A Framework for Information Disorder: Modeling Mechanisms and Implications Based on a Systematic Literature Review

• URL: http://arxiv.org/abs/2504.12537v1
• Date: Wed, 16 Apr 2025 23:57:21 GMT
• Title: A Framework for Information Disorder: Modeling Mechanisms and Implications Based on a Systematic Literature Review
• Authors: Julie Ricard, Ivette Yañez, Leticia Hora,
• Abstract summary: We propose a five-stage framework capturing information disorder's full life cycle.<n>This approach calls for a shift away from fragmented interventions toward more holistic, system-level policy responses.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This systematic literature review seeks to explain the mechanisms and implications of information disorder for public policy and the democratic process, by proposing a five-stage framework capturing its full life cycle. To our knowledge, no prior reviews in the field of public administration have offered a comprehensive, integrated model of information disorder; most existing studies are situated within communication, information science, or data science, and tend to focus on isolated aspects of the phenomenon. By connecting concepts and stages with enabling factors, agents, tactics and impacts, we reframe information disorder not as a question of "truthiness", individual cognition, digital literacy, or merely of technology, but as a socio-material phenomenon, deeply embedded in and shaped by the material conditions of contemporary digital society. This approach calls for a shift away from fragmented interventions toward more holistic, system-level policy responses.

Related papers

• Intervention strategies for misinformation sharing on social media: A bibliometric analysis [1.8020166013859684]
  Inaccurate shared information causes confusion, can adversely affect mental health, and can lead to mis-informed decision-making. This study explores the typology of intervention strategies for addressing misinformation sharing on social media. It identifies 4 important clusters - cognition-based, automated-based, information-based, and hybrid-based.
  arXiv  Detail & Related papers  (2024-09-26T08:38:15Z)
• A Survey of Stance Detection on Social Media: New Directions and Perspectives [50.27382951812502]
  stance detection has emerged as a crucial subfield within affective computing. Recent years have seen a surge of research interest in developing effective stance detection methods. This paper provides a comprehensive survey of stance detection techniques on social media.
  arXiv  Detail & Related papers  (2024-09-24T03:06:25Z)
• Community Shaping in the Digital Age: A Temporal Fusion Framework for Analyzing Discourse Fragmentation in Online Social Networks [45.58331196717468]
  This research presents a framework for analyzing the dynamics of online communities in social media platforms. By combining text classification and dynamic social network analysis, we uncover mechanisms driving community formation and evolution.
  arXiv  Detail & Related papers  (2024-09-18T03:03:02Z)
• Ontology Embedding: A Survey of Methods, Applications and Resources [54.3453925775069]
  Onologies are widely used for representing domain knowledge and meta data.<n> logical reasoning that can directly support are quite limited in learning, approximation and prediction.<n>One straightforward solution is to integrate statistical analysis and machine learning.
  arXiv  Detail & Related papers  (2024-06-16T14:49:19Z)
• Decoding the Sociotechnical Dimensions of Digital Misinformation: A Comprehensive Literature Review [1.7478203318226313]
  The review consists of 788 studies from SCOPUS, IEEE, and ACM digital libraries, synthesizing the primary research directions and sociotechnical challenges. The mapping identifies issues related to the concept of misinformation, highlights deficiencies in mitigation strategies, discusses challenges in approaching stakeholders, and unveils various sociotechnical aspects relevant to understanding and mitigating the harmful effects of digital misinformation.
  arXiv  Detail & Related papers  (2024-04-02T20:09:27Z)
• Theoretical Unification of the Fractured Aspects of Information [0.0]
  An overview of the concept of information in the conceptualization of intelligence, complexity, and consciousness. An example of a possible application in the development of the unified theory of information free from unnecessary divisions and claims of superiority.
  arXiv  Detail & Related papers  (2024-02-26T10:35:41Z)
• False Information, Bots and Malicious Campaigns: Demystifying Elements of Social Media Manipulations [6.901078062583646]
  False information and persistent manipulation attacks on online social networks (OSNs) have affected the openness of OSNs. This paper synthesizes insights from various disciplines to provide a comprehensive analysis of the manipulation landscape.
  arXiv  Detail & Related papers  (2023-08-24T01:37:33Z)
• Foundational Models Defining a New Era in Vision: A Survey and Outlook [151.49434496615427]
  Vision systems to see and reason about the compositional nature of visual scenes are fundamental to understanding our world. The models learned to bridge the gap between such modalities coupled with large-scale training data facilitate contextual reasoning, generalization, and prompt capabilities at test time. The output of such models can be modified through human-provided prompts without retraining, e.g., segmenting a particular object by providing a bounding box, having interactive dialogues by asking questions about an image or video scene or manipulating the robot's behavior through language instructions.
  arXiv  Detail & Related papers  (2023-07-25T17:59:18Z)
• Aggression and "hate speech" in communication of media users: analysis of control capabilities [50.591267188664666]
  Authors studied the possibilities of mutual influence of users in new media. They found a high level of aggression and hate speech when discussing an urgent social problem - measures for COVID-19 fighting. Results can be useful for developing media content in a modern digital environment.
  arXiv  Detail & Related papers  (2022-08-25T15:53:32Z)
• Causal Fairness Analysis [68.12191782657437]
  We introduce a framework for understanding, modeling, and possibly solving issues of fairness in decision-making settings. The main insight of our approach will be to link the quantification of the disparities present on the observed data with the underlying, and often unobserved, collection of causal mechanisms. Our effort culminates in the Fairness Map, which is the first systematic attempt to organize and explain the relationship between different criteria found in the literature.
  arXiv  Detail & Related papers  (2022-07-23T01:06:34Z)
• Hierarchical Reinforcement Learning for Automatic Disease Diagnosis [52.111516253474285]
  We propose to integrate a hierarchical policy structure of two levels into the dialogue systemfor policy learning. The proposed policy structure is capable to deal with diagnosis problem including large number of diseases and symptoms.
  arXiv  Detail & Related papers  (2020-04-29T15:02:41Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.