Mood map visualizes the moods of Korean people in color and
light through textual analysis of their Tweets on Twitter. We create a custom
software program in Processing that searches and analyzes Tweets in Korean
language through the Twitter API. Tweets are analyzed using a text analysis
library that searches for specific strings of Korean characters that describe
certain moods or feelings.There are 6 main categories of feelings or moods we will search
and visualize: joy/pride, love, fear/ shame, anger, pity, and
sadness/frustration. Mood Map cycles through 3 visualization sequences. The
first sequence displays occurrences of tweets in real time. The second sequence
is showing collective data of two moods in past one hour. And the third is
collective data of one mood in a day. This sequence control the intensity of
color associated with each mood/feeling. The 6 mood/feeling categories are
associated with 6 fiber optic illuminators, each with a specific color. Each
illuminator will be paired to two other illuminators through the connection of
fiber optic cables. So as the intensity of certain moods changes over time,
visitors can witness the relative expression of all the moods compared to each
other, changing dynamically over time every 30 seconds. The overall composition
will express a flux of mood, feeling, intensity and time transmitted to a
spatial 3D body.
Mood map is built and exhibited at “Data Curation” in Museum of
Art at Seoul National University.
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