CAREER: Fostering Prosocial Behavior and Well-Being in Online Communities

职业：在在线社区中培养亲社会行为和福祉

• 批准号: 2143529
• 负责人: David Jurgens
• 金额: $ 58.14万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2027-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2143529&HistoricalAwards=false
• 关键词: CAREER; Fostering; Prosocial; Behavior; Well

This award is funded in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Social media platforms are a common part of daily life that connect people and aid in sharing information. While society has learned how these platforms can negatively impact individuals, little is known comparatively about how our interactions on the platforms benefit us and how to encourage positive behaviors of people on these platforms. Being able to measure the potential benefits of social media can help understand its cumulative effects on people and help identify both ways individuals can change their own behavior and inform the design of social media platforms themselves. This project aims to develop computational tools to identify and measure a variety of ways in which positive behaviors such as compassion or empathy occur online. This research will study the effects of experiencing positive and negative behaviors in social media on people’s psychological well-being to create a holistic picture of social media’s impact. Furthermore, the project will identify strategies for how to phrase positive reinforcement and develop tools to support individuals in behaving positively, both of which should encourage future positive behavior in social media. The project team will also release educational material, courses, and videos for the public and students at multiple levels, as well as provide practical and informative public-facing tools that educate people about the impact of social media on well-being at a personal level.This project studies prosocial behavior in social media and quantifies the impact of interactions, content, and interventions there on specific dimensions of psychological well-being. To accomplish this goal, the project will develop datasets, models, and technologies to identify and encourage positive behaviors. The computational techniques will combine insights from natural language processing and computational social science to recognize subtle social signals in language, which will enable moving from just understanding the meaning of a text to understanding the text’s effects on the audience. The project will address three core technical challenges: (1) recognizing prosocial behavior in online spaces in ways that are sensitive to the norms of the community; (2) quantifying the impact of social media interactions and content on dimensions of psychological well-being and developing computational methods for analyzing this impact at scale; and (3) creating proactive technologies that promote prosocial behavior via behavioral nudges and tools to help people write more prosocially.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项部分由2021年美国救援计划法案（公法117-2）资助。社交媒体平台是日常生活中常见的一部分，它将人们联系起来，帮助分享信息。虽然社会已经了解了这些平台如何对个人产生负面影响，但相对而言，我们对平台上的互动如何使我们受益以及如何鼓励人们在这些平台上的积极行为知之甚少。能够衡量社交媒体的潜在好处，有助于理解它对人们的累积影响，有助于确定个人改变自己行为的两种方式，并为社交媒体平台的设计提供信息。该项目旨在开发计算工具，以识别和测量在线上出现的积极行为（如同情或同情）的各种方式。本研究将研究在社交媒体中体验积极和消极行为对人们心理健康的影响，以全面了解社交媒体的影响。此外，该项目将确定如何表达积极强化的策略，并开发支持个人积极行为的工具，这两者都应该鼓励未来在社交媒体上的积极行为。项目团队还将为公众和学生发布教育材料、课程和视频，并提供实用和信息丰富的面向公众的工具，教育人们在个人层面上了解社交媒体对福祉的影响。本项目研究社交媒体中的亲社会行为，并量化互动、内容和干预对心理健康特定维度的影响。为了实现这一目标，该项目将开发数据集、模型和技术来识别和鼓励积极的行为。计算技术将结合自然语言处理和计算社会科学的见解来识别语言中微妙的社会信号，这将使人们能够从仅仅理解文本的含义转向理解文本对受众的影响。该项目将解决三个核心技术挑战：(1)以对社区规范敏感的方式识别在线空间中的亲社会行为；(2)量化社交媒体互动和内容对心理健康维度的影响，并开发大规模分析这种影响的计算方法；(3)创造积极主动的技术，通过行为推动和工具来促进亲社会行为，帮助人们写得更亲社会。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Exploring Linguistic Style Matching in Online Communities: The Role of Social Context and Conversation Dynamics

探索在线社区中的语言风格匹配：社会背景和对话动态的作用

• DOI: 10.18653/v1/2023.sicon-1.7
• 发表时间: 2023
• 期刊: Proceedings of the First Workshop on Social Influence in Conversations (SICon 2023
• 作者: Ananthasubramaniam, Aparna;Chen, Hong;Yan, Jason;Alkiek, Kenan;Pei, Jiaxin;Seth, Agrima;Dunagan, Lavinia;Choi, Minje;Litterer, Benjamin;Jurgens, David
• 通讯作者: Jurgens, David

Analyzing the Engagement of Social Relationships during Life Event Shocks in Social Media

分析社交媒体中生活事件冲击期间社会关系的参与度

• DOI: 10.1609/icwsm.v17i1.22134
• 发表时间: 2023
• 期刊: Proceedings of the International AAAI Conference on Web and Social Media
• 作者: Choi, Minje;Jurgens, David;Romero, Daniel M.
• 通讯作者: Romero, Daniel M.

SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis

SemEval-2023 任务 9：多语言推文亲密度分析

• DOI: 10.18653/v1/2023.semeval-1.309
• 发表时间: 2023
• 期刊: Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023
• 作者: Pei, Jiaxin;Silva, Vítor;Bos, Maarten;Liu, Yozen;Neves, Leonardo;Jurgens, David;Barbieri, Francesco
• 通讯作者: Barbieri, Francesco

When Do Annotator Demographics Matter? Measuring the Influence of Annotator Demographics with the POPQUORN Dataset

注释者人口统计数据何时重要？

• DOI: 10.18653/v1/2023.law-1.25
• 发表时间: 2023
• 期刊: Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII
• 作者: Pei, Jiaxin;Jurgens, David
• 通讯作者: Jurgens, David