摘要
[目的/意义]随着Web2.0时代的到来,社交媒体中涌现了大量有价值的政务舆论信息,其中,公众的政策支持度不仅可以反映新政策的执行效果,也可为后续政策模拟提供若干数据支持。[方法/过程]为探求公共政策舆情支持度的研究方法,本文以新浪微博中关于延迟退休政策的若干博文为研究对象,利用框架语义与词典相结合的方式,从政策目标、政策期望、政策方案、政策对象4个维度识别了民众的情感倾向,最终采用AHP和DF权重测度方法合成了该政策的公众舆情支持度。[结果/结论]研究一方面验证了该模型的有效性,另一方面表明公众对延退政策的非异议性比例仍在可行性标准之下,政府需不断协调各项工作,以确保其顺利推行。
[Purpose/significance] With the arrival of Web 2. 0,a great deal of valuable information about government affairs has emerged in social media,in which the policy support of the public can not only reflect the effect of the new policy,but also provide some data support for the follow-up policy simulation. [Method/process]In order to explore the research methods,this paper takes some micro-blogs about the policy of delaying retirement from Sina Weibo as the research objects,using the method of frame semantics and dictionary to identify people＇s emotion tendency from the dimensions of policy objectives,policy expectations,policy options and policy objects. On this basis,the final public support for this policy is measured by the integration of AHP and DF weighting methods. [Result/conclusion] The results verify the validity of the model,and at the same time show that the proportion of non-objection of the public is under the feasible standard,so the government needs to coordinate the relevant work to ensure the smooth implementation of the policy.
出处
《情报理论与实践》
CSSCI
北大核心
2018年第3期95-100,共6页
Information Studies:Theory & Application
基金
国家自然科学基金青年项目"基于公众网络参与的民生公共政策第三方动态评估机理与方法研究"(项目编号:71503195)
陕西省社会科学基金青年项目(项目编号:2015R020)
中央高校基本科研业务费项目(项目编号:20101155915)的研究成果之一
