M. Thelwall, Meiko Makita, Amalia Más-Bleda, E. Stuart
{"title":"“My ADHD Hellbrain”: A Twitter Data Science Perspective on a Behavioural Disorder","authors":"M. Thelwall, Meiko Makita, Amalia Más-Bleda, E. Stuart","doi":"10.2478/jdis-2021-0007","DOIUrl":null,"url":null,"abstract":"Abstract 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.","PeriodicalId":92237,"journal":{"name":"Journal of data and information science (Warsaw, Poland)","volume":"6 1","pages":"13 - 34"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of data and information science (Warsaw, Poland)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/jdis-2021-0007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Abstract 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.