The Popularity of The Artist
MAT 259, 2016 Lu Liu
Concept
People use diverse ways to show their favorites.
For example, the popularity of a singer not only could be revealed from music website, but also picture website. I tried to find the connections between these singers and did comparison of the popularity of their arts works in different types social medias(Instagram and Spotify).
Approach
I used the API from Instagram and Spotify.
Instagram: https://www.instagram.com/developer/endpoints/
Spotify: https://developer.spotify.com/web-api/
Process:
The first idea of first version is the picture moving along with the soundwave of specific song.
I found this form(first version) was not enough to present the data itself, so I did some revision.
Final Results:
Every circle represents a singer. The line means these two artists have some connections. Clicking the circle, you can see the detail info about this singer. The popularity of his/her/their every album, every track. And the comparion of popularity of each song in Instagram and Spotify.
Press 'b'or'B' to back to main page.
PROJ 3: STUDENT DEFINED VISUALIZATION
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- Posts: 4
- Joined: Wed Jan 06, 2016 1:42 pm
Re: PROJ 3: STUDENT DEFINED VISUALIZATION
Why do people like the SPL?
Visualizing the SPL Yelp reviews
Motivation:
In this project, we try to answer the question of "What do people think of the Seattle Public Library? If we want to explore what do the people think, the first and naive thing that comes to mind is visiting the yelp website and reading the reviews. The more efficient solution is to compress the reviews into one visualization. The visualization will have text from the reviews and images the users took and uploaded themselves.
Steps:
Step 1: Build the database
The first step to tackling this problem was to download the reviews through the Yelp API. Unfortunately, upon checking the Yelp API, I found out that the Yelp API does not provide access to the full review text at this point. At that point, I decided to build my own database. The database consisted of three columns: Review (contains the review text), Images (contains the image names associated with that review), and Image Tags (contains the user-generated labels associated with the images).
Step 2: Extract review tags
The second step was to extract review tags from the review text. Since most of the review texts contained a lot of unimportant and common words, I used manual feature selection to get the most important features of the review. The third step was visualizing the review features and the images uploaded by the users.
Preliminary Results:
This list contains some of the reasons of why people like the SPL. These were obtained after the review tags extraction phase.
The idea in the visualization is positioning the extracted features and the images around the Seattle Space Needle which is an observation tower in Seattle, Washington, a landmark of the Pacific Northwest, and an icon of Seattle. I positioned the title "Why do people like the Seattle Public Library?" in the middle of the visualization as shown in Fig. . The images were placed above the title. Underneath the title, I positioned the extracted features from the review tags using the library word crammer. The library positions the text and also controls the size of the text by positively correlating it with the number of repetitions in the text corpse. When the visualization process is run, the words start to appear incrementally as seen in the first image in this section. Pressing any number in the range 0-9 will result in changing the images at the top of the visualization so that you can view different images from different users.
Final visualizations
Attached are different views of the visualization.
Visualizing the SPL Yelp reviews
Motivation:
In this project, we try to answer the question of "What do people think of the Seattle Public Library? If we want to explore what do the people think, the first and naive thing that comes to mind is visiting the yelp website and reading the reviews. The more efficient solution is to compress the reviews into one visualization. The visualization will have text from the reviews and images the users took and uploaded themselves.
Steps:
Step 1: Build the database
The first step to tackling this problem was to download the reviews through the Yelp API. Unfortunately, upon checking the Yelp API, I found out that the Yelp API does not provide access to the full review text at this point. At that point, I decided to build my own database. The database consisted of three columns: Review (contains the review text), Images (contains the image names associated with that review), and Image Tags (contains the user-generated labels associated with the images).
Step 2: Extract review tags
The second step was to extract review tags from the review text. Since most of the review texts contained a lot of unimportant and common words, I used manual feature selection to get the most important features of the review. The third step was visualizing the review features and the images uploaded by the users.
Preliminary Results:
This list contains some of the reasons of why people like the SPL. These were obtained after the review tags extraction phase.
- big children's section
filled with light
cool building
modern engineering marvel
Designed by famed architect Rem Koolhaas
built in 2004
view from the top floor will stop your heart
final escalator down with it's neon lighting
terrific little store in the lobby to buy some great souvenirs
beautiful architecture
10 floors of just quiet and peaceful people doing work
people just relaxing
favorite floor is the third where the "Living Room" is small cafe
open floor
SO QUIET
ton of people
amazing architecture
10 floors of pure awesomeness
10th floor highest view point
9th floor map room
really short bathroom stall doors
worth the stop
Beautiful library
plenty of seating
meetings at the auditorium
great resources for business and market research
helpful librarians
click to chat feature on website
good customer experience
Seahawks-themed library cards.
best library
crazy fast wi
The idea in the visualization is positioning the extracted features and the images around the Seattle Space Needle which is an observation tower in Seattle, Washington, a landmark of the Pacific Northwest, and an icon of Seattle. I positioned the title "Why do people like the Seattle Public Library?" in the middle of the visualization as shown in Fig. . The images were placed above the title. Underneath the title, I positioned the extracted features from the review tags using the library word crammer. The library positions the text and also controls the size of the text by positively correlating it with the number of repetitions in the text corpse. When the visualization process is run, the words start to appear incrementally as seen in the first image in this section. Pressing any number in the range 0-9 will result in changing the images at the top of the visualization so that you can view different images from different users.
Final visualizations
Attached are different views of the visualization.