Creten Silke, Heynderickx Priscilla, Dieltjens Sylvain
Faculty of Arts, KU Leuven, Antwerp, Belgium.
J Health Commun. 2022 Oct 3;27(10):697-705. doi: 10.1080/10810730.2022.2149904. Epub 2022 Dec 15.
People living with dementia are often faced with attitudes indicating stigma. Social media platforms, such as Twitter, can allow for self-expression and support, but can also be used to disseminate misinformation, which can reinforce existing stigma. In the present study, we explore whether the stigma toward dementia is present in Dutch language tweets. In total, 969 tweets containing dementia-related keywords were collected during a period of five months in 2019 and 2020. These were analyzed by means of a sentiment analysis, which we approached as a classification task. The tweets were coded into seven dimensions, i.e., information, joke, metaphor, organization, personal experience, politics, and ridicule, using a semi-automatic machine learning approach. The emerging correlations with our use of Linguistic Inquiry and Word Count software for sentiment analysis validate our approach. In the present study, 9.29% of tweets contain ridicule, propagating stigmatic attitudes on Twitter.
患有痴呆症的人常常面临带有污名化的态度。社交媒体平台，如推特，既可以让人们进行自我表达和获得支持，但也可能被用来传播错误信息，从而强化现有的污名。在本研究中，我们探讨荷兰语推文中是否存在对痴呆症的污名。2019年和2020年的五个月期间，共收集了969条包含痴呆症相关关键词的推文。我们采用情感分析方法对这些推文进行分析，并将其作为一个分类任务来处理。推文使用半自动机器学习方法被编码为七个维度，即信息、笑话、隐喻、组织、个人经历、政治和嘲笑。我们使用语言查询与字数统计软件进行情感分析所呈现出的相关性验证了我们的方法。在本研究中，9.29%的推文包含嘲笑内容，在推特上传播了污名化态度。
