Information Ecology Research Articles

Community-driven enhancement of information ecosystems for the discovery and use of paleontological specimen data: Stakeholder engagement workshop

A stakeholder engagement workshop was held in May 2024 as part of the "Community-driven enhancement of information ecosystems for the discovery and use of paleontological specimen data" project, which is funded under the United States National Science Foundation (NSF) Geosciences Open Science Ecosystem (GEO OSE) program. This report describes the activites and outcomes of the workshop.

In the digital trenches: Mapping the structure and evolution of the Islamic State’s information ecosystem (2023–2024)

In the digital trenches: Mapping the structure and evolution of the Islamic State’s information ecosystem (2023–2024)

Study on the Behavioral Motives of Algorithmic Avoidance in Intelligent Recommendation Systems

Through an exploration of the underlying mechanisms driving users' algorithmic avoidance in intelligent recommendation systems, this study aims to facilitate a positive interaction between users and technology, providing theoretical guidance for the efficient operations of enterprises using intelligent recommendation systems. The research integrates the theories of information ecology and psychological resistance, establishing a model of influencing factors on users' algorithmic avoidance in intelligent recommendation systems. Utilizing a structural equation model, the study conducts analysis and validation on data collected from 506 questionnaires. The findings reveal that algorithmic transparency and perceived manipulation significantly impact the users' algorithmic avoidance in intelligent recommendation systems. The sense of being manipulated emerges as a crucial psychological factor leading to algorithmic avoidance, playing a complete mediating role in the influence of information quality, homogeneous recommendation, and algorithmic transparency on algorithmic avoidance.

Information ecosystems in early academic career building: how do researchers in the social sciences and humanities learn the tricks of the trade?

Early career investigators (ECIs) in the Social Sciences and Humanities need to receive adequate information so that they will be empowered to progress in their academic career and deal with the various evaluation processes that constitute an essential part of their professional development. This article relies on an informational-ecosystemic approach originally developed in the context of resilience studies and crisis communication and uses it as a theoretical framework to analyse and understand the “early academic career building information ecosystems” (EACBIEs), into which ECIs professionally develop. The characteristics of these ecosystems are then refined through the analysis of interviews conducted with ECIs from all around Europe in the framework of the European Network for Research Evaluation in Social Sciences and Humanities (ENRESSH), European Cooperation in Science and Technology (COST) Action. The analysis reveals the remarkable heterogeneity of the information ecosystems into which early career researchers have to build their career in Europe, articulating a diversity of formal, non-formal and informal learning environments, and several related information channels, as well as showing a geographical spread that covers institutional, national and international levels. Furthermore, although the diverse information channels at hand and geographical levels at which they operate appear in some cases to be complementary, and even mutually reinforcing, they can also, in other cases, be dysfunctional, fragmented and unfair to some extent.

Healthier information ecosystems: A definition and agenda

AbstractAs digitally enabled information systems play an increasingly central role in culture and economics, their negative consequences have become apparent. This guest editorial addresses the urgent need for information scientists to take a more deliberate stance in designing and guiding the evolution of these systems. We propose a framework for conceptualizing “healthier information ecosystems” by drawing on theories from complex systems and ecological research, grounded in a value‐oriented approach. The article reviews key concepts from systems science, complex systems, and ecology, with a focus on ecosystem and adaptation research. These perspectives offer analytical approaches for decomposing information ecosystems and provide a foundation for understanding “health” in the context of evolving, open systems. Unlike natural ecosystems, information ecosystems must be evaluated according to human values; thus, we articulate a set of values as a starting point for defining health in this context. By introducing insights from beyond the field of information systems, we aim to instigate scholarly dialog, connect prior work in new ways, and reveal new opportunities for research and intervention. This connective and argumentative contribution is intended to guide future research and identify solutions to the proliferating problems in our current information ecosystems.

Journalism in a new informative environment structured by Artificial Cognitive Systems

Journalism has evolved over the centuries, adapting to capture the audience's attention. With the emergence of intelligent systems such as chatbots and software that transform data into news narratives, giving rise to Artificial Media, computational systems with cognitive bias create content in real-time through interactive engagement with the audience. This new information ecosystem blurs the boundaries between human-generated content and that produced by machines. The introduction of Artificial Cognitive Systems establishes a symbiotic partnership between biological and artificial agents, transforming the way information is consumed. This Human Information Interaction replaces the previous master-slave relationship from the Industrial Revolution. The article suggests the hypothesis of the consolidation of Artificial Media, in which the machine can process events, contexts, and actions, initially dealing with immediate situations and increasingly acquiring predictive or prospective capabilities, thus reshaping the production, distribution, and consumption of news.

Integrating Blockchain technology within an Information Ecosystem

ContextBlockchain-based Information Ecosystems (BBIEs) are a type of information ecosystem in which blockchain technology is used to provide a trust mechanism among parties and to manage shared business logic, breaking the traditional scheme of Information Ecosystems dominated by a leading company and leveraging the decentralization of data management, information flow, and business logic. ObjectiveIn this paper, we propose architecture and technical aspects concerning creating a BBIE, underlining the advantages supplied and the logic decomposition among the business and storage components. MethodThe requirements are derived from the current needs of the collaborative business and the data collected by surveying practitioners. To get these needs we followed the Grounded Theory research approach. We validate our architectural schema against a case study on managing a wine supply chain–involving different companies and supervision authorities. ResultsThe proposed solution integrates blockchain-based applications with the existing information system as a module of the ecosystem, leveraging on the low costs, scalability, and high-level security because of the restricted access to the network. ConclusionWe must go a long way in deepening and refining the possibilities offered by technology in supporting innovative multi-organizational business models. BBIEs can contribute substantially to paving the way in such a direction.

Combating misinformation in the age of LLMs: Opportunities and challenges

AbstractMisinformation such as fake news and rumors is a serious threat for information ecosystems and public trust. The emergence of large language models (LLMs) has great potential to reshape the landscape of combating misinformation. Generally, LLMs can be a double‐edged sword in the fight. On the one hand, LLMs bring promising opportunities for combating misinformation due to their profound world knowledge and strong reasoning abilities. Thus, one emerging question is: can we utilize LLMs to combat misinformation? On the other hand, the critical challenge is that LLMs can be easily leveraged to generate deceptive misinformation at scale. Then, another important question is: how to combat LLM‐generated misinformation? In this paper, we first systematically review the history of combating misinformation before the advent of LLMs. Then we illustrate the current efforts and present an outlook for these two fundamental questions, respectively. The goal of this survey paper is to facilitate the progress of utilizing LLMs for fighting misinformation and call for interdisciplinary efforts from different stakeholders for combating LLM‐generated misinformation.

Computational thinking in primary mathematics classroom activities

The integration of computational thinking (CT) into primary education is often facilitated using one or more CT tools, such as block-based programming environments and educational robotics. A major concern is that these CT tools often are used to design mathematics classroom activities that focus on CT at the expense of mathematics. Hence, there is a need to investigate more closely how CT tools can be used in primary mathematics classroom activities in ways that enable a stronger focus on the learning of mathematics. Using information ecology as a theoretical lens, this study aims to understand how and why CT tools are integrated into primary mathematics classrooms, and how teachers value the possible contributions of such tools. We draw on multiple interviews with two primary teachers, recordings of planning sessions where classroom activities that include CT were designed, the classroom implementations themselves, and reflective conversations with the teachers after the CT tools were integrated in their mathematics classrooms. A deductive analytical approach to our data revealed that (1) CT tools, to varying degrees, facilitate the learning of mathematics; (2) some CT tools were valued by teachers as a better ‘fit’ than others; and (3) CT tools are primarily used to support the learning of geometry, excluding other mathematical domains. Based on these findings, we suggest that there is a need for more research on the use of different CT tools and their role in the learning of primary mathematics. Moreover, more research is needed to understand how CT tools can be used in topics other than geometry.

Creating, publishing, and spreading processes of health-related contents in internet news sites: evaluation of the opinions of actors in health communication.

The accuracy and reliability of health information disseminated through news is crucial, as it directly impacts both individual and societal health outcomes. This study aims to analyze the publication process of health content in Türkiye and its implications for public health. By examining the perspectives of various health communication stakeholders, the study seeks to identify existing issues and propose potential solutions. The research uses a mixed-methods approach, including baseline content analysis of 846 news by 133 criteria, quantitative research with 78 participants encompassing bureaucrats, academics, journalists, and health association members, and 15 in-depth interviews for comprehensive insights. The content analysis indicated that 23.2% of the analyzed news articles lacked credible sources, while 63% did not mention the author's name. A striking 96.2% of respondents stated that inaccurate health news poses a risk to public health, emphasizing the urgent need for standardized reporting practices. The majority (90.9%) pinpointed the media as the primary catalysts for infodemic spread, with 93.5% citing gatekeepers as barriers to accurate information. Eroding trust in media, fueled by unethical practices, harms both media credibility and effective public health interventions. The study underscores the necessity for a collaborative approach among public institutions, academia, and media, focusing on responsibility, regulation, and sanctions against the infodemic. The research advocates for a balanced approach that prioritizes health rights and press freedom within a stakeholder-driven framework, highlighting that legislation alone cannot fully enhance the digital information ecosystem.

What are the key factors influencing scientific data sharing? A combined application of grounded theory and fuzzy-DEMATEL approach

Scientific data sharing (SDS) has become essential for scientific progress, technological innovation and socioeconomic development. Identifying the key influencing factors of SDS can effectively promote SDS programmes and give full play to the critical role of scientific data. This study used grounded theory and information ecology theory to construct an SDS influencing factor model that encompassed five dimensions and 28 influencing factors and followed the fuzzy decision-making trial and evaluation laboratory (fuzzy-DEMATEL) approach to measure and analyse the degree of influence of each influencing factor and identify the key factors. The results show that (1) there are interactions and mutual interactions between the various influencing factors of SDS, which can form a complex network system. (2) 16 influencing factors, such as data-sharing policies, data-sharing regulations and data-sharing standards, comprise the key influencing factors in SDS. (3) The optimisation path of SDS is ‘Scientific Researchers’ → ‘Scientific Data’ → ‘Policy Environment’ → ‘Research Organisations → ‘Information Technologies’. In this regard, we proposed the following management suggestions to promote the development of SDS programmes in China: focusing on researchers' subjective willingness to share, enhancing the integrated governance of scientific data, fulfilling the role of policy support and guidance, strengthening the support of research organisations and improving SDS platforms with information technology.

Cyber influence defense: Applying the DISARM framework to a cognitive hacking case from the Romanian digital space

One of the main lessons learned in the context of Russia’s full-scale invasion of Ukraine starting in February 2022 is that for- eign information manipulation and interference (FIMI) operations are closely coupled with cyber threats. Regardless of whether cyberattacks are followed by an information manipulation compo- nent and vice versa, the merger of the two can be an early indica- tor of the potential for a conflict to escalate from the cyber area to the ground. Our article is premised on the idea that today’s highly technologised information ecosystem is a fertile ground for cyberattacks and information manipulation in the context of FIMI; more specifically, it enables cognitive hacking, meaning hacking the human mind and human cognition altogether through techno- logical disruption and cyber pressure. Starting from this premise, the aim of the article is to highlight the technological determi- nants of cognitive hacking and identify silent or emerging threats that bypass technological sensors and seek to disrupt and manip- ulate the information environment. The empirical part is based on observation as a descriptive method, which is used to analyse a case of cognitive hacking carried out via a YouTube malvertis- ing campaign targeting Romanian users. This case study is anal- ysed qualitatively by matching the DISinformation Analysis & Risk Management (DISARM) framework with evidence collected through Open-Source Intelligence (OSINT) tools, following an innovative analysis structured according to the purposes, actions, results and techniques (PART) model. The extensive analysis of the identified case shows that applying the DISARM framework to cyber-enabled operations can be useful for anticipating and responding to FIMI threats, even when such operations do not appear to have a spe- cific, immediately identifiable purpose.

From innovation to participation: connectivity and the conduct of contemporary warfare

Abstract The war in Ukraine is the first conventional war to ever take place in an entirely connected information ecology. The internet has not been switched off. Mundane smart devices are ubiquitous. Soldiers and ordinary civilians are participating in the conflict in ways that have never previously been possible. This stretches participation beyond the information domain and the kinds of connectivity that shaped conflicts in places like Syria, Tigray and Mali. Now the smartphone is routinely being used by soldiers and civilians alike to geolocate enemy columns, control drones to range find for artillery, and produce and broadcast the damage assessment for online audiences to watch. Surveillance technology already makes it possible to track individual smartphone users. In times of peace these forms of surveillance are curtailed. During a conventional war, however, private organizations and governments have reason to circumvent peacetime legal conventions. The result is that mundane connected technology forms part of an extended chain of sensors that feeds data and information to those involved in information warfare and targeting activities. In effect, the smartphone has collapsed the means to fight and represent war into the functionality of one device. This article maps the policy and military implications of these developments in relation to participation, the conduct of war and the law of armed conflict.

National sepsis strategy to improve knowledge, prevention and treatment

National sepsis strategy to improve knowledge, prevention and treatment Discover what you need to know about sepsis from a top group of experts, including their call for a national sepsis strategy to improve its knowledge, prevention, and treatment to save lives. The rapidly evolving health information ecosystem describes how the public, healthcare professionals, scientists and policymakers exchange knowledge that influences decisions. Our research team at Sepsis Canada studies how knowledge about the body’s response to infection permeates these groups. Sepsis is a costly severe response to infection that is a leading preventable cause of death in Canada.

ZTCloudGuard: Zero Trust Context-Aware Access Management Framework to Avoid Medical Errors in the Era of Generative AI and Cloud-Based Health Information Ecosystems

Managing access between large numbers of distributed medical devices has become a crucial aspect of modern healthcare systems, enabling the establishment of smart hospitals and telehealth infrastructure. However, as telehealth technology continues to evolve and Internet of Things (IoT) devices become more widely used, they are also increasingly exposed to various types of vulnerabilities and medical errors. In healthcare information systems, about 90% of vulnerabilities emerge from medical error and human error. As a result, there is a need for additional research and development of security tools to prevent such attacks. This article proposes a zero-trust-based context-aware framework for managing access to the main components of the cloud ecosystem, including users, devices, and output data. The main goal and benefit of the proposed framework is to build a scoring system to prevent or alleviate medical errors while using distributed medical devices in cloud-based healthcare information systems. The framework has two main scoring criteria to maintain the chain of trust. First, it proposes a critical trust score based on cloud-native microservices for authentication, encryption, logging, and authorizations. Second, a bond trust scoring system is created to assess the real-time semantic and syntactic analysis of attributes stored in a healthcare information system. The analysis is based on a pre-trained machine learning model that generates the semantic and syntactic scores. The framework also takes into account regulatory compliance and user consent in the creation of the scoring system. The advantage of this method is that it applies to any language and adapts to all attributes, as it relies on a language model, not just a set of predefined and limited attributes. The results show a high F1 score of 93.5%, which proves that it is valid for detecting medical errors.

The effect of novel linguistic-based review features on review helpfulness through information ecosystem and ELM theories: Heterogeneity analysis across platforms

Although online review helpfulness has been extensively discussed, examining it at the platform level can still yield new insights. Drawing on ELM and information ecosystem theories, this study identifies heterogeneity in review features and their impact on helpfulness across platforms through a multimethod analysis of 82,130 reviews on JD and TikTok. Econometric analysis revealed that reviews on mature platforms contain richer objective content, more diverse language styles, and stronger semantic associations. In terms of content, objective content diversity positively affects helpfulness on emerging platforms, while it has the opposite effect on mature platforms. Negative sentiment significantly affects helpfulness only on mature platforms, and positive sentiment has no significant effect on either platform. In terms of language style, the analysis indicated that language style diversity positively impacts the helpfulness of emerging platforms. However, four specific styles (figurative, comparative, interrogative and exaggerative) negatively affect helpfulness on emerging platforms, with only comparative style having a significant negative effect on mature platforms. In terms of semantic association, the results show a more substantial positive impact on emerging platforms. Machine learning-based performance analysis corroborates the core findings of the econometric analysis. This study provides novel findings to the existing literature and provides managerial implications for different platforms.

"Do not inject our babies": a social listening analysis of public opinion about authorizing pediatric COVID-19 vaccines.

Designing effective childhood vaccination counseling guidelines, public health campaigns, and school-entry mandates requires a nuanced understanding of the information ecology in which parents make vaccination decisions. However, evidence is lacking on how best to "catch the signal" about the public's attitudes, beliefs, and misperceptions. In this study, we characterize public sentiment and discourse about vaccinating children against SARS-CoV-2 with mRNA vaccines to identify prevalent concerns about the vaccine and to understand anti-vaccine rhetorical strategies. We applied computational topic modeling to 149 897 comments submitted to regulations.gov in October 2021 and February 2022 regarding the Food and Drug Administration's Vaccines and Related Biological Products Advisory Committee's emergency use authorization of the COVID-19 vaccines for children. We used a latent Dirichlet allocation topic modeling algorithm to generate topics and then used iterative thematic and discursive analysis to identify relevant domains, themes, and rhetorical strategies. Three domains emerged: (1) specific concerns about the COVID-19 vaccines; (2) foundational beliefs shaping vaccine attitudes; and (3) rhetorical strategies deployed in anti-vaccine arguments. Computational social listening approaches can contribute to misinformation surveillance and evidence-based guidelines for vaccine counseling and public health promotion campaigns.

The Role and Influence of Social Media in Crisis Communication: An Analysis with Twitter as An Example

Nowadays, social media has become an indispensable part of information dissemination, and its role and influence are constantly shaping the information ecology of today's society. At the same time, the attention of crisis events on social media continues to increase, which is of great significance for crisis management and response. This paper aims to take Twitter as an example to explore the role and influence of social media in crisis communication, and to analyze its role in instant transmission, information transmission speed, public opinion guidance, public relations channels and emotional connection in crisis events through literature review and case analysis. This paper aims to reveal the function mode, communication effect and coping strategy of social media in crisis communication and provide theoretical support and practical reference for improving public crisis awareness and crisis coping ability. At the same time, this paper provides reference for establishing an effective crisis communication management mechanism, which is helpful to improve the public's cognition and understanding of crisis events.

Algorithm-Based Recommendations: A Study on the Media Behavior of "Lurking" Participants

This study delves into the media behaviors of "lurking" participants, a distinct user group, by analyzing their activities in the online space. It uncovers the multifaceted impacts of algorithmic recommender systems on "lurking" participants. The research finds that algorithms not only profoundly influence users' content selection and preference development but also play a pivotal role in shaping their social interaction patterns, thereby having profound effects on the overall information ecosystem. Furthermore, this study explores the complexities of how algorithmic recommender systems mold users' information consumption habits.

Exploring the paradox: Perceptions of AI in higher education – a study of hype and scandal

In the rapidly evolving field of generative artificial intelligence (GenAI), the introduction of OpenAI’s ChatGPT-4 signifies a noteworthy juncture economically, in workplaces, and in education. This article explores the dual public perception of GenAI as both promising and controversial, especially in higher education. The study is rooted in ‘information ecologies’ to understand the integration and implications of new technologies in educational settings. Employing a ‘multiplicity’ method, the article emphasizes a self-reflexive, context-sensitive approach, utilizing digital ethnography and auto-ethnographic narratives to analyse the nuanced public perception and its effects on the use of AI in academia. The research underlines the importance of a balanced integration of AI, aiming for students to become proficient in managing AI products, which is essential for aligning educational practices with modern workplace demands.