{"title":"Opting out in computer-supported sequential collaboration","authors":"Maren Mayer , Daniel W. Heck , Joachim Kimmerle","doi":"10.1016/j.chb.2024.108527","DOIUrl":null,"url":null,"abstract":"<div><div>Many online collaborative projects such as Wikipedia and OpenStreetMap organize collaboration among their contributors sequentially. When engaging in sequential collaboration, one contributor creates an initial entry which is then consecutively adjusted or maintained by the following contributors. Thereby, only the latest version of this entry is presented to subsequent contributors. Sequential collaboration was recently examined as a method for aggregating numerical judgments compared to averaging independently provided judgments (i.e., wisdom of crowds). Sequential collaboration was shown to yield increasingly accurate judgments that result in estimates that are at least as accurate as those obtained from aggregating independent judgments. However, sequential collaboration differs from simply aggregating independent judgments in the sequential nature of the process of providing judgments and in the possibility of contributors to opt out of providing a judgment by maintaining it. How these different features contribute to the accuracy of provided judgments is still unknown. In two experiments, we found that the most accurate judgments were provided by participants who engaged in standard sequential collaboration (with an opt-out option), whereas participants who performed sequential collaboration without opt-out gave less accurate judgments; and independent judgments were least accurate. Thus, both the sequential-collaboration process per se as well as the possibility to opt out and not provide a judgment contribute to the accuracy of contributions. These two features come together in a typical sequential-collaboration paradigm. Allowing contributors to use sequential collaboration in collaborative online projects or at least implement some features of sequential collaboration can be beneficial for the resulting entries and information.</div></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":"165 ","pages":"Article 108527"},"PeriodicalIF":9.0000,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in Human Behavior","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0747563224003959","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
Many online collaborative projects such as Wikipedia and OpenStreetMap organize collaboration among their contributors sequentially. When engaging in sequential collaboration, one contributor creates an initial entry which is then consecutively adjusted or maintained by the following contributors. Thereby, only the latest version of this entry is presented to subsequent contributors. Sequential collaboration was recently examined as a method for aggregating numerical judgments compared to averaging independently provided judgments (i.e., wisdom of crowds). Sequential collaboration was shown to yield increasingly accurate judgments that result in estimates that are at least as accurate as those obtained from aggregating independent judgments. However, sequential collaboration differs from simply aggregating independent judgments in the sequential nature of the process of providing judgments and in the possibility of contributors to opt out of providing a judgment by maintaining it. How these different features contribute to the accuracy of provided judgments is still unknown. In two experiments, we found that the most accurate judgments were provided by participants who engaged in standard sequential collaboration (with an opt-out option), whereas participants who performed sequential collaboration without opt-out gave less accurate judgments; and independent judgments were least accurate. Thus, both the sequential-collaboration process per se as well as the possibility to opt out and not provide a judgment contribute to the accuracy of contributions. These two features come together in a typical sequential-collaboration paradigm. Allowing contributors to use sequential collaboration in collaborative online projects or at least implement some features of sequential collaboration can be beneficial for the resulting entries and information.
期刊介绍:
Computers in Human Behavior is a scholarly journal that explores the psychological aspects of computer use. It covers original theoretical works, research reports, literature reviews, and software and book reviews. The journal examines both the use of computers in psychology, psychiatry, and related fields, and the psychological impact of computer use on individuals, groups, and society. Articles discuss topics such as professional practice, training, research, human development, learning, cognition, personality, and social interactions. It focuses on human interactions with computers, considering the computer as a medium through which human behaviors are shaped and expressed. Professionals interested in the psychological aspects of computer use will find this journal valuable, even with limited knowledge of computers.