My inspiration of this project became from Neil Harbssion, who could not see colors. His world is black and white, but now he is an artist. Harbssion describes him as a cyborg. Dangling over his forehead is an antenna that curves up and over from the back is his skull. The device, which he calls “eyeborg”, helps him connect him and the color by detect the light frequencies of color hues and translate it into sound frequencies.

Harbission’s artwork burs the boundaries between sight and sound. He can listen to color, and also see sounds.

Here is the how Harbssion sees Biber’s Baby and Beethoven’s Fur Elise.

These made me wonder if normal people without an eyeborg could also participate into this fun with the help of software technology.

We have many phone games that are able to transform the tones, beats, and melody into colors, such as Cosmic DJ, Synesthetic, InSong, which means there is a technology to establish my assumption.

I found Harbssion’s match sheet between sounds and colors from his cyborg company and hope if there is someway I can match the color and sound frequency myself.

In the beginning when I asked around my friend, nobody seemed have this kind of experience. They said the assumption sounds doable, but they do not how to do it. Finally I reached my friend’s friend, who is an artist with CS skills, she said:

“His (Neil Harbssion’s) mapping of tone to color is actually really complex, and he uses frequency to detect the nuances of colors, which is a very laborious and intense process. If you want to do it from a scientific approach of parsing frequency to color, it is not an easy process and you won’t be able to finish in time.”

However, she said, I can also fake it by assigning the color with very basic tone.

I tried several music software and finally came up with one called Mixed in Key 6.

This is a DJ software that simplifies a DJ technique called harmonic mixing. It analyzes MP3 files and determines the musical key of every file.

The basic key of each song from Mixed in Key is showing as a specific number with letter, such as 12B as E major.

My datasets includes, Billboard Hot 100 from 2014 as representation of Western pop music, Melon top 100 from 2014 as representation of Korean pop music, Li Yundi’s Tokyo Concert as representation of classical music, and the sound tracks from Jersey Boys as representation of the Broadway music. By using Mixed in Key 6, I can generate the basic key into letter and match back to basic key in musical notes.

After getting all the basic keys of my music, I use the tableau Public to generate the date into columns and pies.

If we distribute the number of songs with specific notes, we can see that the 4 groups of music have their own “favorable” notes.

(from left to right: billboard, korean, classical, and jersey boy )

For billboard, it will be C minor, D major, D flat Major, D flat minor, and G major.

For Korean music, it will be A minor.

For classical music, it will be C minor and some B-flat minor, D flat, and F sharp major.

For Broadway music, it will be A major, B-flat major, E major, and F minor.

We can have a simple conclusion that note C and A seems apparent more frequent than others.

In the beginning, I used specific color to draw the pie; the color distribution looks very complex and uneven.

Then I started thinking that the match of Harbssion’s mapping has many color in similar tones, and it may be because the color has similar hue tone also reflect to the keys that sound similar for people to hear.

I modified the pies and use the same shade of the color to indicate keys also share similar hues from the map. The distributions look much better now. (from left to right: billboard, korean, classical, and jersey boy )

Looking at the second color pie, it seems all four groups have more even distribution in music tones. And because some color is more brighter, it looks more obvious, such as the orange, representing F#. There is no trend showing that people will be more in favor of one color tone. However, by looking at the pie, we can see that classical music use more F than other genres, and broadway music uses more F#. Theses four genres share similar distribution of note A (green) and D (magenta). And classical music may have more common with broadway music.

There are some limitations of this data project:

1. Mixed in Key 6 is not a software with high accuracy to determine the basic key of a music
2. It may be to broad or rough to only look at the basic key of a music and may mislead the interpretation of a song.
3. Whether the dataset is representative enough

To determine whether is a real trend of music that people like to hear, further research of this project is, indeed, needed.

And it will be on my project proposal.

If more than one people you subscribed retweeted this post, you can also see their “retweet” at the bottom.

When you click “forward” on user A’s retweet, you can see all the retweets made from user A. You can write down your own comment but only 85 characters remain due to pervious comments were being made. You have to share the length. There will be a double slash to separate the two opinions. Weibo considers this as part of your post. So you can delete or edit the previous opinions if you want. One thing about weibo is its privacy. You don’t have to make every tweet public. You can choose to tweet it as visible only to your own friends group. It also applies when you retweet. You can even retweet it via private message. It is like Facebook.

You can go to the original post and check all the forwards (retweet) and comments made directly to the original post. And if you decide to forward directly from the original post, you have 140 characters to comment! Yay!

The “forward” (retweet) and comments allow for more ‘reposted’, engaged, threaded conversation. Twitter users can also share the tweet with her/his followers by retweeting. However, the tweet to be shared can’t be modified.

On weibo, user can do more than that. She or he can add comments or opinions to the retweeted tweet. The opinion is limited to 140 Chinese or 280 western characters.

This is how you “Weibo”.

You can see different potions to insert rich media like images, videos, music, emoticons and polls when you click “more”.

You can see different portions to insert rich media like images, videos, music, emoticons and polls when you click “more”.

Weibo in Chinese means “micro-blogging”, with its hierarchical  comments to the original tweet, it seems quite easy to follow and participate in conversation. Weibo has adopted many features from Facebook to fit into the Twitter platform. These features such as the emoticon which people can use to tweet to total online strangers is a representation of the “online-identity”, which can be very different from the one in real life. Comments made when retweeting or those which are read after the previous tweet is also a process of self-consciousness and self-censorship. If you use Weibo as database to study an Internet phenomenon, the numbers of forwards and comments can show you directly how hot and trendy the post is.

One of the criticisms about Weibo is that it is not simple enough. The conversation may be fun but information can be overwhelming. You cannot directly quote from one comment to reply, which makes it hard to follow (but now Weibo learnt from Twitter again and had the feature of conversation that allows you see the information line). If the original poster deletes her/his post, you can no longer see it, which unlike on Twitter when you RT the tweet, it is on your timeline and no one can take it off.

However, simply being a database or archive, Weibo may have done enough.

Here are some English weibo accounts from celebrities if you want to explore weibo further:

David Beckham,  Stephon Marbury, Alicia Keys.

Happy weiboing!