%0期刊文章%@ 2368- 7959% I JMIR出版物%V 5%卡塔尔世界杯8强波胆分析 N 4% P e61% T识别和理解使用Twitter联系抑郁症的社区:横剖面研究德约翰，安珀·舒尔茨，艾米丽·英格利森，安珀·拉克马尔，梅金·维滕伯恩，安德里亚·K +密歇根州立大学地理、环境和空间科学系，地理大楼，东兰辛礼堂路673号，密歇根州，48824，美国，1 5173554649，apearson@msu.edu %K抑郁症%K网络%K社会联系%K推特%K推特%K在线社区%D 2018 %7 05.11.2018 %9原始论文%J JMIR Ment健康%G英语%X背景:抑郁症是全球疾病的主要原因，通常以缺乏社会联系为特征。随着社交媒体的兴起，Twitter用户正在寻找基于网络的抑郁症联系。目的:这项研究旨在确定推特用户使用#我的抑郁症看起来像#标签发布推文的社区。一旦确定，我们想要了解哪些社区特征与Twitter用户转向基于网络的社区来谈论抑郁症相关。方法:使用NCapture软件收集2016年5月25日至6月1日美国东北部和华盛顿特区心理健康月期间的推文(n=104)。在绘制推文后，我们使用泊松多水平回归模型来预测每个社区(县)的推文被人口抵消，并根据女性比例、15-44岁人口比例、白人比例、贫困以下人口比例和单人家庭比例进行调整。然后，我们比较了预测的和观察到的计数，并计算出推文指数值(TIVs)来表示推文不足和推文过度。最后，我们利用Pearson相关分析了TIV的社区特征趋势。 Results: We found significant associations between tweet counts and area-level proportions of females, single-person households, and population aged 15-44 years. TIVs were lower than expected (TIV 1) in eastern, seaboard areas of the study region. There were communities tweeting as expected in the western, inland areas (TIV 2). Counties tweeting more than expected were generally scattered throughout the study region with a small cluster at the base of Maine. When examining community characteristics and overtweeting and undertweeting by county, we observed a clear upward gradient in several types of nonprofits and TIV values. However, we also observed U-shaped relationships for many community factors, suggesting that the same characteristics were correlated with both overtweeting and undertweeting. Conclusions: Our findings suggest that Web-based communities, rather than replacing physical connection, may complement or serve as proxies for offline social communities, as seen through the consistent correlations between higher levels of tweeting and abundant nonprofits. Future research could expand the spatiotemporal scope to confirm these findings. %M 30401662 %R 10.2196/mental.9533 %U http://mental.www.mybigtv.com/2018/4/e61/ %U https://doi.org/10.2196/mental.9533 %U http://www.ncbi.nlm.nih.gov/pubmed/30401662