Semantic network analysis of vaccine sentiment in online social media.
Semantic network analysis of vaccine sentiment in online social media.
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DOI：
10.1016/j.vaccine.2017.05.052
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发表时间：
2017-06-22
期刊：
影响因子：
5.5
通讯作者：
Swarup S
中科院分区：
文献类型：
--
作者：
Kang GJ;Ewing-Nelson SR;Mackey L;Schlitt JT;Marathe A;Abbas KM;Swarup S
通过构建和分析来自美国Twitter用户高度共享的网站的疫苗信息的语义网络，检查社交媒体上当前的疫苗情绪;并协助疫苗的公共卫生传播。疫苗犹豫继续导致美国的疫苗接种覆盖率不佳，构成疾病爆发的重大风险，但仍然知之甚少。我们从美国Twitter用户分享的互联网文章中构建了疫苗信息的语义网络。我们分析了由此产生的网络拓扑结构，比较了语义差异，并确定了网络中表达积极，消极和中性疫苗情绪的最突出的概念。积极疫苗情绪的语义网络在话语中表现出更大的凝聚力，而消极疫苗情绪的语义网络更大，连接更少。积极情绪网络以父母为中心，重点是沟通健康风险和益处，强调麻疹，自闭症，HPV疫苗，疫苗-自闭症联系，脑膜炎球菌病和MMR疫苗等医学概念。相反，负面网络以儿童为中心，集中在CDC、疫苗行业、医生、主流媒体、制药公司和美国等组织机构。负面疫苗情绪的普遍性通过不同的信息传递得到了证明，这些信息围绕着对政府组织的怀疑和不信任，这些政府组织传达了支持疫苗积极益处的科学证据。对在线社交媒体中疫苗情绪的语义网络分析可以增强对当前对疫苗的态度和信念的范围和可变性的理解。我们的研究综合了来自跨学科方法的定量和定性证据，以更好地了解公共卫生传播疫苗犹豫的复杂驱动因素，以提高美国的疫苗信心和疫苗接种覆盖率。
To examine current vaccine sentiment on social media by constructing and analyzing semantic networks of vaccine information from highly shared websites of Twitter users in the United States; and to assist public health communication of vaccines. Vaccine hesitancy continues to contribute to suboptimal vaccination coverage in the United States, posing significant risk of disease outbreaks, yet remains poorly understood. We constructed semantic networks of vaccine information from internet articles shared by Twitter users in the United States. We analyzed resulting network topology, compared semantic differences, and identified the most salient concepts within networks expressing positive, negative, and neutral vaccine sentiment. The semantic network of positive vaccine sentiment demonstrated greater cohesiveness in discourse compared to the larger, less-connected network of negative vaccine sentiment. The positive sentiment network centered around parents and focused on communicating health risks and benefits, highlighting medical concepts such as measles, autism, HPV vaccine, vaccine-autism link, meningococcal disease, and MMR vaccine. In contrast, the negative network centered around children and focused on organizational bodies such as CDC, vaccine industry, doctors, mainstream media, pharmaceutical companies, and United States. The prevalence of negative vaccine sentiment was demonstrated through diverse messaging, framed around skepticism and distrust of government organizations that communicate scientific evidence supporting positive vaccine benefits. Semantic network analysis of vaccine sentiment in online social media can enhance understanding of the scope and variability of current attitudes and beliefs toward vaccines. Our study synthesizes quantitative and qualitative evidence from an interdisciplinary approach to better understand complex drivers of vaccine hesitancy for public health communication, to improve vaccine confidence and vaccination coverage in the United States.
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影响因子：
4.1
作者：
Burscher, Bjorn;Vliegenthart, Rens;de Vreese, Claes H.
通讯作者：
de Vreese, Claes H.
DOI：
10.1016/s0022-5371(83)90201-3
发表时间：
1983-01-01
期刊：
JOURNAL OF VERBAL LEARNING AND VERBAL BEHAVIOR
影响因子：
--
作者：
ANDERSON, JR
通讯作者：
ANDERSON, JR
影响因子：
5.4
作者：
COLLINS, AM;LOFTUS, EF
通讯作者：
LOFTUS, EF
影响因子：
5.4
作者：
DELL, GS
通讯作者：
DELL, GS
影响因子：
3.1
作者：
FREEMAN, LC
通讯作者：
FREEMAN, LC