The Anatomy of Loneliness

MFA Thesis

PENNSYLVANIA STATE UNIVERSITY

2020

Research Question

How can graphic design translate clinical research on loneliness into forms that hold both scientific rigor and emotional legibility?

Overview

The Anatomy of Loneliness was an MFA thesis investigating how graphic design can mediate between clinical mental health research and the everyday language people use to describe their own experience. The project tested whether data humanism and dual narratives could hold scientific detail without losing emotional weight.

Process

The illustration work started by breaking down clinical research into short visual sequences. The data visualization work grew out of collaboration with Penn State IST students, whose NLP analysis of over 1,000 tweets tagged #depression and #mentalhealth revealed emotional patterns in everyday language — late-night spikes, sarcasm, the ways depression hides inside ordinary words.

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Data Analytics from Literature

Data Analytics from Literature

An illustrated long-form scroll. Children's book-style illustrations animated with Lottie sync to scrolling text, producing a dual narrative where the scientific and the personal are read together.

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Tweet Analysis & Data Visualization

Tweet Analysis & Data Visualization

An interactive Flourish visualization built from the NLP analysis. Viewers can move between aggregate patterns and individual tweets.


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Tweet Analysis & Data Visualization

Tweet Analysis & Data Visualization

An interactive Flourish visualization built from the NLP analysis. Viewers can move between aggregate patterns and individual tweets.


Findings

The project argues that design is not neutral translation: choices in illustration style, narrative pacing, and visualization shape what readers can know and how they are positioned to know it. By holding clinical research and lived language in the same frame, the work proposes that mental health communication can refuse the choice between rigor and resonance.

Anchors : data humanism; data-as-narrative methodology

Set in Jetbrains

Created in Framer

© Anjana Padmakumar