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Understanding Relation between Public Sentiments and Government Policy Reforms

机译:理解公众情绪与政府政策改革之间的关系

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Government of any democratic country usually needs to take decisions for the welfare of its citizens and sometimes for political gain. So, whenever government implements any major policy reforms, government collects feedback from citizens of country through surveys. For these surveys data is gathered through different agencies and from the data available on social network sites. Now a days Twitter has become the major source of open data, as it is the platform where people share their views. In this paper tweets posted by people on recently introduced policy by government of India on `Demonetization' are extracted at regular intervals. Especially, whenever any policy change is implemented by government, tweets from the date of reform till the date of next reform is considered for the study. The extracted tweets are analyzed and change in sentiments of citizens related to reform is measured. Data is collected using Twitter API (Application Program Interface) in Python and sentiment analysis is performed using R Programming. Correlation between policy reform related to demonetization and public sentiments are found and the type of correlation is determined.
机译:任何民主国家的政府通常都需要为其公民的福利做出决定,有时则为政治收益。因此,每当政府实施任何重大政策改革时,政府通过调查收集来自国家公民的反馈。对于这些调查,数据通过不同的代理商和社交网站上提供的数据收集。现在,Twitter已成为开放数据的主要来源,因为它是人们分享观点的平台。在本文中,人们在最近引入了印度政府的政策的推文以定期的间隔提取了“天文化”。特别是,每当政府实施任何政策变更时,从改革之日起推文,直到下一步改革的日期被考虑为这项研究。分析了提取的推文,并测量了与改革相关的公民情绪的变化。使用Python中使用Twitter API(应用程序接口)收集数据,并且使用R编程执行情绪分析。发现了与恶魔化和公众情绪相关的政策改革之间的相关性,并确定了相关类型。

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