This draft paper presents a workflow for creating User Personas with Large Language Models, using the results of a Thematic Analysis of qualitative interviews. The proposed workflow uses improved prompting and a larger pool of Themes, compared to previous work conducted by the author for the same task. This is possible due to the capabilities of a recently released LLM which allows the processing of 16 thousand tokens (GPT3.5-Turbo-16k) and also due to the possibility to offer a refined prompting for the creation of Personas. The paper offers details of performing Phase 2 and 3 of Thematic Analysis, and then discusses the improved workflow for creating Personas. The paper also offers some reflections on the relationship between the proposed process and existing approaches to Personas such as the data-driven and qualitative Personas. Moreover, the paper offers reflections on the capacity of LLMs to capture user behaviours and personality traits, from the underlying dataset of qualitative interviews used for the analysis.
Personality Vector: Modulating Personality of Large Language Models by Model Merging
Department of Human-Artificial Intelligence Interaction, Sungkyunkwan University（人类-人工智能交互系，成均馆大学）；Department of Immersive Media Engineering, Sungkyunkwan University（沉浸式媒体工程系，成均馆大学）
Generative Personality Simulation via Theory-Informed Structured Interview
Department of Psychological Sciences & 2 Department of Computer Science, Rice University（1 心理学系 & 2 计算机科学系，莱斯大学）；Department of Electrical and Computer Engineering, Northeastern University（3 电气与计算机工程系，东北大学）；Department of Computer Science, Johns Hopkins University（4 计算机科学系，约翰霍普金斯大学）；Microsoft Research Asia（微软亚洲研究院）
Exploring the Impact of Personality Traits on Conversational Recommender Systems: A Simulation with Large Language Models
Chinese University of Hong Kong（香港中文大学）；National University of Singapore（新加坡国立大学）；Singapore Management University（新加坡管理大学）；Hong Kong Baptist University（香港浸会大学）；Huazhong University of Science and Technology（华中科技大学）
Scaling Law in LLM Simulated Personality: More Detailed and Realistic Persona Profile Is All You Need
Department of Computer；Information Engineering, Hebei Petroleum University of Technology, Chengde, China (e-mail；School of Computer Science \& Technology, Beijing Institute of Technology, Beijing, China (e-mail
LLMvsSmall Model? Large Language Model Based Text Augmentation Enhanced Personality Detection Model
Beijing Institute of Technology（北京理工大学）；Beijing University of Posts and Telecommunications（北京邮电大学）；Harbin Institute of Technology (Shenzhen)（哈尔滨工业大学（深圳））
EERPD: Leveraging Emotion and Emotion Regulation for Improving Personality Detection
State Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University（北京大学计算机学院多媒体信息处理国家重点实验室）；School of Software, BNRist, Tsinghua University（清华大学软件学院北京信息科学与技术国家研究中心）
InCharacter: Evaluating Personality Fidelity in Role-Playing Agents through Psychological Interviews
Fudan University（复旦大学）；Carnegie Mellon University（卡内基梅隆大学）；The Chinese University of Hong Kong（香港中文大学）；Renmin University of China（中国人民大学）；Beijing University of Technology（北京工业大学）；Boston University（波士顿大学）；RhineAI（莱茵AI公司）；SenseTime（商汤科技）
Neuron-based Personality Trait Induction in Large Language Models
Gaoling School of Artificial Intelligence, Renmin University of China（中国人民大学首都人工智能学院）；Tongyi Lab（通义实验室）；Institute of Statistics and Big Data, Renmin University of China（中国人民大学统计与大数据研究院）
Is ChatGPT a Good Personality Recognizer? A Preliminary Study
Institute of AI Education, East China Normal University（华东师范大学人工智能教育研究院）；School of Computer Science and Technology, East China Normal University（华东师范大学计算机科学与技术学院）；School of Psychology and Cognitive Science, East China Normal University（华东师范大学心理与认知科学学院）；Shanghai Changning Mental Health Center（上海市长宁区精神卫生中心）
Evaluating and Inducing Personality in Pre-trained Language Models
Institute for Artificial Intelligence, Peking University（北京大学人工智能研究院）；Yuanpei College, Peking University（北京大学元培学院）；National Key Laboratory of General Artificial Intelligence, BIGAI（北京通用人工智能研究院通用人工智能全国重点实验室）；Beijing Jiaotong University（北京交通大学）
Evaluating Personality Traits in Large Language Models: Insights from Psychological Questionnaires
School of Physics, Mathematics and Computing（物理、数学与计算学院）；University of Western Australia（西澳大学）；School of Computing（计算机学院）；School of Psychological Sciences（心理科学学院）
Do Personality Traits Interfere? Geometric Limitations of Steering in Large Language Models
Network Analysis and Social Influence Modelling (NASIM) Lab（网络分析与社会影响建模实验室）；School of Physics Maths and Computing（物理数学计算学院）；The University of Western Australia（西澳大学）；School of Computing（计算学院）；Macquarie University（麦觉瑞大学）
We present an intelligent virtual interviewer that engages with a user in a text-based conversation and automatically infers the user's psychological traits, such as personality. We investigate how the personality of a virtual interviewer influences a user's behavior from two perspectives: the user's willingness to confide in, and listen to, a virtual interviewer. We have developed two virtual interviewers with distinct personalities and deployed them in a real-world recruiting event. We present findings from completed interviews with 316 actual job applicants. Notably, users are more willing …
Sensor data collected from smartphones provides the possibility to passively infer a user's personality traits. Such models can be used to enable technology personalization, while contributing to our substantive understanding of how human behavior manifests in daily life. A significant challenge in personality modeling involves improving the accuracy of personality inferences, however, research has yet to assess and consider the cultural impact of users' country of residence on model replicability. We collected mobile sensing data and self-reported Big Five traits from 166 participants (54 wom…
