What You Say in the Conversation Affects the Flow: Building a Model for Conversational Flow Using NLP Methods

“没有人是一座孤岛”--约翰·多恩(1624)人类天生就是社会性的存在，我们彼此不断地互动。会话作为一种最普遍的社会行为，在我们的生活中扮演着至关重要的角色。它们使我们能够联系、交流、建立关系并实现我们的目标。在组织中，对话是有效协作和决策的基础。成功的对话建立了信任，在团队成员之间建立了积极的关系，改善了团队活力，并导致了更好的问题解决和创新，最终推动了朝着集体目标的更好表现。然而，并不是所有的对话都很容易导航。当个人互动和共同工作时，各种挑战就会出现，这可能会对工作场所的关系和绩效产生负面影响。例如，在社交活动中发起与陌生人的对话可能会令人望而生畏。在团队中，冲突可能是由于个性、沟通方式或目标的不同而发生的，个人可能会犯错误，影响团队的表现或关系。由于很难捕捉和分析自然对话，以前对对话的研究一直很有限。在我的研究中，我的目标是结合尖端方法，如自然语言处理(NLP)、机器学习和实验，揭示人类对话的潜在机制，并开发实用的干预措施，帮助个人在日常生活和组织环境中导航重要对话。我的第一篇论文《你在对话中说的话影响流动：使用自然语言处理方法建立对话流模型》已被英国皇家学会科学会议、国际关系研究协会年会和2022年人工智能走向未来会议接受为学术报告。在这项研究中，我建立在最近关于对话流的研究基础上，并使用先进的计算方法来研究对话的内容如何影响其流。在我的第二篇论文《理解对话中的自我关注和他人关注》中，我研究了交流的基本维度：自我关注与他人关注。在交谈中，我们有时会更多地关注自己(例如，将话题转向自己，吹嘘)或我们的对话伙伴(例如，提出问题，做出有效的回应)。这些关注可以反映在我们的言辞中，并导致重大的个人和人际后果。先前的研究已经将会话自恋与社交吸引力降低联系在一起(Vangelisti等人，1990)，并发现第一人称单数代词的使用与说话者的消极情绪有关(Berry-Brunt等人，2021)。在这些工作的基础上，利用先进的计算方法，我的目标是识别不同的语言特征，并全面了解对话中的自我关注和他人关注倾向。作为该项目的一部分，我将访问哈佛商学院，与我的合作者和这一研究领域的专家合作，从行为实验室的真实对话中收集数据，并进一步发展这项研究。这种协作对于数据收集、分析和论文开发至关重要。因此，我将申请OSFW，因为这次访问对于我的研究项目的推进和完成是必不可少的。总而言之，我的研究利用尖端方法来理解人类对话，通过揭示困难社交环境中的决策过程，并开发干预措施，以改善日常生活和组织环境中的互动和关系。

"No Man Is an Island" - John Donne (1624)Humans are inherently social beings; we interact with each other constantly. Conversations, one of the most prevalent social behaviors, play crucial roles in our lives. They allow us to connect, communicate, build relationships, and achieve our goals. In organizations, conversations are fundamental for effective collaboration and decision-making. Successful conversations build trust, foster positive relationships among team members, improve team dynamics, and lead to better problem-solving and innovation, ultimately driving better performance towards collective goals. However, not all conversations are easy to navigate. Various challenges arise when individuals interact and work together, potentially impacting workplace relationships and performance negatively. For instance, initiating conversations with strangers at networking events can be daunting. In teams, conflicts may occur due to differences in personality, communication styles, or goals, and individuals may make mistakes that affect their team's performance or relationships. Previous research on conversations has been limited due to the difficulty of capturing and analyzing natural conversations.In my research, I aim to combine cutting-edge methods such as natural language processing (NLP), machine learning, and experiments to uncover the underlying mechanisms of human conversations and develop practical interventions to help individuals navigate important conversations in everyday life and organizational settings.My first paper "What You Say in the Conversation Affects the Flow: Modelling Conversational Flow Using NLP Methods" has been accepted for academic presentations at the Royal Society scientific meeting, the International Association for Relationship Research annual conference, and the Towards the Future of AI conference in 2022. In this study, I build on recent research on conversational flow and use advanced computational methods to investigate how the content of a conversation influences its flow. I analyze real-world networking conversation data and develop practical interventions to improve conversational flow in networking.In my Second Paper "Understanding Self-Focus and Other-Focus in Conversations", I investigate the fundamental dimension of communication: self-focus versus other-focus. In conversations, we sometimes focus more on ourselves (e.g., redirecting topics to ourselves, bragging) or on our conversation partner (e.g., asking questions, making effective responses). These focuses can be reflected in our words and lead to substantial intrapersonal and interpersonal consequences. Previous research has linked conversational narcissism to lower social attraction (Vangelisti et al., 1990) and found that first-person singular pronoun use relates to speakers' negative emotionality (Berry-Blunt et al., 2021). Building on these works and leveraging advanced computational methods, I aim to identify diverse linguistic features and create a comprehensive understanding of self-focus and other-focus tendencies in conversations.As part of this project, I will visit Harvard Business School to collaborate with my collaborators and experts in this research field, collect data from real conversations in the behavioral lab, and further develop the research. This collaboration is crucial for data collection, analysis, and paper development. Therefore, I will apply for OSFW, as the visit is essential for the advancement and completion of my research projects.In summary, my research leverages cutting edge methods to understand human conversations by unpacking decision-making processes in difficult social situations and develop interventions to improve interactions and relationships in everyday life and organizational contexts.