预测公民安全相关推文发布行为：一种霍克斯点过程分析
Predicting Tweet Posting Behavior on Citizen Security: A Hawkes Point Process Analysis
AI总结：
本文提出一种基于霍克斯点过程的模型，利用社交网络数据在短时间框架内预测安全感知，并纳入影响内容发布与转发的外部因素，在保持高可解释性的同时取得了有竞争力的预测性能，为主动式安全规划提供支持。
摘要：
安全感知（Perception of Security, PoS）指人们对某一地点或情境中安全或不安全状况的看法。虽然问卷调查历来是捕捉此类感知的主要手段，但它们在提供实时监测或对未来安全感知的预测性洞察方面仍有待改进。近期证据表明，社交网络内容可以为量化这些感知提供补充性洞察。然而，准确预测这些感知并具备提前预判能力这一挑战仍有待探索。本文引入一种利用社交网络数据在短时间框架内分析安全感知的创新方法。我们的模型纳入了影响安全感知相关内容发布与转发的外部因素。实验结果表明，所提出的模型取得了具有竞争力的预测性能，并在影响安全感知的因素方面保持了较高的可解释性。本研究有助于理解时间模式和外部因素如何影响安全感知的提前预判，为主动式安全规划提供了有价值的见解。
英文摘要：
The Perception of Security (PoS) refers to people's opinions about security or insecurity in a place or situation. While surveys have traditionally been the primary means to capture such perceptions, they need to be improved in their ability to offer real-time monitoring or predictive insights into future security perceptions. Recent evidence suggests that social network content can provide complementary insights into quantifying these perceptions. However, the challenge of accurately predicting these perceptions, with the capacity to anticipate them, still needs to be explored. This article introduces an innovative approach to PoS within short time frames using social network data. Our model incorporates external factors that influence the publication and reposting of content related to security perceptions. Our results demonstrate that this proposed model achieves competitive predictive performance and maintains a high degree of interpretability regarding the factors influencing security perceptions. This research contributes to understanding how temporal patterns and external factors impact the anticipation of security perceptions, providing valuable insights for proactive security planning.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
