The popular song means buzz business. So the lyrics of the lyricists so much. Music companies spend more money on the popular songs to add to the necessary elements, music companies spend money. But all the songs are more popular? It's difficult to determine which audience will like songs or which songs will get popular overnight. Because, there is a complex mix of different elements in the song. It is not specific how they will be judged. Again, the popular song variety is different at different times, it becomes more difficult to fix. But this difficult task has been made easy by the University of California, Arvin's mathematician Natalia Komarova This week he wrote an article in the 'Royal Society Open Science' magazine. Some of the information behind his popularity has been known.
Natalie used the computer's analysis method when she came back to popularity of the song. It has been found that the songs which can be danced or played in the present times, are more likely to attract customers.Comaro and his colleagues collect music data from 1985 to 2015, to find reasons for the popularity of the song. In this work, they used metadata of popular ganavandar for the use of singing and academic work. They compare with the metadata of these databases, along with how popular songs have come to the top of the list. The metadata used in this case is - the type of music-related information, from which the audience gets an idea about that song.
Researchers have compared the song's metadata to flop or unpopular songs with the song topped as the popular song. They see, the songs of happiness are less. More than sad songs.
In the last three decades in the United Kingdom, the 'Happy' and 'Bright' tags have become rare or a kind of joy and delightful song. Instead, sadly the song of sadness is happening. But this is not reflected in the popular song list. Songs that are top of the list are those songs which have more fun and excitement. The average of songs released in the same year have become more popular than less popular songs than popular songs. Most of the TopCart songs are sung by women artists.
Researchers say these very important information for music company officials.
Researcher Kimmova and her colleagues created special models for her computer using the information found in the study. The computer model that he made can predict whether any song will be popular or not. Generally speaking, if a song is a success, it can be successfully predicted 4 percent, but the success rate in the comarovara system is 75 percent.
Researchers say that, in the popular songs, its content is not all. With this, there is also a situation in the field of music. Especially the influence of artists is influenced. However, the influence of artists' reputation is not very much in the popularity of the song. If the artist's information is included in the case of Komarova, then the popularity of the song is 85 percent successful. It is understood that the fame of the song depends more on the artist's talent than the public. It can be useful for those who do not care for talent in music.