Identify song lyrics sentiment
using AI
Below is a free classifier to identify song lyrics sentiment. Just input your text, and our AI will predict the sentiment of song lyrics - in just seconds.
Contact us for API access
Or, use Nyckel to build highly-accurate custom classifiers in just minutes. No PhD required.
Get started
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("song-lyrics-sentiment", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/song-lyrics-sentiment/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_text_here"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_text_here"}' \
https://www.nyckel.com/v1/functions/song-lyrics-sentiment/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict the sentiment of song lyrics.
This pretrained text model uses a Nyckel-created dataset and has 16 labels, including Angry, Conflicted, Disappointed, Excited, Happy, Hopeful, Indifferent, Melancholic, Negative and Neutral.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the sentiment of song lyrics).
Whether you're just curious or building song lyrics sentiment detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify song lyrics sentiment at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Sentiment Analysis for Music Marketing: This function can analyze song lyrics to determine their overall sentiment, allowing music marketers to craft targeted promotional strategies. By identifying the emotional tone of lyrics, brands can align their marketing campaigns with songs that resonate positively with their audience.
- Music Recommendation Systems: Streaming platforms can utilize this identifier to improve their recommendation algorithms. By analyzing the sentiment of song lyrics, users can receive tailored suggestions that match their mood or preferences, enhancing their listening experience.
- Playlist Curation: Curators and DJs can use the sentiment analysis of song lyrics to create thematic playlists. By categorizing songs based on their emotional content, they can easily compile playlists that evoke specific feelings, such as positivity, nostalgia, or empowerment.
- Content Moderation for Social Media: Social media platforms can implement this function to identify and moderate posts containing song lyrics that may have inappropriate or harmful sentiments. This helps ensure a safer online environment by filtering out lyrics that may promote negativity or hostility.
- Licensing and Sync Analysis: Music supervisors can apply this tool to analyze song lyrics for matching sentiment during film and advertisement licensing. By understanding the emotional impact of lyrics, they can select songs that align with the intended mood of visual content, enhancing emotional engagement.
- Fan Engagement and Insights: Music artists and labels can use sentiment analysis of fan interactions around song lyrics to gain insights into listener emotions. This information can guide future music creation, helping artists to write lyrics that resonate more deeply with their audience.
- Academic Research in Musicology: Researchers can employ this function for studies in musicology, exploring how sentiment in song lyrics evolves over time across different genres. This analysis can contribute to greater understanding of cultural trends and the emotional impact of music within society.