Blockchain technology in policies to combat disinformation

Research on disinformation and fake news has advanced significantly following the election of Donald Trump in the United States (2016), the Brexit referendum in the United Kingdom (2016) and, in Brazil, the election of Jair Bolsonaro as president in 2018 (Recuero, 2019). Authors such as Abad (2018) and Volkoff (2004, p. 11) argue that the term disinformation had already been used during Second World War, and particularly during the Cold War, as a strategic instrument in geopolitical disputes. Likewise, Darnton (2017) traces the use of disinformation back to historical records from the Byzantine Empire (sixth century). Accordingly, disinformation should be understood as a deliberate instrument for distorting reality that predates contemporary digital technologies and constitutes part of the broader phenomenon of information disorder (Wardle & Derakhshan, 2017). According to Genesini (2018, p. 49), what is truly “new” is not the practice of disinformation itself, but rather the platforms and technologies that enable its large-scale dissemination, since “attempts at political falsification through the distortion of facts and information” have been present throughout human history.

This “new” technological dimension has attracted increasing scholarly attention. Several authors (Castro & Ribeiro, 1997; Francisco, 2004; Wardle, 2016; Tandoc, Lim, & Ling, 2018; Carvalho, 2019; Madrigal, 2018; Tsfati et al., 2020; Carvalho & Mateus, 2018; Brisola & Romeiro, 2018; Blanco Alfonso, Galera,& Calvo, 2019; Pinto & Zanetti, 2020) have highlighted the expansion of research on disinformation across different disciplines and theoretical perspectives. These studies contribute to establishing disinformation as a broader phenomenon, while fake news is understood as one of its manifestations, alongside other forms such as satire, manipulated content, clickbait and related practices.

Regarding the technological challenges emphasized in discussions on disinformation and fake news, another technology – blockchain – has emerged as a promising tool across multiple areas of government. The first proof of concept for this technology was introduced in October 2008 through the anonymous paper published under the pseudonym Satoshi Nakamoto, entitled Bitcoin: A Peer-to-Peer Electronic Cash System. The paper describes how the core characteristics of a secure, decentralized network could enable the creation of a transferable digital currency. Freitas and Vaz (2022) document and systematize blockchain initiatives implemented in various sectors of public administration in Brazil and internationally. They also highlight the potential for developing new blockchain-based applications to address a broader range of public sector challenges.

Against this background, this study investigates a new potential application by addressing the following research question: How can blockchain technology contribute to combating fake news and disinformation? This inquiry is grounded in the premise that disinformation constitutes a public problem in which the State plays a central role. Although the terms disinformation and fake news are occasionally used interchangeably throughout this article, it is important to clarify that disinformation is understood here as the broader phenomenon, whereas fake news is regarded as one of its manifestations. Therefore, examining how blockchain technology can contribute to addressing disinformation necessarily encompasses its potential contribution to combating fake news, since mitigating fake news also helps reduce disinformation and, consequently, information disorder.

To address this research question, an analytical framework was developed based on an integrative literature review to investigate potential applications of blockchain technology, bridging theoretical discussions from the fields of public policy and the literature on fake news and disinformation. The primary objective is to explore the intersections between blockchain technology and disinformation, particularly from the perspective of its potential use by the State. Accordingly, the scope of this study extends beyond a conventional literature review by identifying potential applications of blockchain technology to support the design of public policies aimed at addressing the challenges posed by disinformation.

The remainder of this article is organized as follows. The next section presents the key concepts necessary to understand fake news and disinformation, followed by an overview of the main characteristics of blockchain technology. The subsequent section describes the research methodology, and the final sections present the principal findings and the systematic synthesis of the results.

Amid ongoing conceptual debates surrounding disinformation and fake news, authors such as Fallis (2015) propose criteria for determining whether a given piece of information constitutes disinformation. These criteria include: (1) recognizing that disinformation is, in fact, information; (2) recognizing that this information is misleading and (3) recognizing that the misleading information is intentionally designed to induce error. In this sense, disinformation should not be understood as the mere absence of information, but rather as existing information that is deceptive and deliberately produced to mislead (Fallis, 2015; Zattar, 2017).

Within this perspective, fake news is considered a specific form of disinformation that manifests itself as the imitation of legitimate news content in digital environments. Christopoulou (2019, p. 55), in a systematic literature review aimed at identifying conceptual variations, concludes that there is still no consensus regarding an appropriate taxonomy. To provide greater conceptual clarity, Wardle & Derakhshan (2017, p. 5) classify information disorder into three categories, each involving combinations of false and/or potentially harmful information:

1. Disinformation: false and harmful information intentionally created and disseminated to cause harm. It is typically promoted by malicious actors who deliberately imitate legitimate communication patterns, including the visual aesthetics of viral memes and seemingly amateur digital content.

2. Misinformation: false information that is not necessarily intended to deceive or cause harm (false information that is not necessarily harmful). In this case, an unsuspecting individual may unknowingly produce or share misleading content without malicious intent.

3. Malinformation: information that may be factually accurate but is shared with the intention of causing harm, often through hate speech, harassment or reputational attacks (harmful information that is not necessarily false). This commonly occurs when truthful information is deliberately taken out of context.

A growing body of research highlights blockchain technology as a promising instrument for addressing public-sector challenges (Freitas & Vaz, 2022; Akers et al., 2019; Alketbi et al., 2018; Ølnes, Ubacht, & Janssen, 2017; Hölbl et al., 2018). Existing applications include healthcare, where blockchain supports the management of medical treatment records; land administration, through the creation of immutable property registries and public accountability initiatives, such as the cooperation agreement between the Brazilian Federal Court of Accounts (TCU) and the Brazilian Development Bank (BNDES) to develop the Brazilian Blockchain Network (RBB) ^[1].

For blockchain to support such applications, the network must be capable of processing a large number of transactions within a short period while ensuring the verification and validation of predefined transaction parameters. These guarantees are achieved through smart contracts executed under the network's consensus protocol. This capability relies on a set of technological characteristics that enable the construction of immutable and highly verifiable distributed data networks (Freitas & Vaz, 2022):

1. Public and private cryptographic keys. These function as authorization mechanisms that enable information to be securely encrypted, transmitted and decrypted within the network. They allow network algorithms to process and validate data without exposing the underlying information (Aranda-Tyrankiewicz & Jahankhani, 2023). The private key is analogous to a digital signature, granting users exclusive access to their information, with each registered participant possessing a unique private key. The public key enables network algorithms to verify the authenticity and integrity of transaction data.

2. Hash-linked blocks. This feature is primarily responsible for blockchain's immutability. Information is stored in blocks, each represented by a cryptographic hash that is mathematically linked to the hash of the previous block. Consequently, every block depends on the integrity of its predecessor. This creates a cascade effect: if the content of Block A is altered, its hash changes, which invalidates Block B, subsequently affecting Block C and the remainder of the chain (Freitas & Vaz, 2022).

3. Smart contracts. Smart contracts consist of predefined logical rules that establish the requirements for validating information within the blockchain. They provide validating algorithms with embedded instructions specifying the conditions that must be satisfied for data to be accepted as valid (Taherdoost et al., 2023). In simplified terms, smart contracts operate through logical “if/when/then” statements that define the criteria for determining the validity of a given set of information (He et al., 2023). Once these logical conditions are fulfilled, the contracts are executed automatically by the blockchain, according to the network's validation and processing capabilities, beginning at the moment new information is added to the blockchain (Agrawal, Angelis, Khilji, Kalaiarasan, & Wiktorsson, 2023).

4. Consensus protocol. The consensus protocol defines the mechanism through which validating algorithms determine whether the information contained in a block is valid. It establishes the procedures required to satisfy the logical requirements specified by smart contracts, ensuring that validators reach algorithmic agreement before information is accepted as trustworthy within the network (Borges do Val, Viana, & Borges Gouveia, 2021). This process substantially enhances network security because transaction validation depends on approval by a majority of validators (50% + 1), which may correspond to hundreds or even thousands of distributed nodes, depending on the degree of decentralization of the blockchain network.

This study develops an analytical framework based on the knowledge currently available in the literature. At the same time, the existing body of knowledge on blockchain technology and its documented applications provides sufficient grounds for drawing inferences regarding this new potential use. Accordingly, the analytical framework proposed here is intended to support future, more in-depth investigations, including empirical studies examining new implementations of blockchain technology that are expected to emerge in the near future. As the field continues to evolve, further developments will naturally require subsequent revisions and refinements of the proposed framework.

Given this context, the study adopts an integrative literature review (also referred to as a systematic integrative review) as its research strategy. This methodological approach enables the synthesis of findings from previously published studies, thereby generating new knowledge grounded in the evidence produced by prior research (Botelho, Cunha, & Macedo, 2011; Silva, 2018).

The literature search encompassed both peer-reviewed journal articles and unpublished master's theses and doctoral dissertations. Given the relatively recent emergence of the topic, including grey literature was considered an appropriate strategy to reduce the risk of overlooking recent studies that had not yet been published in conference proceedings or academic journals. The search was limited to publications produced between 2017 and 2023, reflecting the growing scholarly interest in disinformation and fake news during this period. This increased attention followed major political events, including the election of Donald Trump in the United States (2016), the Brexit referendum in the United Kingdom (2016) and the election of Jair Bolsonaro as President of Brazil in 2018, all of which intensified debates regarding the impact of fake news on the public sphere (Recuero, 2019).

In defining the scope of our literature review from 2017 onward, we considered two key contextual factors. First, we observed the remarkable advancement of digital platforms and information technologies, which have played a crucial role in the dissemination and influence of disinformation. Second, we recognized the ongoing societal debates that not only intensified during this period but also elevated the issue onto the governmental policy agenda. Furthermore, the substantial body of studies published during this time provides a valuable opportunity for a more comprehensive analysis. By adopting this more focused time frame, we are able to examine recent trends, emerging developments and evolving strategies in the field of disinformation with greater precision, including the innovative potential of blockchain technology as a tool for combating this phenomenon.

For the literature review, an initial mapping was conducted by selecting keywords and searching nine bibliographic databases, including both Brazilian and international sources: CAPES Journal Portal, Brazilian Digital Library of Theses and Dissertations (BDTD), ProQuest, Oasis IBICT, SciELO, ScienceDirect, SpringerLink, Scopus and Web of Science. The review process followed the PRISMA guidelines (Page et al., 2021), which enhance the transparency and methodological rigor of the literature selection process. The search strategy was developed iteratively, with keywords being progressively refined based on the results obtained from the initial searches and insights from previous studies, until the final set of search terms was established. Combining these search terms made it possible to identify points of convergence between blockchain technology and its potential applications in addressing disinformation.

Table 1 presents the initial search results according to each search term and the corresponding bibliographic database.

The following inclusion and exclusion criteria were established:

Inclusion criteria: (a) studies presenting proof-of-concept applications of blockchain technology for combating fake news; (b) studies focusing on solutions implemented through blockchain-based networks and algorithms and (c) studies discussing the role of blockchain as a tool to support the State in addressing fake news.

Exclusion criteria: (a) studies describing blockchain technology in general terms without providing technical specifications regarding its application to the context of disinformation or fake news; (b) duplicate publications presenting the same discussion under a different title and (c) studies for which the full text was unavailable.

Figure 1 illustrates the article selection process adopted for this integrative literature review.

The application of the inclusion and exclusion criteria described above resulted in a final sample of 13 studies, which provided relevant insights into the potential of blockchain technology to address disinformation and fake news.

The selected studies were analyzed to identify the authors' proposed solutions, with particular attention to how they conceptualized the role of the State in implementing measures to combat fake news. These considerations also informed the development of the analytical categories used to classify the selected studies. This process enabled the organization and synthesis of the evidence, leading to the construction of an analytical framework that captures the current state of the art regarding the use of blockchain-based systems to combat fake news. In addition, the framework provides a foundation for future research on the evolution of these technological solutions. The analysis also considered the potential integration of complementary technologies, such as artificial intelligence (AI) and machine learning, with blockchain to develop more comprehensive solutions with enhanced capabilities for verifying the authenticity of information.

The proposed categorization is based on two dimensions identified in the literature: the type of application and the technological layer of implementation. This two-dimensional framework recognizes that the adoption of blockchain technology is shaped both by the specific demands of society and the State and by the technological capabilities inherent to blockchain itself, as well as by its integration with other digital technologies. It also acknowledges the fact that governments may employ these technological resources both as direct users and as regulators of emerging technologies capable of influencing public policies aimed at combating disinformation.

This study represents a focused effort to identify research that demonstrates the synergies between blockchain technology and strategies for combating disinformation. The proposed approach seeks not only to map the current state of research on these two topics but also to highlight their intersections and the potential contributions that blockchain technology may offer to mitigate the effects of disinformation in contemporary society. It is important to emphasize that the objective of this study is not to provide an exhaustive review of all available research on blockchain and disinformation. Rather, it aims to extract relevant insights from these fields in order to identify patterns, research gaps and opportunities that can support the development of an analytical framework. Particular attention is given to studies presenting empirical evidence of proof-of-concept applications, implemented solutions and discussions of blockchain as a technological resource to support government efforts in addressing disinformation. This approach is consistent with the need to establish a robust foundation for future empirical research and for the continued refinement of the proposed analytical framework, while acknowledging the dynamic nature of both the study of disinformation and the rapid evolution of blockchain and related digital technologies.

The main characteristics of the selected studies, as well as their respective classifications, are presented in Table 2 and discussed in the following sections.

The proposed analytical framework conceptualizes the use of blockchain networks according to two distinct functional needs. The first is validation, which involves analyzing sets of information to establish a reliable body of parameters that can subsequently be used to validate future blocks of information. Within this category, two alternative approaches emerge from the literature: (a) validation based on parameters defined by trusted media authorities or fact-checking organizations; and (b) validation performed automatically through algorithms embedded within the blockchain network.

The second functional need is traceability, which enables the identification of the sources and dissemination pathways of fake news across different formats and communication channels. This capability facilitates the detection of professional and/or criminal organizations that systematically produce and disseminate false information as part of business models or political strategies, as well as actors who manipulate truthful information by removing it from its original context. Accordingly, the proposed framework considers the continuous evolution of Internet communication channels, encompassing not only traditional or purported news websites but also social media platforms and other forms of digital content dissemination. Given the diversity of these communication environments, effective responses require technological solutions that can be adapted to different contexts. Based on these functional requirements, the framework identifies three categories of blockchain network applications for combating fake news. The first two categories are associated with information validation and parameter definition, whereas the third focuses on traceability.

1. Blockchain networks based on validation through parameters established by trusted authorities within the network. This category encompasses most of the proposals that are already operational to some extent, as well as the most advanced proof-of-concept implementations. These approaches rely on validation mechanisms that incorporate assessments or parameters provided by trusted participants within the network (i.e., validating agents), representing recognized communication stakeholders such as universities, newspapers, magazines, television organizations and other public and private institutions. Among the studies included in this category, some advocate building these solutions on existing blockchain infrastructures, particularly Ethereum, because of its mature smart contract capabilities and scalability (Christodoulou & Christodoulou, 2020). Others argue that new infrastructures are required to integrate blockchain systems with social media platforms, where fake news is disseminated on a large scale (Paul et al., 2019). Several proposals also adopt consensus mechanisms, particularly the Proof of Credibility (PoC) protocol, in which semantic similarity analyses are performed on validators' feedback to classify information. Based on these analyses, credibility and reputation scores are assigned to validators and content publishers. Over time, these scores become reference parameters for grouping information sources and identifying news networks with a higher probability of containing either reliable or false information (Torky et al., 2019).

2. Blockchain networks based on validation through parameters determined by internal algorithms. This category is represented by a smaller number of studies, largely because the proposed solutions require a more advanced level of technological development, particularly with regard to processing capabilities. The decision-making structures needed to establish validation parameters are considerably more complex than those based on human validators. The limited number of contributions in this area can also be attributed to the frequent need to integrate blockchain with additional technologies, especially those related to AI, such as machine learning and deep learning. The incorporation of these technologies adds another layer of technical complexity to discussions regarding the feasibility of blockchain-based systems for detecting and combating fake news (Shahbazi & Byun, 2021). The idea of granting the system sufficient authority to autonomously classify information is directly related to two key factors: (i) the degree of structuring and categorization of the underlying database of false and misleading content, and (ii) the level of governance and transparency associated with the AI algorithms responsible for making validation decisions.

3. Blockchain networks focused on traceability. This category comprises proposals that emphasize the traceability capabilities of blockchain networks. Rather than focusing on the semantic validation of content, these approaches aim to identify dissemination patterns in order to detect networks and actors responsible for spreading fake news (Babar et al., 2020). They also seek to identify cases in which factually accurate information has been deliberately taken out of context to generate disinformation. Within this approach, objective publication metadata, such as the author's identity, the web address (URL) and the publication timestamp, are permanently recorded on the blockchain. Each time the content is shared, information about the user responsible for the dissemination is automatically added to the distributed ledger. This makes it possible to reconstruct patterns of information sharing and identify coordinated dissemination networks.

The State should be viewed not only as the entity responsible for designing and coordinating public policies to combat fake news, but also as the representative of the public interest in overseeing the approaches adopted by organizations and the technological systems they develop to implement different validation protocols. In other words, the State's role extends beyond coordinating strategies to combat fake news (Christodoulou & Christodoulou, 2020); it also includes supervising their implementation to ensure that citizens' rights and the public interest are safeguarded throughout the process. To fulfill this role, governments require a strategic understanding of where and how they can intervene in the design, implementation and oversight of validation processes, as well as in the definition of the requirements embedded in blockchain networks used to detect disinformation and the dissemination of fake news.

The analytical framework proposed in this study identifies two technological layers through which blockchain can support the establishment of validation requirements: the External Parameter Layer (EPL) and the Internal Parameter Layer (IPL).

1. EPL. This first technological layer encompasses blockchain-based approaches in which validation parameters are established through the feedback provided by trusted participants within the network (i.e., validating agents) (Qayyum, Qadir, Janjua, & Sher, 2019), as well as approaches focused on detecting dissemination patterns (Dwivedi et al., 2020). In these cases, the interpretation of information is not performed autonomously by the system itself but is based on assessments issued and recorded on the blockchain by recognized authorities or qualified entities within the relevant domain (Paul et al., 2019). Consequently, the primary challenge lies in ensuring the appropriate qualification and monitoring of the feedback provided by these trusted participants. In this context, PoC protocols (Torky et al., 2019) represent an important complementary mechanism because they evaluate not only the credibility of the information being assessed but also the reputation of the validators themselves. This is achieved through a reputation system that assigns different weights to each evaluator's assessment according to its degree of agreement with the evaluations provided by the majority of other validators. Within the EPL, the State may intervene through the regulation, coordination and oversight of the process by which social actors are accredited to participate in the blockchain network as trusted validators responsible for establishing validation parameters. Such intervention may vary in scope, ranging from relatively light-touch regulatory approaches, such as regulating civil society consortia, collaborative networks or industry self-regulatory initiatives, to more interventionist models involving public–private collaborative networks dedicated to information validation (Christodoulou & Christodoulou, 2020).

2. IPL. This technological layer requires a higher level of technological maturity than currently available, as the development of fully automated systems for establishing validation parameters depends on the integration of blockchain with additional computational technologies (Xiao et al., 2020). The most promising approaches within this layer involve the integration of AI techniques (Shahbazi & Byun, 2021), particularly natural language processing (NLP), enabling systems to analyze the semantic structure of information and compare it with previously validated datasets. Based on these analyses, the system can estimate the probability that a given piece of information is false or has been deliberately presented out of context. The principal limitations of this layer are associated with the substantial computational resources required to maintain these interconnected validation algorithms operating across the blockchain network (Saad et al., 2019). Factors such as computational capacity, network scalability and processing time become increasingly critical as the number of validation parameters and the volume of information recorded on the blockchain continue to grow. Within this context, the State's role is to establish mechanisms for algorithmic transparency, enabling effective oversight of both the validation protocols and the parameter-setting processes carried out by advanced AI-based systems. As with the EPL, government intervention may vary in intensity.

By associating the findings of the literature review on blockchain-based approaches to combating disinformation with the theoretical categories of disinformation and the technological layers identified in the previous sections, it was possible to develop an analytical framework for organizing different strategies to address disinformation, as illustrated in Figure 2.

As shown in Figure 2, the categories disinformation, misinformation and malinformation can be organized according to whether the information is false, harmful or both. False information can be assessed through language-based validation parameters, whereby its semantic content is compared against a trusted reference database. In contrast, harmful information that is not necessarily false requires the analysis of contextual elements, making dissemination-based validation parameters more appropriate. For example, the widespread circulation of otherwise truthful information may indicate that it is being strategically employed to produce harmful effects.

In this context, both technological layers (EPL and IPL) play complementary roles. With respect to language-based validation parameters, external validators remain necessary until the blockchain network accumulates a sufficiently robust knowledge base to enable autonomous validation through its own internal algorithms. Similarly, in the case of harmful information requiring dissemination-based validation, traceability mechanisms benefit from the interaction between the two layers: while internal parameters can identify anomalous dissemination patterns automatically, external validation can provide additional contextual assessment. At the technological frontier, the principal challenge lies in developing internal parameters capable of identifying not only textual patterns but also contextual indicators.

The analytical framework developed through the proposed methodology made it possible to understand the relationship between validation capability and the legitimacy of the parameter-setting process. When the blockchain network possesses sufficient analytical capacity to interpret and validate information autonomously according to predefined parameters, the legitimacy of the process depends primarily on ensuring algorithmic transparency. Conversely, when the network is unable to establish validation parameters independently and therefore relies on external actors to provide them, the central challenge becomes the development of transparent and robust governance protocols for selecting, accrediting and monitoring the validators responsible for participating in the network. In both scenarios, the State can play a fundamental role, through regulation, implementation and oversight, in supporting the use of blockchain technology to combat fake news and disinformation.

The proposed framework is based on a systematic synthesis of the existing literature on the application of blockchain technology to public policies aimed at combating fake news and disinformation. Accordingly, it is important to emphasize that the framework is limited to technological resources and applications that have already been documented in the academic literature. It does not seek to propose a novel implementation model for blockchain-based systems.

Likewise, the framework is not intended to prescribe an ideal model for technology regulation or implementation. Instead, its purpose is to organize and integrate the evidence reported in previous studies, highlighting potential areas of convergence that deserve further investigation. The framework proved capable of consistently classifying the technological initiatives proposed in the studies analyzed, thereby demonstrating its analytical validity. Ultimately, this framework provides a comprehensive and structured perspective on existing blockchain-based approaches to combating disinformation and fake news, offering a valuable foundation for future research and practical applications in this field.

This study sought to answer the following research question: How can blockchain technology contribute to combating fake news and disinformation? To address this question, an analytical framework was developed based on an integrative literature review of the potential applications of blockchain technology, bridging theoretical perspectives from the fields of public policy, fake news and disinformation. In addition to positioning blockchain as a potential tool for public administration, this study reinforces the need to recognize disinformation as a relevant research topic and as a public policy problem. Addressing this challenge requires the development of an interdisciplinary research agenda capable of supporting solutions that involve multiple sectors.

Although the analysis of specific implementation cases was beyond the scope of this study, the proposed framework proved applicable to the cases reported in the literature reviewed. Future research may employ this framework as an analytical tool to examine new initiatives involving the use of blockchain technology to combat disinformation. Nevertheless, the framework is not intended to serve as the sole or definitive analytical instrument for this purpose. Given the relatively recent application of blockchain technology in this domain, complementary analytical approaches will be necessary. Such approaches may also contribute to the future refinement of the proposed framework.

The findings of this study suggest several directions for future research.

From an institutional perspective, further studies are needed to examine the political and social processes involved in implementing blockchain-based solutions such as those discussed in this article. Public policy instruments and governance arrangements designed to combat disinformation may themselves constitute important objects of investigation, particularly with respect to the factors that facilitate or hinder their implementation. The adoption of blockchain technologies for combating disinformation requires the development of institutional arrangements in which the State plays a central role. As governmental organizations assume greater responsibilities in this field, the demand for technological expertise and institutional capacity will inevitably increase. Future research should also investigate mechanisms for decentralizing the governance of user accreditation and oversight within blockchain networks operating under internal validation parameters, thereby reducing the risks associated with unilateral or overly centralized control of network governance by public authorities. Consequently, the adoption of blockchain technologies requires the development of new technological capacities within the public sector. These capacities extend beyond technical expertise and include the competencies of public officials responsible for implementing these technologies. Examining how governments adopt blockchain technologies in other policy domains may provide valuable insights into the institutional capabilities required to support their application in combating disinformation.

From a technological perspective, additional research is needed to evaluate the large-scale implementation of applications that integrate AI with blockchain networks for information validation and source traceability. Finally, future studies should adopt a comparative perspective by examining the implementation of other technologies, whether complementary to blockchain or independent of it, in order to broaden our understanding of the methods, institutional arrangements and technological practices available for addressing disinformation.