Situations in 140 Characters: Assessing Real-World Situations on Twitter

Over 20 million Tweets were used to study the psychological characteristics of real-world situations over the course of two weeks. Models for automatically and accurately scoring individual Tweets on the DIAMONDS dimensions of situations were developed. Stable daily and weekly fluctuations in the situations that people experience were identified. Predicted temporal trends were found, providing validation for this new method of situation assessment. On weekdays, Duty peaks in the midmorning and declines steadily thereafter while Sociality peeks in the evening. Negativity is highest during the workweek and lowest on the weekends. pOsitivity shows the opposite pattern. Additionally, gender and locational differences in the situations shared on Twitter are explored. Females share both more emotionally charged (pOsitive and Negative) situations, while no differences were found in the amount of Duty experienced by males and females. Differences in the situations shared from Rural and Urban areas were not found. Future applications of assessing situations using social media are discussed.本研究依托超2000万条推文（Tweet），针对为期两周内真实场景的心理特征展开分析。研究构建了可自动、精准对单条推文进行情境DIAMONDS维度评分的模型，识别出人们所经历的情境存在稳定的日度与周度波动特征，并验证了可预测的时序趋势，为这一新型情境评估方法提供了实证支撑。在工作日，“职责感（Duty）”维度于上午中段达到峰值，随后持续回落；“社交性（Sociality）”维度则在晚间达到峰值。“消极性（Negativity）”维度在工作日水平最高，周末降至最低；“积极性（Positivity）”维度则呈现完全相反的变化趋势。此外，本研究还探讨了推特（Twitter）平台分享的情境所存在的性别与地域差异：女性用户分享的带有强烈情绪色彩（积极与消极）的情境内容更多，而男女用户所经历的职责感维度并无显著差异；农村与城市地域的用户所分享的情境则未表现出显著差异。文末对基于社交媒体的情境评估方法的未来应用方向进行了探讨。