Finance_Behavior_Dataset.csv

This dataset captures demographic, behavioral, and psychological traits related to decision-making, impulsivity, and financial behavior. Each row represents an individual, detailing their <b>age</b> and <b>gender</b> alongside behavioral measures. The <b>Mood_Frequency</b> column reflects how often individuals experience moods that may influence their decision-making processes. The <b>Reward_Pursuit</b> column indicates how frequently they seek rewards, potentially on a numerical scale, with higher values representing a stronger tendency to pursue rewards. <b>Impulsivity</b> captures general impulsive behavior, while <b>Decision_Consistency</b> assesses how consistently individuals make decisions over time. The dataset also measures <b>Risk_Tolerance</b>, showing each person's comfort level with taking risks, and <b>Impulsive_Finance</b>, which reflects the frequency of impulsive financial decisions. <b>High_Risk_Decisions</b> might capture either a date or frequency of engaging in high-risk choices, potentially for tracking behavioral patterns over time.In addition, the dataset records the speed and duration of <b>Satisfaction</b> post-decision, indicating how quickly participants feel satisfied and how long the satisfaction lasts. <b>Pursuit_Next_Reward</b> measures the time it takes for individuals to seek the next reward after achieving satisfaction, reflecting reward-seeking behavior. <b>Review_Adjust_Finance</b> shows how often participants review and adjust their financial strategies, while <b>Decision_Preference</b> describes whether their financial decisions are impulsive or carefully considered. Finally, <b>Confidence_Financial_Decisions</b> captures their self-reported confidence in making financial choices, likely on a scale where higher values represent greater confidence. Overall, the dataset provides a comprehensive view of how personality traits, mood, and impulsivity interact with financial behaviors and decision-making processes.

本数据集收录了与决策、冲动性及金融行为相关的人口统计学、行为学与心理学特征数据。每一行对应一名个体，详细记录了其<b>年龄（age）</b>与<b>性别（gender）</b>，并附带多项行为学测量指标。<b>情绪频率（Mood_Frequency）</b>列反映个体经历可能影响决策过程的情绪的频繁程度。<b>奖励寻求倾向（Reward_Pursuit）</b>列表明个体寻求奖励的频率，该指标大概率基于数值量表，数值越高代表奖励寻求倾向越强。<b>冲动性（Impulsivity）</b>用于衡量个体的一般性冲动行为，<b>决策一致性（Decision_Consistency）</b>则评估个体在不同时间点做出决策的一致性程度。数据集还涵盖<b>风险容忍度（Risk_Tolerance）</b>，用以体现个体对承担风险的接受程度，以及<b>冲动性金融行为（Impulsive_Finance）</b>，该指标反映个体做出冲动性金融决策的频率。<b>高风险决策（High_Risk_Decisions）</b>可记录个体参与高风险选择的日期或频率，用于追踪长期行为模式。此外，数据集还记录了决策后<b>满意度（Satisfaction）</b>的产生速度与持续时长，用以体现参与者获得满足感的快慢以及该满足感的维持时间。<b>后续奖励寻求时长（Pursuit_Next_Reward）</b>用于衡量个体在获得满足感后，寻求下一项奖励所需的时间，反映其奖励寻求行为特征。<b>金融策略复盘与调整频率（Review_Adjust_Finance）</b>展示参与者复盘并调整自身金融策略的频繁程度，<b>决策偏好（Decision_Preference）</b>则描述个体的金融决策属于冲动型还是深思熟虑型。最后，<b>金融决策自信心（Confidence_Financial_Decisions）</b>记录了个体自我报告的金融决策自信心水平，该指标大概率基于量表形式，数值越高代表自信心越强。总体而言，本数据集全面展现了人格特质、情绪与冲动性如何与金融行为及决策过程相互作用。