Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Research on the Influence of Music

View through CrossRef
As for question 1, based on the directed relationship between influencers and followers, we building a network of musicians based on influential relationships. A Music Influence Evaluation Model (MIEM) was also established, and the model formula is shown in the text. We then select the top 200 artists in the “music influence” ranking to build a subnet. The larger the subnet node, the more lines are extended. Indicating that the node represents the musician’s influence is large and extensive. From the graph, we can see that Bob Dylan is influential, but the breadth of influence is not enough; Miles Davis influenced a wide range of music factions.As for question 2?We have developed a Music Similarity Evaluation Model (MSEM) to calculate the contribution parameters of fifteen different music metrics. Using fully connected neural networks combined with triple loss to solve the answer. According to the characteristics of Triple Loss, we can make the similar nodes in the space closer together and the dissimilar nodes further apart. After training, our neural network is able to distinguish artists very well. The results were obtained: artists within genres are far more similar than artists between genres, and a classification image of musicians from different genres was produced.As for question 3, a comparative plot of characteristics revealed that music genres also have their own particular musical characteristics. The comprehensive analysis concludes that the difference between genres is mainly reflected by the six features of valence, tempo, mode, key, acousticness, and instrumentalness, and this result is verified by k-means clustering. By plotting the percentage of influence as well as the change of musical characteristics, it was concluded that the influence of genres changes over time; some musical characteristics in genres also change over time. Finally, the similarity between each faction is calculated and plotted as a heat map, and the genres with high similarity must have interrelated relationships with each other.As for question 4, we have developed a Music Influence T-test Model (MITM). We hypothesized that “influencers” would not influence followers to create music, and a t-test using SPSS rejected the original hypothesis and concluded that “influencers” would influence followers to create music. Additionally, Contagious Evaluation Model(CEM) was also be created. We established the “contagious” index and calculated the Pearson correlation coefficients between “contagious” and 15 musical characteristics, and obtained the results: energy, loudness, and acousticness are more “contagious” than other characteristics. Results: energy, loudness and acousticness are more “contagious” than other features.As for question 5, a time series plot of the variation for each musical characteristic with year was plotted and the analysis yielded the following conclusion: There are characteristics that signify revolutions in musical evolution from these data. For example, the music after 1960s showed changes characterized by higher rhythmicity, faster tempo, and fewer spoken words. Based on these musical evolutionary changes, combined with the “musical influence” we calculated earlier, we select five musical change-makers: The Beatles, Bob Dylan, The Rolling Stones, Miles Davis and Jimi Hendrix.As for question 6, we combined musical influences to identify the most influential musicians in each genre in each era as dynamic influencers to represent the music of the genre in that period. Creating images of their musical characteristics over time and analyzing them in relation to the history of musical development led to the conclusion that an artist’s musical identity changes with technology, social development, and changes in genre representation?As for question 7, a Network Connectivity Evaluation Model(NCEM) was developed to measure which artists in the music network were heavily influenced by external factors during the time period. The first and middle of the 20th century were found to be highly connected online, and this period coincided with a period of social upheaval, with the Cold War, World War II, the Industrial Revolution, and the rapid development of the Internet having a great impact on music, from which many new musical styles were born.
Title: Research on the Influence of Music
Description:
As for question 1, based on the directed relationship between influencers and followers, we building a network of musicians based on influential relationships.
A Music Influence Evaluation Model (MIEM) was also established, and the model formula is shown in the text.
We then select the top 200 artists in the “music influence” ranking to build a subnet.
The larger the subnet node, the more lines are extended.
Indicating that the node represents the musician’s influence is large and extensive.
From the graph, we can see that Bob Dylan is influential, but the breadth of influence is not enough; Miles Davis influenced a wide range of music factions.
As for question 2?We have developed a Music Similarity Evaluation Model (MSEM) to calculate the contribution parameters of fifteen different music metrics.
Using fully connected neural networks combined with triple loss to solve the answer.
According to the characteristics of Triple Loss, we can make the similar nodes in the space closer together and the dissimilar nodes further apart.
After training, our neural network is able to distinguish artists very well.
The results were obtained: artists within genres are far more similar than artists between genres, and a classification image of musicians from different genres was produced.
As for question 3, a comparative plot of characteristics revealed that music genres also have their own particular musical characteristics.
The comprehensive analysis concludes that the difference between genres is mainly reflected by the six features of valence, tempo, mode, key, acousticness, and instrumentalness, and this result is verified by k-means clustering.
By plotting the percentage of influence as well as the change of musical characteristics, it was concluded that the influence of genres changes over time; some musical characteristics in genres also change over time.
Finally, the similarity between each faction is calculated and plotted as a heat map, and the genres with high similarity must have interrelated relationships with each other.
As for question 4, we have developed a Music Influence T-test Model (MITM).
We hypothesized that “influencers” would not influence followers to create music, and a t-test using SPSS rejected the original hypothesis and concluded that “influencers” would influence followers to create music.
Additionally, Contagious Evaluation Model(CEM) was also be created.
We established the “contagious” index and calculated the Pearson correlation coefficients between “contagious” and 15 musical characteristics, and obtained the results: energy, loudness, and acousticness are more “contagious” than other characteristics.
Results: energy, loudness and acousticness are more “contagious” than other features.
As for question 5, a time series plot of the variation for each musical characteristic with year was plotted and the analysis yielded the following conclusion: There are characteristics that signify revolutions in musical evolution from these data.
For example, the music after 1960s showed changes characterized by higher rhythmicity, faster tempo, and fewer spoken words.
Based on these musical evolutionary changes, combined with the “musical influence” we calculated earlier, we select five musical change-makers: The Beatles, Bob Dylan, The Rolling Stones, Miles Davis and Jimi Hendrix.
As for question 6, we combined musical influences to identify the most influential musicians in each genre in each era as dynamic influencers to represent the music of the genre in that period.
Creating images of their musical characteristics over time and analyzing them in relation to the history of musical development led to the conclusion that an artist’s musical identity changes with technology, social development, and changes in genre representation?As for question 7, a Network Connectivity Evaluation Model(NCEM) was developed to measure which artists in the music network were heavily influenced by external factors during the time period.
The first and middle of the 20th century were found to be highly connected online, and this period coincided with a period of social upheaval, with the Cold War, World War II, the Industrial Revolution, and the rapid development of the Internet having a great impact on music, from which many new musical styles were born.

Related Results

Music and Mysticism
Music and Mysticism
The word “mystic” has a common meaning in philosophical traditions like neo-Platonism and religions (Hindu, Jewish, Christian, and Muslim)—namely the elevation of a human being to ...
Owner Bound Music: A study of popular sheet music selling and music making in the New Zealand home 1840-1940
Owner Bound Music: A study of popular sheet music selling and music making in the New Zealand home 1840-1940
<p>From 1840, when New Zealand became part of the British Empire, until 1940 when the nation celebrated its Centennial, the piano was the most dominant instrument in domestic...
Advancing knowledge in music therapy
Advancing knowledge in music therapy
It is now over 20 years since Ernest Boyer – an educator from the US and, amongst other posts, President of the Carnegie Foundation for the Advancement of Teaching – published his ...
Music Video
Music Video
Music video emerged as the object of academic writing shortly after the introduction in the United States of MTV (Music Television) in 1981. From the beginning, music video was cla...
Does music counteract mental fatigue? A systematic review
Does music counteract mental fatigue? A systematic review
Introduction Mental fatigue, a psychobiological state induced by prolonged and sustained cognitive tasks, impairs both cognitive and physical performance. Several studies have inve...
Folk Music
Folk Music
Folk music, a widely used but controversial term, means oral-tradition music by and for peasants/the working class in regional cultures where there is also a sophisticated art musi...
Dragutin Gostuški’s Television Narrative
Dragutin Gostuški’s Television Narrative
The selection of music combined with the text about music is very important for the effect on the viewer of the television music programs. The interaction between music and text tu...
If I Had Possession over Judgment Day: Augmenting Robert Johnson
If I Had Possession over Judgment Day: Augmenting Robert Johnson
augmentvb [ɔːgˈmɛnt]1. to make or become greater in number, amount, strength, etc.; increase2. Music: to increase (a major or perfect interval) by a semitone (Collins English Dicti...

Back to Top