인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
개인구독
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지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 저자정보
피인용 0
초록·키워드
Background : The editorial history of Wikipedia articles, especially those on controversial topics, shows the evolution of the topic and cues on whether they were written impartially. This study suggested a compact information-rich visual representation for a better understanding of the complex public discourse in a more intuitive and effective way.
Methods : We developed Flow Circle and demonstrated its effectiveness by using a case of “Gun Politics in the United States” from Wikipedia. We also conducted a user study to compare the usability between Flow Circle and History Flow.
Results : The structure and function of Flow Circle are explained through History Flow, CircosView, and MDS plot. This system provides various interaction methods for users to explore details in multiple aspects and levels. According to the user study results, the participants preferred Flow Circle over History Flow in terms of system functionality and intuitiveness.
Conclusions : In the current study, we developed Flow Circle and suggested its effectiveness in analyzing complex text-based public discourse. Unlike previous approaches, Flow Circle showed integrated multiple data representation in one consistent design, and the user study results also supported its strengths.
Methods : We developed Flow Circle and demonstrated its effectiveness by using a case of “Gun Politics in the United States” from Wikipedia. We also conducted a user study to compare the usability between Flow Circle and History Flow.
Results : The structure and function of Flow Circle are explained through History Flow, CircosView, and MDS plot. This system provides various interaction methods for users to explore details in multiple aspects and levels. According to the user study results, the participants preferred Flow Circle over History Flow in terms of system functionality and intuitiveness.
Conclusions : In the current study, we developed Flow Circle and suggested its effectiveness in analyzing complex text-based public discourse. Unlike previous approaches, Flow Circle showed integrated multiple data representation in one consistent design, and the user study results also supported its strengths.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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