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）我们不断地相互交流。对话是最普遍的社会行为之一，在我们的生活中扮演着至关重要的角色。它们让我们联系、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。成功的对话建立信任，培养团队成员之间的积极关系，提高团队活力，并导致更好的解决问题和创新，最终推动更好的绩效实现集体目标。然而，并不是所有的对话都很容易引导。当个人在一起互动和工作时，会出现各种各样的挑战，可能会对职场关系和绩效产生负面影响。例如，在社交活动中主动与陌生人交谈可能会让人望而生畏。在团队中，由于性格、沟通方式或目标的差异，可能会发生冲突，个人可能会犯错误，影响团队的表现或关系。由于难以捕捉和分析自然对话，以往对对话的研究受到了限制。在我的研究中，我的目标是结合前沿的方法，如自然语言处理（NLP），机器学习和实验，以揭示人类对话的潜在机制，并开发实际的干预措施，以帮助个人在日常生活和组织环境中导航重要的对话。我的第一篇论文“你在谈话中所说的话会影响流动：使用NLP方法建模会话流”已被英国皇家学会科学会议、国际关系研究协会年会和2022年的人工智能未来会议的学术报告所接受。在这项研究中，我以最近对会话流的研究为基础，使用先进的计算方法来研究会话内容如何影响会话流。我分析了现实世界的网络会话数据，并开发了实际的干预措施，以改善网络中的会话流。在我的第二篇论文“理解对话中的自我关注和他人关注”中，我研究了沟通的基本维度：自我关注与他人关注。在谈话中，我们有时更关注自己（例如，把话题转到自己身上，吹牛）或我们的谈话对象（例如，提出问题，做出有效的回应）。这些焦点可以反映在我们的语言中，并导致实质性的人际关系和人际关系的后果。先前的研究将会话自恋与较低的社会吸引力联系起来（Vangelisti et al., 1990），并发现第一人称单数代词的使用与说话者的负面情绪有关（Berry-Blunt et al., 2021）。在这些作品的基础上，利用先进的计算方法，我的目标是识别不同的语言特征，并对对话中的自我关注和他人关注趋势有一个全面的理解。作为这个项目的一部分，我将访问哈佛商学院，与我在这个研究领域的合作者和专家合作，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，因为访问对我的研究项目的推进和完成至关重要。总而言之，我的研究利用尖端的方法，通过在困难的社会情况下解开决策过程来理解人类的对话，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.