Twitter能够预测冠心病发生?

2015-01-23 MedSci MedSci原创

Twitter(推特)是一个社交网络及微博客服务的网站,是全球互联网上访问量最大的十个网站之一。它允许用户将自己的最新动态和想法以短信形式发送给手机和个性化网站群,通过快速、及时、直接的传递信息达到对社会各方面产生深远的影响。然而,来自美国宾夕法尼亚大学的研究人员通过最新的研究发现,推特除了作为社会媒体平台以外,还能够有效地指示社区心理状态,并且,它还能够预测冠心病的发病率。 既往的研究发现

Twitter(推特)是一个社交网络及微博客服务的网站,是全球互联网上访问量最大的十个网站之一。它允许用户将自己的最新动态和想法以短信形式发送给手机和个性化网站群,通过快速、及时、直接的传递信息达到对社会各方面产生深远的影响。然而,来自美国宾夕法尼亚大学的研究人员通过最新的研究发现,推特除了作为社会媒体平台以外,还能够有效地指示社区心理状态,并且,它还能够预测冠心病的发病率。

既往的研究发现了一系列可以预示心脏病风险的因素,传统的因素包括吸烟、收入水平等,同时,心理因素,例如压力也是心脏病的重要元凶之一。研究人员认为,从推特的信息中可以获取某个社区的整体心理状况,并且较传统的风险因素更能获取心脏病发病方面的信息。

从研究结果中看出,如果一个社区整体的推特内容中包含负面的情绪较多,如愤怒、压力、疲惫等,则该区域人群患心脏病风险较高。反之亦然。研究人员曾经试图研究社区心理环境对心脏健康的长期影响,但缺乏合适的平台和测量工具。推特的出现则提供了一个潜在的良好的用于公众健康以及心脏健康干预的流行病学研究平台。

Johannes Eichstaedt是宾夕法尼亚大学心理学专业的研究生,也是该研究项目的负责人,带领着整个工作组进行了长期的研究,并将此研究结果发表于Psychological Science杂志。他认为,情绪与身体健康程度密切相关,但人内心的情绪难以通过仪器测量。因此,他们的研究组着力于心理学方向的研究,即从人们书写或语言中表达出来的内容来推断他们的情绪。他们分析了1300多个郡县的推特词频及其当地的健康数据,涵盖了约美国88 %的人口,并随后将这些情绪的变化与生理健康水平进行比较。最终发现,在推特中出现如“憎恨”等极其负面的词语,与该区域的冠心病致死率密切相关。而高频率的积极词语如“美妙”、“伙伴”等,则是冠心病的保护因素。

该研究结果同现有的社会学研究结果相一致,即将多社区多中心的数据联合进行分析,能够更有助于科学家对人群生理健康情况的预测和判断,从而引导和促进社会健康发展。

原始出处

Evan Lerner.Twitter can predict rates of coronary heart disease, according to Penn research.EurekAlert!21-Jan-2015

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  2. [GetPortalCommentsPageByObjectIdResponse(id=2038382, encodeId=b6522038382a1, content=<a href='/topic/show?id=f7c61e90472' target=_blank style='color:#2F92EE;'>#TTE#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=47, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=17904, encryptionId=f7c61e90472, topicName=TTE)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=96f62500201, createdName=12498e67m28暂无昵称, createdTime=Fri Nov 27 11:26:00 CST 2015, time=2015-11-27, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=16245, encodeId=dea516245a3, content=已阅', beContent=null, objectType=article, channel=null, level=null, likeNumber=115, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=da6b7222, createdName=chinayinhan, createdTime=Tue Feb 17 01:01:00 CST 2015, time=2015-02-17, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=15493, encodeId=a5d9154938d, content=明白, beContent=null, objectType=article, channel=null, level=null, likeNumber=88, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20200609/ef6a57dbe7f1489dad7446b7c5217858/d5e4fe65996c4446a029b0f5d056abb1.jpg, createdBy=6b011518214, createdName=午夜星河, createdTime=Sun Feb 15 14:02:00 CST 2015, time=2015-02-15, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=14642, encodeId=c951146422a, content=社交媒体可能预测疾病发生,迁移, beContent=null, objectType=article, channel=null, level=null, likeNumber=169, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=c4a5105539, createdName=lovetcm, createdTime=Sat Jan 24 14:20:00 CST 2015, time=2015-01-24, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=14605, encodeId=0eb81460543, content=真正的大数据, beContent=null, objectType=article, channel=null, level=null, likeNumber=120, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=f0620, createdName=42.122.229.**, createdTime=Fri Jan 23 20:36:00 CST 2015, time=2015-01-23, status=1, ipAttribution=)]
    2015-02-17 chinayinhan

    已阅'

    0

  3. [GetPortalCommentsPageByObjectIdResponse(id=2038382, encodeId=b6522038382a1, content=<a href='/topic/show?id=f7c61e90472' target=_blank style='color:#2F92EE;'>#TTE#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=47, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=17904, encryptionId=f7c61e90472, topicName=TTE)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=96f62500201, createdName=12498e67m28暂无昵称, createdTime=Fri Nov 27 11:26:00 CST 2015, time=2015-11-27, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=16245, encodeId=dea516245a3, content=已阅', beContent=null, objectType=article, channel=null, level=null, likeNumber=115, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=da6b7222, createdName=chinayinhan, createdTime=Tue Feb 17 01:01:00 CST 2015, time=2015-02-17, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=15493, encodeId=a5d9154938d, content=明白, beContent=null, objectType=article, channel=null, level=null, likeNumber=88, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20200609/ef6a57dbe7f1489dad7446b7c5217858/d5e4fe65996c4446a029b0f5d056abb1.jpg, createdBy=6b011518214, createdName=午夜星河, createdTime=Sun Feb 15 14:02:00 CST 2015, time=2015-02-15, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=14642, encodeId=c951146422a, content=社交媒体可能预测疾病发生,迁移, beContent=null, objectType=article, channel=null, level=null, likeNumber=169, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=c4a5105539, createdName=lovetcm, createdTime=Sat Jan 24 14:20:00 CST 2015, time=2015-01-24, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=14605, encodeId=0eb81460543, content=真正的大数据, beContent=null, objectType=article, channel=null, level=null, likeNumber=120, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=f0620, createdName=42.122.229.**, createdTime=Fri Jan 23 20:36:00 CST 2015, time=2015-01-23, status=1, ipAttribution=)]
    2015-02-15 午夜星河

    明白

    0

  4. [GetPortalCommentsPageByObjectIdResponse(id=2038382, encodeId=b6522038382a1, content=<a href='/topic/show?id=f7c61e90472' target=_blank style='color:#2F92EE;'>#TTE#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=47, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=17904, encryptionId=f7c61e90472, topicName=TTE)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=96f62500201, createdName=12498e67m28暂无昵称, createdTime=Fri Nov 27 11:26:00 CST 2015, time=2015-11-27, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=16245, encodeId=dea516245a3, content=已阅', beContent=null, objectType=article, channel=null, level=null, likeNumber=115, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=da6b7222, createdName=chinayinhan, createdTime=Tue Feb 17 01:01:00 CST 2015, time=2015-02-17, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=15493, encodeId=a5d9154938d, content=明白, beContent=null, objectType=article, channel=null, level=null, likeNumber=88, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20200609/ef6a57dbe7f1489dad7446b7c5217858/d5e4fe65996c4446a029b0f5d056abb1.jpg, createdBy=6b011518214, createdName=午夜星河, createdTime=Sun Feb 15 14:02:00 CST 2015, time=2015-02-15, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=14642, encodeId=c951146422a, content=社交媒体可能预测疾病发生,迁移, beContent=null, objectType=article, channel=null, level=null, likeNumber=169, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=c4a5105539, createdName=lovetcm, createdTime=Sat Jan 24 14:20:00 CST 2015, time=2015-01-24, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=14605, encodeId=0eb81460543, content=真正的大数据, beContent=null, objectType=article, channel=null, level=null, likeNumber=120, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=f0620, createdName=42.122.229.**, createdTime=Fri Jan 23 20:36:00 CST 2015, time=2015-01-23, status=1, ipAttribution=)]
    2015-01-24 lovetcm

    社交媒体可能预测疾病发生,迁移

    0

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    2015-01-23 42.122.229.**

    真正的大数据

    0

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