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Love Lyric Charts

The Sexual Healing Infographic Combines Musician's Words of Affection

The Sexual Healing Infographic gives viewers the information needed to understand love-inspired music. Love is easily the number one topic when it comes to songs, ranging from heartbreak to eternal devotion (that means you Nat King Cole).

Using venn diagrams, one can see what happens when the words of two artists are combined to form the lyrics of another artist. When the Boyz II Men's lyric "I'll make love to you" is combined with Roxy Music's "Love is the drug," you are left with Sexual Healing by Marvin Gaye. There is also a helpful part of the chart that tells you when musicians recommend you make love. Whether you want to have a good time listening to "When the Sun Goes Down" or "All Night Long" is up to you.

To find out what musicians really know about love, check out the full Sexual Healing Infographic.
Trend Themes
1. Love-inspired Music - Opportunity to create platforms or apps that curate and analyze love-themed songs based on lyrics and artist recommendations.
2. Lyric Combinations - Potential for technology solutions that analyze and combine lyrics from different artists to create unique music compositions or remixes.
3. Data Visualization - Opportunity to develop visual charts or infographics that present interesting data and insights about music genres, lyrics, and artist collaborations.
Industry Implications
1. Music Streaming Platforms - Potential for streaming services to enhance their recommendation algorithms by incorporating love-themed music and personalized playlists based on lyrics.
2. Music Production and Remixing - Opportunity for remixing artists or AI-powered music production tools to experiment with combining lyrics from different sources to create new and unique compositions.
3. Data Visualization Tools - Potential for data visualization software companies to develop specialized tools or templates that allow users to create visually appealing infographics or charts specifically for music-related data analysis.
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