{"title":"活动断点对移动众包任务性能的影响","authors":"Chia-En Chiang, Yung-Ju Chang, Felicia Feng","doi":"10.1145/3410530.3414409","DOIUrl":null,"url":null,"abstract":"Mobile phones have become a new means of accessing and executing crowdsourcing tasks in a variety of situations. Yet, while it is commonly assumed that people are likely to perform these tasks during activity breakpoints, it remains unclear whether different types of such breakpoints affect the likelihood that crowdsourcing tasks will be performed. To explore this question, we classified breakpoints into five types, according to phone users' preceding, current, and upcoming activities, and conducted a six-week experience sampling method study of 30 users' breakpoint-type-specific crowdsourcing-task performance behavior. We found that these participants tended to engage in crowdsourcing tasks when they were at breakpoints between two different activities, rather than within an activity, and also when breakpoints were long. Additionally, the higher the complexity of their previous activity, the lower the crowdsourcing-task execution rate. However, high complexity of the post-crowdsourcing task activity had no obvious impact on execution rate.","PeriodicalId":7183,"journal":{"name":"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers","volume":"45 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effects of activity breakpoints on mobile crowdsourcing task performance\",\"authors\":\"Chia-En Chiang, Yung-Ju Chang, Felicia Feng\",\"doi\":\"10.1145/3410530.3414409\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobile phones have become a new means of accessing and executing crowdsourcing tasks in a variety of situations. Yet, while it is commonly assumed that people are likely to perform these tasks during activity breakpoints, it remains unclear whether different types of such breakpoints affect the likelihood that crowdsourcing tasks will be performed. To explore this question, we classified breakpoints into five types, according to phone users' preceding, current, and upcoming activities, and conducted a six-week experience sampling method study of 30 users' breakpoint-type-specific crowdsourcing-task performance behavior. We found that these participants tended to engage in crowdsourcing tasks when they were at breakpoints between two different activities, rather than within an activity, and also when breakpoints were long. Additionally, the higher the complexity of their previous activity, the lower the crowdsourcing-task execution rate. However, high complexity of the post-crowdsourcing task activity had no obvious impact on execution rate.\",\"PeriodicalId\":7183,\"journal\":{\"name\":\"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers\",\"volume\":\"45 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3410530.3414409\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3410530.3414409","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Effects of activity breakpoints on mobile crowdsourcing task performance
Mobile phones have become a new means of accessing and executing crowdsourcing tasks in a variety of situations. Yet, while it is commonly assumed that people are likely to perform these tasks during activity breakpoints, it remains unclear whether different types of such breakpoints affect the likelihood that crowdsourcing tasks will be performed. To explore this question, we classified breakpoints into five types, according to phone users' preceding, current, and upcoming activities, and conducted a six-week experience sampling method study of 30 users' breakpoint-type-specific crowdsourcing-task performance behavior. We found that these participants tended to engage in crowdsourcing tasks when they were at breakpoints between two different activities, rather than within an activity, and also when breakpoints were long. Additionally, the higher the complexity of their previous activity, the lower the crowdsourcing-task execution rate. However, high complexity of the post-crowdsourcing task activity had no obvious impact on execution rate.