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Ph.D Course/Data Science

History of Rock Music

지식 연주가 Knowledge Designer 2015.01.25 00:50

Here is Big Data Visualization Example: History of Rock Music. Experience big data visualization through SDVS's interactive chart of the top 100 rock and roll songs along with bands and influence. Learn how it was built.

 

Silicon Valley Data Science 라는 회사에서 <History of Rock Music> 제목으로 비주얼라이션한 페이지입니다.  

 

페이지 주소입니다. http://svds.com/rockandroll/#thebeatles

 

 

 http://svds.com/rockandroll/#thebeatles 페이지에서 링크와 함께 자세히 보실 수 있습니다.

 

 

밴드간 네트워크 다이어그램을 보여줍니다. 이미지에 보이는 것처럼 main band blue band 보다 gold band 와 더 유사성을 보이고 있습니다. 크기로 살펴보면 main band blue gold 보다 더 많은 연결성을 가지고 있음을 볼 수 있습니다.

 

 

 

아티스트를 클릭하면 어떠한 밴드들과 연결성이 있는지를 그래프로 보여줍니다. Bob Dylan 을 클릭하니 이런 다이어그램이 나옵니다. 저 위에 있는 그림은 비틀즈가 클릭되어 있는 초기화면입니다. 비틀즈가 Rock & Roll 역사에서 얼마나 많은 영향력을 가지고 있는지 유추해볼 수 있습니다.

 

 

다이어그램의 하단에는 연도가 표기되어 있고, 오른쪽에는 아티스트의 이름이 열거되어 있습니다. 아티스트의 이름을 클릭하면 위에 설명드린대로 네트워크 다이어그램이 나옵니다. 연도를 통해 살펴볼 수 있는 것은 각 아티스트가 어느 시대에 활동했는지입니다. 이 자료를 통해 살펴보면 1970년대에 굉장히 많은 아티스트가 활동한 것을 볼 수 있습니다. Rock 음악의 황금기라고 할 수 있겠네요.

 

 

이 자료는 2011 년에 가디언에서 발표한 Rock and roll 의 대표적인 100 곡을 기반으로, 여러가지 컨텍스트(곡 정보, 에너지, 취향, 밴드간 영향력 지수) 를 더해 구성했다고 합니다.

 


 

About this visualization

 

 Rock is one of the most popular music genre’s today but where did it begin? The following data visualization shows one facet of this complicated answer. In 2011 the Guardian released a list of 100 songs in their editorial judgement represent milestones in the evolution of rock and roll.


From that list we have added deeper context to the song with information about the artists, and analyses of qualitative attributes like energy level, and happy vs. sad. Trace the influence of bands beginning at the origin, Sister Rosetta Tharpe (1919 - 1973), to modern day groups such as Coldplay (1996 - present).


Visually see the “Golden Age” of Rock as song upon song stack around 1970. Below are sections about this site, where to get the data, and how it was built. We would love to hear feedback. You can reach out on Twitter, or by email. Happy exploration!
 


 

Get the data

 

The Guardian

100 songs that are representative of the history of rock


Music Bloodline

Choose an artist and find the bands that influenced that artist, and bands that artist influenced.


Echo Nest

Find data points about a band such as familiarity, news articles, and reviews, and song data such as energy, speechiness, and danceability.


Last.fm

Find data points about a band such as band tracks, last.fm plays, and band photos

 


 

How was this built?

 

Data Manipulation

  Python + Excel

I switched back and forth from Python and Excel for data exploration and data manipulation.
  Mr.Data Converter

A website made by Shan Carter. It is used for converting tabular data into JSON objects. A very simple tool, but it has definitely improved my workflow from data exploration to front-end development.
 

Front End Development

  Gumby + Sass

An open source responsive grid and UI kit. Previously I had been using Bootstrap but I wanted to explore some of the other front-end solutions. Gumby interested me because it was built on Sass, which I also wanted to try.
  Backbone.js

This is a Model-Collection-View JavaScript library. Backbone creates structure for JavaScript code. I’ve learned to love Backbone because the organization it provides is indispensable for making an interactive app.

 

Data Visualization
  Gephi

An open source network graph visualization tool. This was used to analyze the data from Music Bloodline and see the relationship of bands within the Guardian's selection.
  d3.js

Data-Driven Documents, is a JavaScript data visualization library. D3 has been in my toolkit ever since I started front-end development focused on data visualization. The library’s website has many examples of apps built with D3, and the list of examples from the community are extremely helpful.

 

<Source=http://svds.com/rockandroll/#thebeatles> 재구성

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