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    트윗을 이용한 서울시 주거환경 만족의 공간적 특성 분석 -도시정책지표 보완을 위한 활용방안 모색- = An Analysis of Spatial Characteristics of Residential Satisfaction in Seoul Using Tweet Data -An Applicability of Tweet Data for Complementing Urban Policy Indicators-

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    https://www.riss.kr/link?id=A100004580

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    SNS including twitter, which many people are recording their present day, is being used for inspecting their concern or response to the issue in regard to huge amount of data that are generated as many as several hundred millions a day and users’ voluntary posting of opinions. In this study we conducted a spatial analysis by extracting twitter data containing evaluation on the residential environment among all twitter data recording users’ present condition. In addition, we also divided the key terms which represent evaluation on the residential environment into ‘anxiety’ and ‘dissatisfaction,’ marked the twitter data which include the key terms on the map and then compared the relative distribution with the result of Seoul survey. Even though there are some limitations such as gender or age bias in the case of twitter data, we can confirm that twitter data can be utilized to complement the urban policy indicators in that we can obtain two kinds of information such as the voluntary opinions which can not be attained in the urban policy indicators and the regional micro information which include spatial information.
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    SNS including twitter, which many people are recording their present day, is being used for inspecting their concern or response to the issue in regard to huge amount of data that are generated as many as several hundred millions a day and users’ vo...

    SNS including twitter, which many people are recording their present day, is being used for inspecting their concern or response to the issue in regard to huge amount of data that are generated as many as several hundred millions a day and users’ voluntary posting of opinions. In this study we conducted a spatial analysis by extracting twitter data containing evaluation on the residential environment among all twitter data recording users’ present condition. In addition, we also divided the key terms which represent evaluation on the residential environment into ‘anxiety’ and ‘dissatisfaction,’ marked the twitter data which include the key terms on the map and then compared the relative distribution with the result of Seoul survey. Even though there are some limitations such as gender or age bias in the case of twitter data, we can confirm that twitter data can be utilized to complement the urban policy indicators in that we can obtain two kinds of information such as the voluntary opinions which can not be attained in the urban policy indicators and the regional micro information which include spatial information.

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