Multi-level Information Communication Function of Social Media after the Jiuzhaigou MS7.0 Earthquake in Sichuan Province
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摘要: 本文以“社交媒体多层次信息流”为概念框架，分析了四川九寨沟7.0级地震发生后，个人、当地的组织、宏观层面的主流媒体使用社交媒体所发挥的作用。通过对微博的数据进行挖掘分析，总结出地震灾害发生后社交媒体所具有的5项功能：人际之间的交流，地方政府、本土组织以及当地媒体的传播渠道，大众传媒信息发布的渠道，信息的收集和分享，微观、中观以及宏观各主体间沟通的渠道。在强震发生后社交媒体有巨大的传播潜力，本文的研究成果对未来大震发生后如何利用社交媒体来应对灾害有一定的借鉴意义。Abstract: Based on the "social media multi-level flow" as the conceptual framework, we analyzed the roles of the mainstream media, individual local organizations, the macro level in social media after the Jiuzhaigou MS7.0 earthquake. After analysed the data of the tweets from Sina-Weibo, we summed up five functions of social media:the interpersonal communication; information from local government, local organizations and local media communication channels; mass media information dissemination channels; information collection and sharing; micro, meso and macro the main communication channel. Social media has great potential impact after a strong earthquake, and can be used to respond more effectively during earthquake emergency in the future.
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Key words:
- Disaster /
- Earthquake /
- Multi-level /
- Social media /
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图 1 社交媒体多层次功能概念模型（Jung等，2014）
Figure 1. Multi level functional conceptual model of social media (after Jung et. al, 2014)
表 1 基础数据列表
Table 1. The list of basic data
信息层级 信息来源 信息内容 数据量 微观 “中国地震台网速报”九寨沟地震速报微博 用户评论 近10万条 中观 30余个微博账号震后72小时数据 粉丝增长数、微博发布数、微博影响力等 近万条 宏观 人民日报、新华社、央视新闻权威媒体微博 粉丝增长数、微博发布数、微博影响力等 3大主流媒体震后72小时数据 
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陈福集, 胡改丽, 2012.网络舆情热点话题传播模式研究.情报杂志, 33(1):97-101, 156. https://www.wenkuxiazai.com/doc/5b2cad45650e52ea551898c2.html 顾福妹, 翟国方, 阮梦乔等, 2012.新媒体背景下的南京市应急管理流程.现代城市研究, (5):88-93. http://wap.cnki.net/touch/web 凯度, 2016. 中国社交媒体影响报告. http://cn.kantar.com. 人民网舆情监控室, 2017. 《九寨沟7. 0级地震政务新媒体传播效果评估及舆论生态变化专项分析报告》. http://weibo.com/ttarticle/p/show?id=2309404144955558855679. 王艳东, 李吴, 王腾等, 2016.基于社交媒体的突发事件应急信息挖掘与分析.武汉大学学报(信息科学版), 41(3):290-297. doi: 10.3969/j.issn.1672-5867.2015.01.021 新华社, 2017. 九寨沟地震造成24人死亡493人受伤. http://news.cctv.com/2017/08/11/ARTIxcoDnPUJXqP9Kw7ReBL7170811.shtml. 殷志强, 赵无忌, 褚宏亮等, 2014."4.20"芦山地震诱发地质灾害基本特征及"5.12"汶川地震对比分析.地质学报, 88(6):1145-1156. https://www.wenkuxiazai.com/doc/9ac8c64859eef8c75ebfb305.html Alexander D. E., 2014. Social media in disaster risk reduction and crisis management. Science & Engineering, 20(3):717-733. Bird D., Ling M. G., Haynes K., 2012. Flooding Facebook:the use of social media during the Queensland and Victorian flood. Australian Journal of Emergency Management, 27(1):27-33. https://www.riskfrontiers.com/pdf/flooding_facebook.pdf David C. C., Ong J. C., Lrgara E. F. T., 2016. Tweeting supertyphoon Haiyan:evolving functions of twitter during and after a disaster event. PLoS One, 11(3):e0150190. doi: 10.1371/journal.pone.0150190 Jung J. Y., Moro M., 2014. Multi-level functionality of social media in the aftermath of the Great East Japan Earthquake. Disasters, 38(S2):123-143. doi: 10.1111/disa.2014.38.issue-s2 Li L., Goodchild M. F., Xu B., et al., 2013. Spatial, temporal, and socioeconomic patterns in the use of Twitter and Flickr. Cartography and Geographic Information Science, 40(2):61-77. doi: 10.1080/15230406.2013.777139 Sakaki T., Okazaki M., Matsuo Y., 2013. Tweet analysis for real-time event detection and earthquake reporting system development. IEEE Transactions On Knowledge and Data Engineering, 25(4):919-931. doi: 10.1109/TKDE.2012.29 -
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