Socio-spatial Self-organizing Maps: Using Social Media to Assess Relevant Geographies for Exposure to Social Processes.
Socio-spatial Self-organizing Maps: Using Social Media to Assess Relevant Geographies for Exposure to Social Processes.
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DOI：
10.1145/3274414
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发表时间：
2018-11-01
影响因子：
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通讯作者：
Chunara, Rumi
中科院分区：
文献类型：
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作者：
Relia, Kunal;Akbari, Mohammad;Chunara, Rumi
社交媒体为了解种族主义和同性恋恐惧症等态度提供了一个独特的窗口，接触这些态度很重要，难以衡量，也没有充分研究健康的社会决定因素。然而，来自社交媒体的个人地理定位观测是嘈杂的，并且在地理上不一致。测量风险的现有区域（例如邮政编码）在不相关的行政定义边界内求平均值。因此，为了能够研究在线社会环境措施，如社交媒体上的态度及其与健康结果的可能关系，首先需要一种方法来定义集体的，潜在的社会媒体态度的程度。为了解决这个问题，我们创建了社会空间自组织地图，“SS-SOM”管道，以最好地识别区域的潜在社会态度从Twitter帖子。SS-SOM使用神经嵌入进行文本分类，并增强传统SOM以生成受控数量的非重叠，拓扑约束和主题相似的聚类。我们发现，与使用邮政编码相比，SS-SOM不仅对缺失数据具有鲁棒性，而且使用SS-SOM测量时，易受多种种族主义和同性恋恐惧症相关健康结果影响的男性群体的暴露量变化高达42%。基于措施。
Social media offers a unique window into attitudes like racism and homophobia, exposure to which are important, hard to measure and understudied social determinants of health. However, individual geo-located observations from social media are noisy and geographically inconsistent. Existing areas by which exposures are measured, like Zip codes, average over irrelevant administratively-defined boundaries. Hence, in order to enable studies of online social environmental measures like attitudes on social media and their possible relationship to health outcomes, first there is a need for a method to define the collective, underlying degree of social media attitudes by region. To address this, we create the Socio-spatial-Self organizing map, "SS-SOM" pipeline to best identify regions by their latent social attitude from Twitter posts. SS-SOMs use neural embedding for text-classification, and augment traditional SOMs to generate a controlled number of nonoverlapping, topologically-constrained and topically-similar clusters. We find that not only are SS-SOMs robust to missing data, the exposure of a cohort of men who are susceptible to multiple racism and homophobia-linked health outcomes, changes by up to 42% using SS-SOM measures as compared to using Zip code-based measures.