Connected Ink

Data Visualization

Reader Map is an interactive data visualization for collectives of web publications. It visualizes the meta data of and inter-connections within a collection of web feeds. With all feeds displayed in one view, the visualization helps the readers to understand which category each publication belongs to, the number of articles published in a previous period, as long as how often the publication updates.


Every feed is represented by one corresponding square. The titles of the web publishers (such as news websites, research organizations, and blogs) are displayed above the squares. 

Different hues of color are used to distinguish the categories of the web feeds. And the transparency reflects the update frequency of the web publications. Web feeds in the same category are represented by squares with the same hue. Squares are also grouped by categories and gathered in allocated locations of the map.


The layout of this map is arranged by a force directed method. To visually make squares from same categories group together, the virtual “spring force” is added between each feed square and the node representing the category it belongs tt

Visualizing publication evolvement

The size of each square indicates the number of articles published by the corresponding publication within a specified period of time.
Visualizing similarity

The similarity in contents is visualized through stroke weight to reflect the connections between different feeds. The similarity is decided based on the meta data of different feeds. The amount of the common labels is here used to reflect the similarity between different feeds.

Grouping and comparing publications
This project was designed and implemented in processing.