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This paper presents an analysis on information disorder in social media platforms. The study employed methods such as Natural Language Processing, Topic Modeling, and Knowledge Graph building to gain new insights into the phenomenon of fake news and its impact on critical thinking and knowledge management. The analysis focused on four research questions: 1) the distribution of misinformation, disinformation, and malinformation across different platforms; 2) recurring themes in fake news and their visibility; 3) the role of artificial intelligence as an authoritative and/or spreader agent; and 4) strategies for combating information disorder. The role of AI was highlighted, both as a tool for fact-checking and building truthiness identification bots, and as a potential amplifier of false narratives. Strategies proposed for combating information disorder include improving digital literacy skills and promoting critical thinking among social media users.

本论文针对社交媒体平台中的信息失序现象开展分析研究。本研究采用自然语言处理（Natural Language Processing）、主题建模（Topic Modeling）与知识图谱构建（Knowledge Graph building）等方法，围绕虚假新闻现象及其对批判性思维与知识管理的影响展开深入探析，以期获得全新研究洞察。本次分析聚焦四大研究问题：1）错误信息（misinformation）、虚假信息（disinformation）与恶意信息（malinformation）在不同平台的分布特征；2）虚假新闻的高频主题及其曝光度；3）作为权威信息源或传播智能体的人工智能所扮演的角色；4）应对信息失序的相关策略。研究着重凸显了人工智能的双重属性：一方面可作为事实核查与真实性识别机器人开发的工具，另一方面也可能成为虚假叙事的潜在放大器。本研究提出的信息失序治理策略包括提升社交媒体用户的数字素养与批判性思维能力。