期刊文献+

政务新媒体与地方政府信任:来自开通政务微博的证据 被引量:12

New Media for Government Affairs and Trust in Local Governments:Local Governments Opening Micro-Blog Accounts
原文传递
导出
摘要 本文通过机器学习算法收集和整理了中国县级政府政务微博的运营信息,匹配中国家庭追踪调查(China Family Panel Studies,CFPS)2012-2018四轮调查数据,探讨了政务微博如何影响居民对地方政府的信任水平。研究发现,县级政府开通政务微博后,当地居民对县级官员信任程度较均值水平提高11.63%。县级政府发布的政务微博数量越多,居民对县级官员信任程度越高。异质性检验、移动份额工具变量和平行趋势检验等均支持这一结果。本文从“技术赋能”角度丰富了数字政府运用影响政府信任的相关机制研究。县级政府可以通过发布政务微博缓解政务信息不对称,提升政府信任水平,并可以通过转发上级政府微博提升政府信任水平。 This paper adopts machine learning algorithms to collect and organise operational information from the Chinese county-level government’s official micro-blog accounts.Comparing four rounds of data from China Family Panel Studies(CFPS)surveys conducted between 2012 and 2018,it explores how the government’s official micro-blog accounts affect residents’level of trust.The study finds that following the opening of official micro-blog accounts by county-level governments,residents’level of trust in local officials increases significantly by 11.63%compared to the average.The more micro-blog posts the county-level government publishes,the greater the degree of residents’trust in local officials.Heterogeneity tests,mobile shared instrumental variable tests,and parallel trend tests support this result.This research provides new evidence in response to the cutting-edge issue of how government social media platforms affect political attitudes and enriches the relevant mechanisms for studying the use of government digital applications in influencing trust in government from the perspective of“technological empowerment”.County-level governments can use official micro-blog accounts to alleviate information asymmetry and improve their trust levels,and also retweet higher-level micro-blog government posts to increase trust levels.
作者 刘伯凡 赵玉兰 梁平汉 张军 Liu Bofan;Zhao Yulan;Liang Pinghan;Zhang Jun
出处 《世界经济》 CSSCI 北大核心 2023年第5期177-200,共24页 The Journal of World Economy
基金 国家自然科学基金项目(71803149) 国家社科基金重点项目(22AZD033)和国家社科基金青年项目(22CGL067)的支持。
关键词 政务微博 政府信任 政务信息公开 机器学习 双重差分模型 government’s official micro-blog accounts trust in government government information disclosure machine learning difference-in-differences(DID)model
  • 相关文献

参考文献18

二级参考文献460

共引文献1692

同被引文献403

引证文献12

二级引证文献48

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部