{"title":"Understanding User's Behavior for Developing Webtoon Rating System Based on Laugh Reaction Sensing through Smartphone","authors":"Sun-gil Yoon, Soyoung Kwon, Kun-Pyo Lee","doi":"10.1145/2702613.2732920","DOIUrl":null,"url":null,"abstract":"In this work-in-progress study, we aim to understand the users' behavior for developing the webtoon(web cartoon) rating system using with users' laugh reactions when they read webtoons by smartphones. First, we conducted an online survey in order to understand general reading environment of a webtoon. Second, we executed a pilot experiment in lab based environment to observe which reactions come from readers and which sensors can use for detecting laugh reactions. Lastly, we exploited an observation experiment to sense participants' laugh reactions and evaluate with manual rating scores of each webtoon episode. For the preliminary finding, we analyzed the laugh reactions from randomly selected 20 sample data out of 1300 episodes, and it exhibits significantly correlated with the manual score.","PeriodicalId":142786,"journal":{"name":"Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2702613.2732920","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this work-in-progress study, we aim to understand the users' behavior for developing the webtoon(web cartoon) rating system using with users' laugh reactions when they read webtoons by smartphones. First, we conducted an online survey in order to understand general reading environment of a webtoon. Second, we executed a pilot experiment in lab based environment to observe which reactions come from readers and which sensors can use for detecting laugh reactions. Lastly, we exploited an observation experiment to sense participants' laugh reactions and evaluate with manual rating scores of each webtoon episode. For the preliminary finding, we analyzed the laugh reactions from randomly selected 20 sample data out of 1300 episodes, and it exhibits significantly correlated with the manual score.
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