杨 军, 张 侃. “广东陆丰乌坎事件”网络舆情演化研究[J]. 电子科技大学学报社科版, 2013, 15(2).
引用本文: 杨 军, 张 侃. “广东陆丰乌坎事件”网络舆情演化研究[J]. 电子科技大学学报社科版, 2013, 15(2).
YANG Jun , ZHANG Kan. Study on Network Public Opinion of “Guangdong Lufeng Wukan Event”[J]. Journal of University of Electronic Science and Technology of China(SOCIAL SCIENCES EDITION), 2013, 15(2).
Citation: YANG Jun , ZHANG Kan. Study on Network Public Opinion of “Guangdong Lufeng Wukan Event”[J]. Journal of University of Electronic Science and Technology of China(SOCIAL SCIENCES EDITION), 2013, 15(2).

“广东陆丰乌坎事件”网络舆情演化研究

Study on Network Public Opinion of “Guangdong Lufeng Wukan Event”

  • 摘要: 广东“乌坎事件”给全国各地处理群体性事件提供了可资借鉴的范式,被认为具有重大标本意义。网络作为舆论的重要载体,在“乌坎事件”的舆论形成过程中发挥着重要作用。“乌坎事件”发生发展过程中伴随着舆情的生成-集聚-热议-消亡。这个过程表现为:“刺激性信息”导致热点议题形成,信息控制导致网络舆情进入潜伏期;网民与政府意见对立,舆情持续高涨;政府转变态度积极响应,舆情达到有序;新的信息输入导致舆情达到新的有序,舆情在波动中渐趋平稳。通过对新浪微博中有关“乌坎事件”的原创微博以及国内媒体对于该事件的报道情况的分析,能理清该事件网络舆情形成、演变过程的脉落,勾勒出网络舆情由无序向有序转化的轨迹

     

    Abstract: Guangdong “Wukan Event” provides a model for reference for all parts of the country to deal with mass disturbances and is considered to have great symbolic significance. As an important carrier of public opinion, the network played an important role in the public opinion formation process of “Wukan Event”. There is public opinion formation, agglomeration, upsurge and disappearance during the development process of “Wukan Event”. The process is as follows: “excitive information” leads to the formation of hot issues; information control leads network public opinion to incubation period; the netizens and the government hold the opposite opinion, causing continuous public opinion upsurge; the government changes attitude and responds positively, causing orderly public opinion; new information input leads to new orderly public opinion and public opinion disappears in fluctuation. The thesis has an analysis of the original post of “Wukan Event” in Sina Microblog and the report on the event by the domestic media, so as to grasp the formation and evolution process of the network public opinion and chart its transformation from disorder to order

     

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