Proceedings of the 2021 on Computers and People Research Conference最新文献_第2页

Tweeting the Alarm: Exploring the Efficacy of Twitter as a Serial Transmitter during the COVID-19 Pandemic 推特警报:在COVID-19大流行期间探索推特作为串行发射器的功效

Proceedings of the 2021 on Computers and People Research Conference Pub Date : 2021-06-29 DOI: 10.1145/3458026.3462159

Jackie London

{"title":"Tweeting the Alarm: Exploring the Efficacy of Twitter as a Serial Transmitter during the COVID-19 Pandemic","authors":"Jackie London","doi":"10.1145/3458026.3462159","DOIUrl":"https://doi.org/10.1145/3458026.3462159","url":null,"abstract":"In this research I seek to understand the efficacy of Twitter as a platform for serial transmission of a crisis communications. As members of the public adopt social media, these platforms are seen as an increasingly strategic channel through which crisis communications can be transmitted. However, there is insufficient understanding of the extent to which these platforms and their users effectively amplify and spread crisis-relevant information during a crisis. I explore these issues in the context of US state health departments and their efforts to inform the public of developments during the COVID-19 pandemic. To do this, I analyze the profiles of the official Twitter account for all 50 state health departments and seek to classify them according to their social presence on social media. Then, I analyze the COVID-19 tweets these health departments sent during the pandemic to better understand how their social media presence and the nature of their messages (tweets, words, URLs, mentions per 7 day) affect the total number of twitter users exposed to each message. My results suggest that systematic differences do exist in the social media presence for state health departments. These differences, as well as the characteristics of the tweets they sent during the pandemic help explain the total number of people exposed to their messages such that short, frequent messages with URLs from departments with high social presence reaching the largest number of users per week. These findings have implications for those responsible for communicating with the public during a crisis and for researchers seeking a better understanding of the flow of crisis communications on social media.","PeriodicalId":402779,"journal":{"name":"Proceedings of the 2021 on Computers and People Research Conference","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130496716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Why do People (not) Want to Work from Home? An Individual-focused Literature Review on Telework 为什么人们(不)想在家工作?以个人为中心的远程工作文献综述

Proceedings of the 2021 on Computers and People Research Conference Pub Date : 2021-06-29 DOI: 10.1145/3458026.3462155

Sven Laumer, C. Maier

引用次数: 8

Capturing the Complexity of Cognitive Computing Systems: Co-Adaptation Theory for Individuals 捕捉认知计算系统的复杂性:个体的共同适应理论

Proceedings of the 2021 on Computers and People Research Conference Pub Date : 2021-06-29 DOI: 10.1145/3458026.3462148

Rasha Alahmad, L. Robert

引用次数: 3

Incentivising the Adoption of COVID-19 Contact-Tracing Apps: A Randomised Controlled Online Experiment on the German Corona-Warn-App 鼓励采用COVID-19接触者追踪应用程序:德国冠状病毒预警应用程序的随机对照在线实验

Proceedings of the 2021 on Computers and People Research Conference Pub Date : 2021-06-29 DOI: 10.1145/3458026.3462158

Victoria Fast, Daniel Schnurr

{"title":"Incentivising the Adoption of COVID-19 Contact-Tracing Apps: A Randomised Controlled Online Experiment on the German Corona-Warn-App","authors":"Victoria Fast, Daniel Schnurr","doi":"10.1145/3458026.3462158","DOIUrl":"https://doi.org/10.1145/3458026.3462158","url":null,"abstract":"Contact-tracing apps constitute a key pillar of many nations' public health strategy to contain the COVID-19 pandemic. However, the effectiveness of digital contact-tracing depends crucially on widespread app installation and usage among citizens. Despite the large social benefits, evidence on the effectiveness of incentives to stimulate adoption of contact-tracing apps is scarce. Whereas monetary compensations for app installation or usage provide users with a direct economic benefit, research in related health domains has found that extrinsic incentives may crowd out intrinsic motivation and pro-social behaviour. Thus, we conduct a randomised controlled online experiment to evaluate the effectiveness of different incentive mechanisms in promoting the installation and usage of the German Corona-Warn-App (CWA). We find that monetary incentives are effective in significantly increasing verified app installations and app usage 14 days after installation, up to three times the usage without compensation. Deferred monetary compensation for verified usage yields lower installation rates than immediate monetary compensation for installation, but sustains the highest retention rate among adopters. Non-monetary compensation in the form of optional charity donations is found to be ineffective in promoting installations or usage beyond outcomes of monetary incentives, suggesting that there is no substantial crowding-out of intrinsic motives. This suggests that monetary incentives can serve as an important policy instrument to encourage the adoption of contact-tracing apps and contain the spread of COVID-19.","PeriodicalId":402779,"journal":{"name":"Proceedings of the 2021 on Computers and People Research Conference","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127455039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Emancipatory Data Science: A Liberatory Framework for Mitigating Data Harms and Fostering Social Transformation 解放数据科学:减轻数据危害和促进社会转型的解放框架

Proceedings of the 2021 on Computers and People Research Conference Pub Date : 2021-06-29 DOI: 10.1145/3458026.3462161

T. Monroe-White

引用次数: 8