Personality Reputation Formation and Network Structure on Computer Technologies

计算机技术上的人格声誉形成与网络结构

• 批准号: 1551817
• 负责人: Sanjay Srivastava
• 金额: $ 48.9万
• 依托单位: University of Oregon Eugene
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1551817&HistoricalAwards=false
• 关键词: Personality; Reputation; Formation; Network; Structure

The last decade has seen explosive growth of online social networks, which are now a pervasive part of everyday life for many people. More and more, people encounter one another for the first time through social media and make important social decisions based on those encounters. Individuals make decisions about who to hire and who to trust based on the impressions others convey on-line. People may decide with whom they will exchange information, and can even decide with whom to pursue close personal relationships based solely on online encounters. Given the multitude of outcomes, people's online social behavior likely reflects their different goals about how they wish to be seen by others, in addition to their personality. Despite the importance of understanding how these issues operate in communication technologies, most research on self-presentational goals, personality traits, and impressions is based on traditional laboratory and survey methodologies. The goal of this project is to study how users' personalities and self-presentation goals are reflected in their social media presence, how people form accurate or biased impressions of one another online, and how people make consequential social decisions based on those impressions. The project will also produce important tools for other scientists. By combining the expertise of a personality psychologist with that of a computer scientist, the project will create new methods and techniques for doing large-scale, automated studies in social psychological science and personality psychology. The outcomes of this research will also inform policy discussions on online privacy and on the use of social media in hiring, in spreading news and information online, and other important social and economic transactions. In their project, the investigators propose to merge "big data" methods from computer science with rigorous laboratory methods from psychology to study personality and reputation on Twitter, a popular online social network with a large and diverse user base in the United States. Five studies focus on a series of related questions about how people convey who they are through Twitter, and how others form impressions by observing such behavior. (1) Data-driven analyses will be used to identify patterns in Twitter users' publicly available information (including profile information, network size and structure, and tweet content) to determine what important stable attributes distinguish users. (2) A sample of Twitter users will complete validated psychometric assessments of personality and self-presentation goals to see how these are reflected in the users' public Twitter data. (3) Research will examine how others form personality impressions based on such Twitter profiles, and the ways those impressions are accurate or biased. (4) Studies will examine how others make important social decisions based on their accurate or inaccurate impressions of Twitter profiles. (5) Finally, research will examine how personality and impressions affect how people decide to affiliate and form online communities. This research will produce new scientific insights about how people express themselves and interact online. It will also generate new tools for assessing personality and reputation in online settings, enabling future "big data" studies in psychology.

过去十年，在线社交网络呈爆炸式增长，现已成为许多人日常生活的普遍组成部分。越来越多的人通过社交媒体第一次相遇，并根据这些相遇做出重要的社会决定。人们根据其他人在网上传达的印象来决定雇用谁和信任谁。人们可以决定与谁交换信息，甚至可以仅根据在线相遇来决定与谁建立密切的个人关系。考虑到多种结果，人们的在线社交行为除了他们的个性之外，还可能反映了他们希望别人如何看待他们的不同目标。尽管了解这些问题在通信技术中如何运作很重要，但大多数关于自我呈现目标、人格特质和印象的研究都是基于传统的实验室和调查方法。该项目的目标是研究用户的个性和自我展示目标如何反映在他们的社交媒体存在中，人们如何在网上形成对彼此的准确或有偏见的印象，以及人们如何根据这些印象做出相应的社会决策。该项目还将为其他科学家提供重要的工具。通过将人格心理学家的专业知识与计算机科学家的专业知识相结合，该项目将创造新的方法和技术，用于社会心理科学和人格心理学的大规模自动化研究。这项研究的结果还将为有关在线隐私、社交媒体在招聘、在线传播新闻和信息以及其他重要社会和经济交易中的使用的政策讨论提供信息。在他们的项目中，研究人员建议将计算机科学的“大数据”方法与心理学的严格实验室方法相结合，以研究 Twitter 上的个性和声誉。Twitter 是一个流行的在线社交网络，在美国拥有庞大且多样化的用户群。五项研究重点关注一系列相关问题，涉及人们如何通过 Twitter 表达自己的身份，以及其他人如何通过观察此类行为形成印象。 (1) 数据驱动分析将用于识别 Twitter 用户公开信息（包括个人资料信息、网络规模和结构以及推文内容）的模式，以确定哪些重要的稳定属性可以区分用户。 (2) Twitter 用户样本将完成经过验证的人格和自我呈现目标心理测量评估，以了解这些如何反映在用户的公开 Twitter 数据中。 (3) 研究将考察其他人如何根据此类 Twitter 个人资料形成个性印象，以及这些印象是准确的还是有偏见的。 (4) 研究将考察其他人如何根据他们对 Twitter 个人资料的准确或不准确的印象做出重要的社会决策。 (5) 最后，研究将考察个性和印象如何影响人们决定加入和形成在线社区的方式。这项研究将对人们如何表达自己和在线互动产生新的科学见解。它还将生成用于评估在线环境中的个性和声誉的新工具，从而使未来的心理学“大数据”研究成为可能。