Farhadloo Mohsen, Winneg Kenneth, Chan Man-Pui Sally, Hall Jamieson Kathleen, Albarracin Dolores
University of Illinois at Urbana-Champaign, Champaign, IL, United States.
Annenberg Public Policy Center, University of Pennsylvania, Philadelphia, PA, United States.
JMIR Public Health Surveill. 2018 Feb 9;4(1):e16. doi: 10.2196/publichealth.8186.
Recent outbreaks of Zika virus around the world led to increased discussions about this issue on social media platforms such as Twitter. These discussions may provide useful information about attitudes, knowledge, and behaviors of the population regarding issues that are important for public policy.
We sought to identify the associations of the topics of discussions on Twitter and survey measures of Zika-related attitudes, knowledge, and behaviors, not solely based upon the volume of such discussions but by analyzing the content of conversations using probabilistic techniques.
Using probabilistic topic modeling with US county and week as the unit of analysis, we analyzed the content of Twitter online communications to identify topics related to the reported attitudes, knowledge, and behaviors captured in a national representative survey (N=33,193) of the US adult population over 33 weeks.
Our analyses revealed topics related to "congress funding for Zika," "microcephaly," "Zika-related travel discussions," "insect repellent," "blood transfusion technology," and "Zika in Miami" were associated with our survey measures of attitudes, knowledge, and behaviors observed over the period of the study.
Our results demonstrated that it is possible to uncover topics of discussions from Twitter communications that are associated with the Zika-related attitudes, knowledge, and behaviors of populations over time. Social media data can be used as a complementary source of information alongside traditional data sources to gauge the patterns of attitudes, knowledge, and behaviors in a population.
近期寨卡病毒在全球范围内爆发,引发了推特等社交媒体平台上对此问题的讨论增多。这些讨论可能会提供有关公众对公共政策重要问题的态度、知识和行为的有用信息。
我们试图确定推特上讨论的话题与寨卡相关态度、知识和行为的调查指标之间的关联,不仅基于此类讨论的数量,还通过使用概率技术分析对话内容来确定。
以美国县和周为分析单位,使用概率主题建模,我们分析了推特在线交流的内容,以识别与美国33周内全国代表性调查(N = 33193)中记录的报告态度、知识和行为相关的主题。
我们的分析揭示,与“国会对寨卡的资金投入”、“小头症”、“与寨卡相关的旅行讨论”、“驱虫剂”、“输血技术”以及“迈阿密的寨卡”相关的主题,与我们在研究期间观察到的态度、知识和行为的调查指标相关。
我们的结果表明,随着时间的推移,有可能从推特交流中发现与人群寨卡相关态度、知识和行为相关的讨论主题。社交媒体数据可作为传统数据来源的补充信息源,用于衡量人群中的态度、知识和行为模式。