Media narratives and the social perception of violence: a computational approach to trauma dynamics.

The model proposed in this article faces the necessity to define a computational framework de-signed to analyze how media narratives shape the perception and experience of violence. The starting point of the analysis is a corpus derived from The Guardian, which serves as a founda-tion for broader extensions to include more diverse media sources. The aim is to investigate how perpetrators of violence may feel emboldened by societal indifference or institutional inertia, while victims may experience a deepening sense of isolation and social alienation. The process begins with the preprocessing of textual data to construct a clean and structured corpus, enabling the application of advanced computational methods. Through document embedding and dimen-sionality reduction techniques such as t-SNE, the model identifies latent patterns and relation-ships within the data, making them visually accessible. This is complemented by keyword ex-traction and ontology mapping, which work together to highlight critical terms and organize them into conceptual frameworks. These steps allow for a deeper understanding of how narra-tives around violence are constructed and disseminated. The integration of topic modeling and sentiment analysis further enriches this understanding by uncovering dominant themes and emo-tional undertones, shedding light on how violence is framed in public discourse. These insights are translated into network representations, revealing the intricate interconnections between enti-ties, events, and sentiments. The resulting visualizations and statistical outputs provide an inter-active lens through which researchers can explore the dynamics of media reception and its psy-chological and social consequences. By linking computational insights to the human experience of trauma, this model facilitates the identification of patterns that illuminate the ways in which media narratives influence both individual and collective responses to violence. The iterative refinement of this methodology seeks to bridge computational analysis with the socio-emotional dimensions of trauma, ultimately offering a powerful tool to interrogate the societal structures that perpetuate harm or, conversely, foster healing and resilience.

本文提出的模型面临定义一种计算框架的必要性，该框架旨在分析媒体叙事如何塑造对暴力的认知与体验。分析之起点为一语料库，源于《卫报》，该语料库作为扩展至更广泛媒体来源的基石。研究旨在探讨暴力实施者可能因社会冷漠或制度惰性而感到壮胆，而受害者则可能体验到愈发深刻的孤立与社会疏离感。分析过程始于文本数据的预处理，构建一个清洁且结构化的语料库，以促进高级计算方法的应用。通过文档嵌入与降维技术，如t-SNE，模型识别数据中的潜在模式和关系，使其可视。此过程得以由关键词提取与本体映射补充，二者协同作用，凸显关键术语并将之组织入概念框架之中。这些步骤有助于深入理解围绕暴力叙事的构建与传播方式。主题建模与情感分析之整合，进一步丰富了这一理解，揭示了主导主题与情感基调，阐明了暴力在公共话语中的框架。这些洞见被转化为网络表示，揭示了实体、事件与情感之间错综复杂的相互联系。由此产生的可视化与统计输出，为研究者提供了一种交互式的视角，借此可以探究媒体接收的动态及其心理与社会后果。通过将计算洞察与创伤的人类体验相联系，此模型促进了揭示媒体叙事如何影响个体与集体对暴力反应的模式之识别。此方法论的迭代优化旨在将计算分析与创伤的社会情感维度相衔接，最终提供一种强大的工具，用以质询那些持续造成伤害或相反，促进治愈与韧性的社会结构。