How Activists Are Both Born and Made: An Analysis of Users on Change.org
How Activists Are Both Born and Made: An Analysis of Users on Change.org
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活动家是如何诞生和形成的：Change.org 用户分析
DOI：
10.1145/2702123.2702559
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Gary Hsieh
中科院分区：
文献类型：
--
作者：
Shih;Minhyang Suh;Benjamin Mako Hill;Gary Hsieh
电子请愿已成为网络行动主义最重要且最受欢迎的形式之一。尽管电子请愿的成功是由用户行为驱动的，但人机交互（HCI）和社会计算研究人员对用户的研究相对较少。借鉴类似社会计算系统中的理论和实证研究，我们确定了关于电子请愿平台上用户轨迹的两种可能相互竞争的理论：（1）社会计算系统中的“强力”用户是天生的，而非后天造就的；（2）用户逐渐成长为“强力”用户。在对Change.org（最大的在线电子请愿平台之一）的数据进行的定量分析中，我们对这两种理论都进行了检验并找到了支持依据。后续的定性分析表明，不仅用户从自身经验中学习，系统也从用户那里“学习”以提供更好的建议。从这个意义上说，我们发现尽管强力用户是“天生的”，但他们也是通过个人成长过程以及系统更好的支持而“造就的”。
E-petitioning has become one of the most important and popular forms of online activism. Although e-petition success is driven by user behavior, users have received relatively little study by HCI and social computing researchers. Drawing from theoretical and empirical work in analogous social computing systems, we identify two potentially competing theories about the trajectories of users in e-petition platforms: (1) "power" users in social computing systems are born, not made; and (2) users mature into "power" users. In a quantitative analysis of data from Change.org, one of the largest online e-petition platforms, we test and find support for both theories. A follow-up qualitative analysis shows that not only do users learn from their experience, systems also "learn" from users to make better recommendations. In this sense, we find that although power users are "born," they are also "made" through both processes of personal growth and improved support from the system.