DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Lee, Wonjae | - |
dc.contributor.advisor | 이원재 | - |
dc.contributor.advisor | Cha, Meeyoung | - |
dc.contributor.advisor | 차미영 | - |
dc.contributor.author | Lim, Hongjun | - |
dc.date.accessioned | 2019-08-28T02:46:33Z | - |
dc.date.available | 2019-08-28T02:46:33Z | - |
dc.date.issued | 2018 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=828477&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/266045 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 문화기술대학원, 2018.8,[iv, 25 p. :] | - |
dc.description.abstract | News posts on Facebook display various types of reader feedback, including comments. To understand how important comments are to readers, we conducted a mixed method study. We first surveyed U.S. young adults (N=514) and found that many readers considered comments as a valid source of supplemental information or overview of article and actively participated in responding to comments through one-click feedback. We also identified that reading comments has become a natural, integral part daily news consumption with 90% of participants reporting that they read comments either before or after reading the actual news article. We then computed comments' relevance to news content based on 40,000 Facebook news posts from four media outlets. Content analysis using natural language processing revealed that Top comments which get abundant one-click feedback have distinctive features compared to comments with no feedback in terms of textual property to the news story. We found Top comments to be 1.3 times more coherent to the full news article than other summaries (e.g., news headline, blurb), indicating that they can be a new gateway for understanding the news article instead of headline and blurb. Based on these findings, we present some design suggestions on how to integrate the role of comments more into the news reading experience. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Computational journalism▼anews▼aonline comments▼asocial media▼afacebook | - |
dc.subject | 계산학적 저널리즘▼a뉴스▼a온라인 댓글▼a소셜 미디어▼a페이스북 | - |
dc.title | Understanding comments on social news | - |
dc.title.alternative | 소셜 뉴스 댓글에 대한 이해 : 페이스북상의 뉴스 게시물의 댓글 읽기 행동 분석과 유사도 비교를 중심으로 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :문화기술대학원, | - |
dc.contributor.alternativeauthor | 임홍준 | - |
dc.title.subtitle | analyzing comment-reading behavior and comparing textual similarity on facebook news posts | - |
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