“My ADHD Hellbrain”: A Twitter Data Science Perspective on a Behavioural Disorder

Mike Thelwall (Lead / Corresponding author), Meiko Makita, Amalia Mas-Bleda, Emma Stuart

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
46 Downloads (Pure)


Purpose: Attention deficit hyperactivity disorder (ADHD) is a common behavioural condition. This article introduces a new data science method, word association thematic analysis, to investigate whether ADHD tweets can give insights into patient concerns and online communication needs.

Design/methodology/approach: Tweets matching “my ADHD” (n=58,893) and 99 other conditions (n=1,341,442) were gathered and two thematic analyses conducted. Analysis 1: A standard thematic analysis of ADHD-related tweets. Analysis 2: A word association thematic analysis of themes unique to ADHD.

Findings: The themes that emerged from the two analyses included people ascribing their brains agency to explain and justify their symptoms and using the concept of neurodivergence for a positive self-image. Research limitations: This is a single case study and the results may differ for other topics.

Practical implications: Health professionals should be sensitive to patients’ needs to understand their behaviour, find ways to justify and explain it to others and to be positive about their condition.

Originality/value: Word association thematic analysis can give new insights into the (self-reported) patient perspective.
Original languageEnglish
Pages (from-to)13–34
Number of pages22
JournalJournal of Data and Information Science
Issue number1
Publication statusPublished - 7 Dec 2020


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