of specialised AI agents rather than a single general-purpose agent. Despite the promise of t...

This study examines diachronic trends in stress-related language, sentiment, and lyrical complexity in popular music’s lyrics from 1973 to 2023, exploring how major societal shocks influenced people’s music preferences and offering insights into collective mood management through music. Over 20,000 lyrics of songs in the US Top 100 charts during this period were analyzed using Natural Language Processing techniques, with stress-related language assessed using a dictionary-based approach (LIWC), sentiment estimated via a rule-based sentiment analysis tool (VADER), and complexity via the LZ77 compression algorithm. Our analysis reveals a significant increase in stress-related language, alongside declines in positive sentiment and lyrical complexity over five decades. Surprisingly, societal shocks like COVID-19 coincided with attenuations rather than amplifications of these trends, indicating a preference for emotion-incongruent music, which may serve as a form of emotion regulation, such as escapism. When controlling for long-term trends, we found no significant relationship between income growth and stress or sentiment in lyrics. In contrast, periods of high-stress language corresponded with increased lyrical complexity. These results support the notion that music plays a dual role in collective mood management, functioning as mood management and regulation, depending on the context and intensity of societal emotions.