Background: People with non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are stigmatized, partly since ‘non-alcoholic’ is in the name, but also because of obesity, which is a common condition in this group. Stigma is pervasive in social media and can contribute to poorer health outcomes. We examine how stigma and negative feelings concerning NAFLD/NASH and obesity manifest on Twitter. Methods: Using a self-developed search terms index, we collected NAFLD/NASH tweets from May to October 2019 (Phase I). Because stigmatizing NAFLD/NASH tweets were limited, Phase II focused on obesity (November-December 2019). Via sentiment analysis, >5000 tweets were annotated as positive, neutral or negative and used to train machine learning–based Natural Language Processing software, applied to 193 747 randomly sampled tweets. All tweets collected were analysed. Results: In Phase I, 16 835 tweets for NAFLD and 2376 for NASH were retrieved. Of the annotated NAFLD/NASH tweets, 97/1130 (8.6%) and 63/535 (11.8%), respectively, related to obesity and 13/1130 (1.2%) and 5/535 (0.9%), to stigma; they primarily focused on scientific discourse and unverified information. Of the 193 747 non-annotated obesity tweets (Phase II), the algorithm classified 40.0% as related to obesity, of which 85.2% were negative, 1.0% positive and 13.7% neutral. Conclusions: NAFLD/NASH tweets mostly indicated an unmet information need and showed no clear signs of stigma. However, the negative content of obesity tweets was recurrent. As obesity-related stigma is associated with reduced care engagement and lifestyle modification, the main NAFLD/NASH treatment, stigma-reducing interventions in social media should be included in the liver health agenda.
Bibliographical noteFunding Information:
INAB|CERTH?s Institutional Funds, the Norwegian PSC Research Center and Canica A/S. The authors would like to acknowledge the contribution of late Dr Vassilis Koutkias in this work, as the head of INAB|CERTHs eHealth Lab. JVL, CAP and MV-R acknowledge support to ISGlobal from the Spanish Ministry of Science, Innovation and Universities through the ?Centro de Excelencia Severo Ochoa 2019-2023? Programme (CEX2018-000806-S), and from the Government of Catalonia through the ?CERCA Programme?. CAP further acknowledges support from the Secretaria d'Universitats i Recerca de la Generalitat de Catalunya and the European Social Fund as an AGAUR-funded PhD fellow.
The authors would like to acknowledge the contribution of late Dr Vassilis Koutkias in this work, as the head of INAB|CERTHs eHealth Lab. JVL, CAP and MV‐R acknowledge support to ISGlobal from the Spanish Ministry of Science, Innovation and Universities through the ‘Centro de Excelencia Severo Ochoa 2019‐2023’ Programme (CEX2018‐000806‐S), and from the Government of Catalonia through the ‘CERCA Programme’. CAP further acknowledges support from the Secretaria d'Universitats i Recerca de la Generalitat de Catalunya and the European Social Fund as an AGAUR‐funded PhD fellow.
© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
- liver disease
- social media
ASJC Scopus subject areas