Research on Convergence Media Ecological Model Based on Blockchain

Abstract

Currently, the media industry is in the rapid development stage of media integration, which has brought about great changes in content production mode, presentation form, communication mechanism, operation and maintenance management, etc. At the same time, it is also faced with problems such as difficult information traceability, declining industry credibility, low data circulation quality and efficiency, difficult data security and user privacy protection, etc. Utilizing blockchain’s characteristics can solve these problems that the media industry is currently facing. This paper designs a convergence media ecology model based on blockchain (CMEM-BC), focusing on the basic elements of the model, node operation and maintenance system, node management mechanism, value circulation mechanism, and storage mechanism, trying to establish a decentralized, traceable, and immutable convergence media ecosystem. On this basis, this paper summarizes the ecological framework and ecological model of CMEM-BC. Finally, the paper describes the verification of the effectiveness of CMEM-BC in key links through simulation experiments, verifying that CMEM-BC has high originality and is more suitable for the application of convergence media ecology through model analysis and comparison.

1. Introduction

At present, the media industry is in the rapid transformation stage of the convergence media and is experiencing the development process of gradual evolution from the full coverage of new media to the comprehensive integration of the media [1]. Since the development of media convergence has been widely explored, it has gradually expanded from the theoretical level to the implementation level and has achieved remarkable results. The media industry has brought about great changes in content production mode, presentation form, communication mechanism, operation and maintenance management, etc. However, in the process of development, the convergence media ecology also faces problems such as difficult information traceability, declining industry credibility, low data circulation quality and efficiency, difficult data security and user privacy protection, and operation and maintenance efficiency [2]. The development of the convergence media ecosystem also faces several urgent issues that need to be addressed [2].

(1)

Difficulty in information traceability

Amidst the rapid development of the convergence media ecosystem, the sources of information have become diversified. Information may be forwarded and adapted by numerous media platforms in a short period, making it difficult to trace the original source. This poses a significant challenge to verifying the authenticity and accuracy of information.

(2)

Decline in industry credibility

With the prosperity of the convergence media ecosystem, competition within the media industry has also intensified. Some media platforms may adopt strategies of false advertising to gain traffic, which not only damages their image but also leads to a gradual decline in industry credibility. So, it is necessary to link the media industry’s credibility with media workers and media platforms [3].

(3)

Inefficient data circulation

In the media industry, due to the diversity of data sources and the complexity of data processing, issues such as delays, losses, and errors may arise during data transmission and processing. This affects the timeliness and accuracy of information dissemination.

(4)

Challenges in data security and user privacy

As the volume of convergence media data continues to increase, data security and user privacy protection have become increasingly prominent issues. Due to limitations in technical means and interference from human factors, the risks of data leaks and privacy violations still exist.

Currently, the development trajectory of convergence media in the media industry is relatively clear. However, the time since the shift towards intelligent media integration has been brief, leading to limited practical application and insufficient depth of implementation. This paper argues that the progress of convergence media should focus on the following key areas [1,4]:

(1)

Content production

The methods of content production in convergence media will undergo significant transformations, becoming more efficient, intelligent, and diverse. This shift will reduce labor and time costs, optimizing the process of content creation and editing.

(2)

Information dissemination

The process of information dissemination within convergence media is likely to evolve in terms of its five core components: the communicator, audience, message, medium, and effect, leading to changes in how information is shared.

(3)

Ecological governance

As convergence media expands in scale and scope, it will develop into a complex industrial ecosystem. To sustain this ecosystem, effective governance is essential, including the establishment of a dynamic management system and mechanism to enhance the efficiency of ecological operations and maintenance.

(4)

Conceptual shift

Technologies such as artificial intelligence, big data, and blockchain will significantly impact the development of media convergence, altering operational methods. To adapt, media professionals must evolve their thinking and stay current with technological advancements, or risk being left behind in this changing landscape.

Blockchain is a distributed database technology that records and verifies data transactions in systems in a decentralized, immutable, and highly secure manner [5]. The ideal application of blockchain in the media industry is to combine the convergence media to build a convergence media ecology based on blockchain. The characteristics of blockchain can reduce the monopoly and control of centralized large platforms and achieve “paid quantification” of the value contribution of media content participants through blockchain technology. At the same time, combining artificial intelligence, big data, and other technologies can change the existing content market pattern, solve the problem of difficult traceability of media content in the transmission process, and solve the problem of low timeliness and high cost faced by media content in the copyright identification and transaction process [2,6].

The convergence media ecology built based on blockchain technology aims to delegate power to ordinary nodes in the ecology, thus changing the pattern of a few central nodes to control information. Blockchain convergence media is expected to have a profound impact and change on the existing business model, content creation mode, and industry structure, and reshape the ecological pattern of the entire media industry [7]. At the same time, the introduction of token economy model can make blockchain media no longer rely on push advertising and fake news to obtain click-through rate for profit. Content creators can share or price their own content through smart contracts, while content consumers can pay through tokens, creating a new collaboration paradigm for media content dissemination [6,8].

In the blockchain convergence media ecology, the creation mode of media content can be changed from a clue-oriented mode to a user-centered mode. By using the blockchain token mechanism, a content crowdfunding platform can be established to determine the production process of content according to the fundraising situation. Under this mechanism, all the participating nodes in the ecology have the opportunity to participate in the dissemination of convergence media content, and the nodes that actively participate in ecological activities can be rewarded. These activities will be recorded on the blockchain, which will have a certain impact on the current communication mechanism of the media [9]. Blockchain convergence media ecosystem can open up the whole industrial chain of content producers, content consumers, advertisers, and ecological builders in the ecosystem, price the communication value of all content, reward and protect the nodes through the token system, and provide a full, safe, and complete economic value transformation mechanism for all links in the content industry chain. In this way, the legitimate benefits of all participants in the digital content industry chain can be fully and fairly quantified, so as to create a media digital content industry chain ecosystem driven by blockchain technology [10].

In this paper, Section 1 introduces the research purpose of this paper, Section 2 introduces the current relevant research status, Section 3 focuses on the main research methods, Section 4 presents the research results and discussion, and Section 5 provides the summary. In summary, the aim of this study was, by introducing blockchain technology in the convergence media, to use the characteristics of blockchain decentralization, traceability, immutability and so on to solve the problems faced by convergence media, such as copyright traceability, transaction difficulties, and profit difficulties of convergence media nodes, eventually forming an industrial ecology and thus changing the operation and maintenance mechanism of the existing media industry. This will play an innovative role in copyright protection and asset management, credit source certification and content review, content production and news crowdfunding, intelligent trading and advertising effect, public opinion analysis of public opinion, and public opinion environment. At the same time, by optimizing some key technologies in the blockchain-based convergence media ecology, gradually improving the overall credibility, communication power, guiding power, and influence of the convergence media platform, a blockchain-based convergence media ecology model (CMEM-BC) was established.

2. Related Work

At present, the media industry is developing rapidly, and artificial intelligence and other technologies have been through the operation and maintenance links of information collection, content production, content distribution, public opinion monitoring, and copyright protection, driving the intelligent transformation of the media industry [11]. Convergence media plays multiple roles in grassroots governance, including information dissemination, organizational mobilization, value guidance, and consultation services, and it plays an increasingly important role in the current grassroots governance. Media convergence is not a simple combination, but an in-depth integration of the existing system, mechanism, content, channels, platforms, talents, and market [12].

In recent years, blockchain technology has developed rapidly and has been widely used in many fields such as healthcare [13], agriculture [14], energy [15], and financial industry [16]. With the maturity of blockchain technology, it has gradually been applied in the media industry. In some European and American countries, blockchain technology was developed early, and the application of blockchain in the media industry has developed relatively fast. Some progress has been made mainly in copyright protection, content production, intelligent trading, and other fields, but there is a lack of systematic research on blockchain in the whole convergence media ecology [17].

Chen B et al. introduced a security model for IoT systems using smart contracts on the blockchain platform, which offers decentralized, tamper-proof, and programmable features. These characteristics help create a secure and trustworthy environment for improving overall IoT system security [18]. Shi QS et al. explored the use of blockchain in a decentralized electricity trading model by incorporating a reliability coefficient with smart contracts and a credit value mechanism. By applying these to a simulated electricity market, their results showed that the blockchain-based system improved efficiency, reduced transaction verification times, and minimized the risk of defaults and attacks [19]. Razaque A et al. proposed a blockchain-enabled deep recurrent neural network (BDRNN) for detecting malicious clickbait. Their experiments demonstrated that the BDRNN model outperformed other approaches in terms of accuracy, link detection, memory usage, and resistance to attacks [20]. Jaiman V et al. presented a blockchain-based consent model for managing access to individual health data. Their model used smart contracts to dynamically capture consent and allowed data requesters to search and access health data. Their evaluation indicated that the model was efficient, adaptable to personalized access control policies, and offered a flexible approach to managing health data-sharing scenarios [21]. Liu Y et al. presented an architecture of a consortium blockchain-empowered port supply chain system and proposed a system verification framework for the smart contracts of port supply chains with probabilistic behaviors [22]. Hisseine MA et al. performed a literature review about the application of blockchain in social media, and their findings showed that previous studies on the applications of blockchain in social media are focused mainly on blocking fake news and enhancing data privacy [2]. Liu LQ et al. studied current difficulties faced by the media, discussed the possibility of developing “blockchain + media”, and through investigation, summarized that blockchain has great potential for media development, but current studies on this topic are still in early-stage, and the results need to be observed [8]. Shin D et al. examined real-world applications of blockchain technology in the media industry using Qingbo Big Data. They analyzed the current global development of blockchain and the media sector, identifying key challenges. To address these issues, they proposed strategies to enhance the integration of blockchain with the media industry in the big data era. Their study revealed that blockchain’s technical features can effectively resolve major concerns such as copyright risks, opaque algorithms, and fragile trust mechanisms within the media industry [23].

In this work, we designed a convergence media ecological model based on blockchain; studied and analyzed the basic components, node operation and maintenance system, node management mechanism, value circulation mechanism, and storage mechanism of CMEM-BC; and initially established an operation and maintenance system based on the ecological node attributes such as participation and credit degree in the convergence media ecology. Then, we designed the dynamic entry and exit mechanism of ecological nodes and developed the storage mechanism of ecological data elements of blockchain combined with interplanetary file system (IPFS). At the same time, the possible problems faced by CMEM-BC were studied, and a solution suitable for this model is proposed in this paper.

3. Materials and Methods

The convergence media ecology based on a blockchain model involves extensive research content. According to the characteristics of the media ecology, this study focused on the basic elements, node operational mechanism, node management mechanism, value circulation mechanism, and storage mechanism, and at the same time, it focused on the basic design of the CMEM-BC, pointed out some problems, and put forward the corresponding solution.

3.1. Base Element

The basic elements of the convergence media ecology based on blockchain are mainly expounded from three aspects: ecological nodes, data elements, and block structure. Together they constitute the internal underlying structure of the blockchain convergence media ecosystem, realize the communication and interaction within the system through the exchange of media content and information, realize the value-added of data through the circulation of information, and optimize the content creation environment under the interaction, coordinate the relationship between participants, and promote the normal operation and maintenance of the convergence media ecosystem.

3.1.1. Ecological Nodes

Ecological nodes are the individuals that exist independently in the media ecology of blockchain and integration. The main functions of nodes can be divided into three types of nodes: content producers, content consumers, and content regulators. The identities of the three nodes can be transformed in the actual ecological operation and maintenance.

Content producers are the key to existing in blockchain media ecology, which potentially involves all citizens in convergence media ecology, and they can be professional journalists, editors, commentators, and the general public. They can also be newspaper, press, news media organizations, radio stations, and network platforms. In some studies, they are also known as the business organization node. These groups can produce professional media content, as well as User-Generated Content (UGC) [24].

Content consumers are the recipients and users of content in the ecology. They may not only participate in the circulation activities of content but also assume the obligation of giving feedback to the content. At the same time, they have the right to use and the right to participate in the content, which is also known as ordinary user nodes in some studies.

The role of content regulators is to supervise and feedback information and nodes, and at the same time to supervise the illegal operation and negative participation of nodes, such as relevant authorities and responsible units in ecology, which is also called the node of regulatory agencies in some studies.

3.1.2. Data Element

In blockchain convergence media ecology, each node can be used as a producer of data element but can also be the data element of consumers. The data element is the core of media ecological content. According to the special properties of the media industry, media ecological data element can be divided into the following categories: content data, interactive data, copyright data, value evaluation data, advertising data, user data, authentication, transaction data, circulation data, token data, etc. In blockchain data circulation, they can be collectively referred to as transaction data [25,26].

In blockchain media ecology, the data element is stored in distributed databases in the form of blocks and encrypted using cryptographic technology, which makes the data more secure and reliable, and it is not affected by centralized institutions. Data elements are managed and exchanged through blockchain technology. Users can create and exchange digital assets in the convergence media ecology, and the ownership and transaction records of these assets are recorded through blockchain technology.

The life cycle of data elements include data production, data transmission, data storage, data processing, data circulation, data privacy protection, data access control, data destruction, etc. Data production refers to the process of the node in the ecology itself or through other equipment; data transmission refers to the transmission process between the nodes in the ecology or between the data centers outside the ecology; data storage means that the data generated in the ecology is stored in a distributed storage, as well as the process of archiving important data; data processing includes the process of completing data iteration through calculation, analysis, and update according to the preset rules or methods in the ecology; data circulation includes the organizational management of the data, as well as the process of data circulation through disclosure, sharing, trading, and other forms; data privacy protection is the process of privacy protection of relevant information in the process of ecological data production, transmission, and processing; data access control is mainly the control of data use rights in the process of data processing and data circulation; data destruction refers to the process of destroying data elements in the ecology in accordance with relevant laws and regulations or industry regulations. The life cycle of ecological data elements in blockchain convergence media is shown in Figure 1.

3.1.3. Block Structure

Like other blockchain systems, the block in the convergence media ecology is also composed of a block head and block body, and the block head also contains version number, timestamp, and previous block hash [27]. Unlike the existing mature Bitcoin blockchain system, there are mainly different aspects:

(1)

Because the consensus mechanism is different, the difficulty target and nonce random number in the common block head will no longer be practical but will use the number of seeds used in the PoE consensus mechanism and the pseudo-random number generated [28]. In addition, there are also version number, previous block hash, timestamp, and Merkle root information. The version number refers to the version information of the block, which is used to identify the version of the block structure and rules; timestamp refers to the time when the block is created, which is used to determine the time order of the block and provide an important factual basis for the blockchain data; previous block hash refers to the hash value of the previous block, which is used to link different blocks in the blockchain; Merkle root refers to the Merkle root hash of transaction data, which is used to verify the transactions contained in the block, and it can quickly verify the integrity of the data element record [29].

(2)

Due to the complex diversity of the blockchain media ecological affairs, the basic data in the block are no longer only the transaction data. According to the classification of common affairs in the blockchain media ecology, the block data should contain content data, interactive data, copyright data, user data, circulation data, evaluation data, etc.

The block structure in the blockchain convergence media ecology is shown in Figure 2.

3.2. Node Operation and Maintenance Mechanism

In order to ensure the basic operation and maintenance of the blockchain convergence media ecology and the basic rights and interests of nodes in the ecology to participate in ecological operation and maintenance, we studied the establishment of a node operation and maintenance system based on node interaction and node integrity, define the participation and credit degree of nodes, and play a role in distinguishing node contribution degree in the relevant links of ecological operation and maintenance.

3.2.1. Participation System

Node participation is a digital embodiment of the comprehensive status of node participation in system affairs, including the frequency, scope of interaction, popularity, etc. The participation system is established mainly based on the following principles:

(1)

Set up the initial participation for the nodes that join the convergence media ecology.

(2)

Nodes publish content in the convergence media ecology, including news, articles, audio, video, patents, etc., to gain participation points.

(3)

Nodes that participate in the forwarding, comments, likes, and other interaction will obtain the corresponding token reward.

(4)

Nodes participate in convergence media ecological management affairs to obtain participation plus points.

(5)

The node actively initiates the transaction by an exit degree, and the node corresponds to the transaction by an additional entry degree.

(6)

The corresponding out and entry degrees of nodes can be accumulated.

The participation P of nodes is the comprehensive embodiment of Out-degree Op, In-degree Ip, and the number of interactive nodes Node.

$$P=a\times Op+b\times Ip+c\times Node$$

(1)

In this model, the weights of output, entry, and total node count can be adjusted by modifying the coefficients a, b, and c. If needed, different weights can be assigned to various transaction types, though this is not elaborated in the paper. Typically, c > b > a, meaning the interaction scope more effectively highlights the importance of nodes in system construction, while the In-degree weight ranks second. This suggests that passively initiated interactions better capture a node’s popularity and help prevent nodes from manipulating the system through excessive active participation.

3.2.2. Credit System

The node credit degree digitally represents a node’s credibility within the system. In the convergence media ecosystem, the node’s credit degree serves as a reference for its trustworthiness when engaging in system activities. Every node is assigned its own credit degree, which fluctuates based on its behavior within the system. The participation mechanism is built upon the following core principles:

(1)

Set up the initial credit rating for the nodes that join the convergence media ecology.

(2)

Credit bonus points for publishing popular media content (combined with likes, comments, and retweets above the threshold).

(3)

The accounting nodes complete the block packaging and receive a credit bonus through the system consensus.

(4)

If the node releases illegal content or participates in evil behavior, there will be credit deduction after passing the punishment consensus.

(5)

If candidate consensus nodes and accounting nodes do not participate in the consensus process many times, there will be a credit deduction.

3.2.3. Credit Influence

During an accounting cycle, the system generates accounting nodes based on the credit of each node. Generally, nodes with a higher credit are more likely to gain accounting rights. Additionally, to incentivize these nodes, they receive both credit and token rewards after block packaging is completed. This increases their chance of securing the next accounting right, potentially leading to a Matthew effect, where the rich get richer and the poor get poorer. While the Matthew effect can be beneficial in some contexts, it can impede the balanced development of the media ecosystem, where active participation from all nodes is encouraged [30]. To address this, the system adjusts the impact of node credit over multiple accounting cycles, with the influence diminishing as the number of accounting instances increases.

The concept of half-life is widely used in fields such as physics, medicine, and chemistry. Statistically, half-life refers to the time required for half of an unstable isotope to decay [31]. We apply this concept to the information half-life of accounting instances. After a node has held accounting rights N times, its credit influence is halved. Consequently, the credit influence for subsequent accounting rights decreases accordingly.

$$E_i=C_i\times {{\displaystyle \frac{1}{2}}}^{{\displaystyle \frac{n}{N}}}$$

(2)

$C_i$ is the credit rating of node i in the current accounting cycle. Assuming that the credit degree of a node changes the data in the consensus cycle, the actual influence in the consensus cycle should show the trend of decay with the change in its accounting times, which can solve the problem of the Matthew effect in the system to a certain extent.

The node for accounting rights is credit reward; assuming that a node bookkeeping credit reward for e, the credit reward should not make the node in the next accounting cycle of credit influence growth, namely the next cycle in the cycle credit after half-life algorithm modification should be less than the last influence; otherwise, the system will lead to the growth of the credit of the Matthew effect.

$$C_i\times {{\displaystyle \frac{1}{2}}}^{{\displaystyle \frac{n}{N}}}>(C_i+e)\times {{\displaystyle \frac{1}{2}}}^{{\displaystyle \frac{n+1}{N}}}$$

(3)

$C_i$ is the current credit degree of node i, N is the number of half-life bookkeeping set by the system, and n is the current bookkeeping times of node i. According to formula (3), we can obtain ${e<C}_{\mathrm{i}}$. It is concluded that when the accounting credit rating reward is less than the current credit rating of the node, the Matthew effect is not easily produced in the system.

3.3. Node Management Mechanism

According to the characteristics of blockchain convergence media ecology, in the early stage of ecological development, CMEM-BC adopts the form of an alliance chain, and the form of a public chain can be tried after the ecology gradually matures. In the alliance chain, the access and exit of nodes should be limited by the alliance. Combined with the characteristics of convergence media ecology, this paper establishes a node dynamic access and exit mechanism (NDAE) according to the participation and credit degree of nodes [32]. The specific process is as follows:

(1)

When a node applies to join the blockchain convergence media ecosystem, it first initializes basic personal information, including unified standard global unique identifier (GUID), asymmetric public and private key pair, communication address, node name, signature information, etc., and submits it to the regulatory node in the ecosystem. After passing the consensus mechanism, it becomes an ecological node. Then, the initial participation and credit degree of the system setting are obtained. Finally, the consensus node broadcasts to increase the ecological node transaction, and the certificate authority in the ecosystem issues digital certificates to it [28].

(2)

In ecological operation and maintenance, nodes update the value of ecological node participation degree and credit degree according to the system rule. When the value of node participation degree and credit degree is less than the threshold set by the system, the supervision node in the ecosystem can initiate an application for withdrawing this node from the ecosystem. After the consensus mechanism is passed, the node will be withdrawn from the ecosystem and its participation degree and credit degree information will be reset to 0. The consensus node broadcasts information about nodes exiting the system, while the certificate authority in the ecosystem deregisters its digital certificate and updates the Certificate Deregistration list (CRL).

(3)

When the ecological node actively applies for withdraw from the ecology, after the consensus mechanism, the consensus node will broadcast the ecological node to exit the broadcast, and the certificate institution will cancel its digital certificate and update the CRL list.

(4)

When a node in the ecology initiates a communication request, the node sends its digital certificate to the communication party node, and the communication party node verifies the digital certificate identity with the certificate agency’s public key, and the communication request is received by the initiator.

The detailed flowchart of the dynamic joining withdrawal mechanism of ecological nodes is shown in Figure 3, in which the ecological node applicant is referred to as A, its communication node T, regulatory agency node R, and certificate institution C.

Based on the above design ideas, this paper studies the smart contract implementation of a node’s dynamic access and exit mechanism. It should be noted that the well-known smart contract of Ethereum is written based on the Solidity language, while the blockchain system studied in this paper is written based on the Python language. In order to facilitate reading, the pseudo-code of this smart contract is written in Python language. The pseudo-code of node dynamic join exit mechanism based on smart contract is as shown in Algorithm 1.

Algorithm 1 Node dynamic access and exit smart contract algorithm

Input: application node base information guide: global unique identifier, public_key: asymmetric public key, private_key: asymmetric private key, address: communication address, name: node name: signature: signature information, participation_score: engagement, credit_score: credit, certificate: digital certificate, nodes []: collection of experimental nodes

Output: node dynamic access and exit ecological information

1:  # The Node applies to join the ecology

2:  def apply_to_join(guid, public_key, private_key, address, name, signature):

3:    # TODO: Initialize the node information and submit the accession request

4:    # TODO: After the consensus mechanism is passed, the ecological node transactions are added by the consensus node broadcast

5:    new_node.certificate = issue_certificate (new_node) # Certificate is issued by the certification authority

6:  # Ecological node is actively withdrawn

7:  def exit_ecosystem(node):

8:    # TODO: After the consensus mechanism is passed, the consensus node broadcasts the node to exit the transaction

9:    nodes.remove(node)

10:    revoke_certificate(node)

11:  # The Certificate Authority issues a digital certificate

12:  def issue_certificate(node):

13:    if verify_signature (node): # Check whether the node information is legal

14:      return certificate = { node.guid,node.public_key, sign_certificate (node)} # Certificate authority returns the certificate information

15:  # Certificate agency signature certificate

16:  def sign_certificate(node):

17:    # TODO: Sign the certificate information with the private key of the certificate authority

18:    return signature = sign_with_key(certificate_info, certificate_authority_private_key)

19:  # The Certificate organization cancels the digital certificate

20:  def revoke_certificate(node):

21:    update (CLS) # Unregister the node certificate and update the CLS list

22:  # Regulatory regulatory initiates the application for mandatory exit node

23:  def initiate_exit(node):

24:    if node.participation_score < threshold or node.credit_score < threshold:

25:      # TODO: After the consensus mechanism is passed, the consensus node broadcasts the node to exit the transaction

26:      nodes.remove(node)

27:      revoke_certificate(node)

28:  if __name__ == “__main__”:

29:    # TODO: Node access and exit call

3.4. Value Circulation Mechanism

The value circulation in the blockchain media ecology refers to the value transfer from the data element of one node to other nodes, and then forms a circular and healthy blockchain media ecology. In this ecology, nodes can obtain value by creating and circulating data elements, and the value circulation can be divided in three ways: sharing, trading, and openness [33,34].

Through the use of blockchain technology, value circulation can be managed and recorded through tokens, credit rating, participation, etc., as a reward for the creators or providers of data elements, or as a tool for value exchange between nodes. In the blockchain convergence media ecology, the circulation of value is managed through a governance mechanism, which can enforce how to circulate tokens or implement credit, engagement rewards, etc., through smart contracts, which helps to ensure fairness and transparency of value within the ecosystem, ensure the completion of the circulation of value within the ecosystem, and help maintain community coordination and consistency [35].

Content producers first perform creation, release, or circulation of media ecological data elements, which can be the article, video, audio, pictures, form of content, and the corresponding blockchain transaction records, through the consensus mechanism uploaded to blockchain media platform, the corresponding data element content stored on the IPFS distributed storage system, and producers according to the system’s preset rules for the corresponding value incentive reward. Content consumers’ browsing, viewing, reading, or distribution of media ecological data elements, such as likes, comments, and circulation, are recorded on the blockchain to ensure transparency and traceability, while obtaining corresponding value incentives according to the preset rules of the system. The systematic establishment of a token system can realize the exchange of token assets and real assets, and encourage ecological nodes to participate in the process of data element value circulation so as to improve the utilization rate of the data element value and realize the appreciation of the data element value.

Value circulation reflects the process of ecological operation, mainly based on the following premises:

(1)

Consensus mechanism is unified. The consensus mechanism is the core of the blockchain convergence media ecology and the baton of the normal operation of the whole ecology, so the consensus mechanism of the nodes in the ecology should be unified.

(2)

Activity rules are unified. This mainly includes the unification of circulation rules and participation rules in the blockchain convergence media ecology. The unification of circulation rules mainly refers to the process, commission fee, and information of circulation requirements; the unification of participation rules mainly refers to the unified authority and obligations of their roles for each participant in the ecology.

(3)

The user system is unified. There are multiple types of functional users in the media ecology of blockchain, and user identity can be changed in the process of ecological operation and maintenance. For example, content producers of a certain link can also be transformed into content consumers in the subsequent links. Users can connect with all affairs in the ecology without re-registering an account, which simplifies the user system in the ecology, facilitates the nodes to participate in the value circulation of data elements, and also improves the retention rate of users.

(4)

Unified circulating assets. Blockchain integrates the media ecology to unify the circulation of assets, establishes a unified token system, and standardizes the value assets in the ecology into a unified media, which can greatly improve the value circulation and exchange of data elements. The unification of circulating assets makes the value circulation between different user groups easier and more transparent. These unified assets can be used to measure and transfer value, thus enabling processes like circulation, motivation, and interaction.

To sum up, value circulation is the core part of the blockchain convergence media ecology, which realizes the creation, transmission, and distribution of value through digital assets and governance mechanism. From the original data circulation through the convergence media ecology based on blockchain, and finally to the new data value circulation, the data value circulation of CMEM-BC data element is shown in Figure 4.

Based on the above process, this paper designs the smart contract in the process of data element circulation. The pseudo-code of the contract is written in the Python language and used in the form of local deployment and operation. The data element and smart contract construction pseudo-code are shown in Algorithm 2.

Algorithm 2 Data elements and smart contract construction

import: Owner: data owner; value: data value; description: data description; sharedWith: list of shared users; isShared: shared; isPublic: open; isTransferred: whether traded

output:Data element and smart contract construction

1:  # Define the structure of the data element

2:  class DataElement:

3:    def __init__(self, owner, value, description, isShared, sharedWith, isPublic, isTransferred):

4:  # Data element contract

5:  class  DataElementContract:

6:    Data _ elements = {} # A dictionary of all data element

7:    # Create a data feature

8:    def create_data_element(self, owner, value, description):

9:      new_data_element = DataElement(owner, value, description)

10:      self.data_elements[new_data_element.id] = new_data_element

11:    # Share the data features to a specific user

12:    def share_data_element(self, data_element_id, user):

13:      data_element = self.data_elements[data_element_id]

14:      data_element.isShared = True

15:      data_element.sharedWith.append(user)

16:    # Open data element

17:    def  make_public(self, data_element_id):

18:      data_element = self.data_elements[data_element_id]

19:      data_element.isPublic = True

20:    # Purchase of the data element

21:    def  buy_data_element(self, data_element_id):

22:      data_element = self.data_elements[data_element_id]

23:      data_element.isTransferred = True

24:      transfer(data_element.value, msg.sender, data_element.owner)

25:      data_element.owner = msg.sender

26:  if  __name__ == “__main__”:

27:    # TODO: Instantiated data element

28:    # TODO: Instantiated data element contract

The pseudo code of ecological node and smart contract construction is shown in Algorithm 3.

Algorithm 3 Ecological node and smart contract construction

import: Basic information of ecological nodes

output: Ecological node and smart contract construction

1:  # User contract

2:  class UserContract:

3:    users = {} # Store the user’s dictionary

4:    def register_user (self, user): # User registration

5:      users[user] = User(user)

6:    def get_user_info (self, user): # Get user information

7:      return users[user]

8:  # Define the structure of the user

9:  class User:

10:    def  __init__(self, address):

11:      self.address = address # user address

12:      self. Owned _ elements = [] # List of data element owned by the user

13:      self.shared_elements = [] # List of data element shared by the user

14:    # Data element sharing

15:    def share_data_element(self, data_element_contract, data_element_id, user):

16:      data_element = data_element_contract.data_elements[data_element_id]

17:      data_element_contract.share_data_element(data_element_id, user)

18:      self.shared_elements.append(data_element_id)

19:    # Data element for disclosure

20:    def make_data_element_public(self, data_element_contract, data_element_id):

21:      data_element = data_element_contract.data_elements[data_element_id]

22:      data_element_contract.make_public(data_element_id)

23:    # Data element trading

24:    def buy_shared_data_element(self, data_element_contract, data_element_id):

25:      data_element = data_element_contract.data_elements[data_element_id]

26:      data_element_contract.buy_data_element(data_element_id)

27:      self.owned_elements.append(data_element_id)

28:  if  __name__ == “__main__”:

29:    # TODO: Registered users

30:    # TODO: instantiated user contracts

3.5. Storage Mechanism

Due to the large volume and variety of data elements in the blockchain convergence media ecology, the data element can be stored on the blockchain in the form of a hash value, while the actual content is stored in the distributed storage system of an interstellar file system (InterPlanetary File System, IPFS) to reduce the burden on the blockchain [36]. The nodes with data element storage requirements can save the data element in the deployed IPFS system storage nodes; the IPFS system will fragment the data element, and then return to the node system according to the unique hash value generated by the data element content. The node can select the resulting storage hash encryption, add the encrypted hash to the corresponding ecological transaction record, and then publish the system broadcast [37]. When the data element content needs to be obtained, the hash value corresponding to the data element can be obtained in the blockchain system, and then the original content of the data element can be obtained in the IPFS system. The IPFS distributed storage system bears the pressure of data storage, making up for the lack of limited storage space and inefficient transaction processing in the blockchain system. The deep integration of blockchain and IPFS greatly improves the storage efficiency of the data element in the blockchain convergence media ecology. The CMEM-BC data element storage process is shown in Figure 5.

In the ecological model of blockchain convergence media, an account-based model is adopted, so that data elements and user behavior can be associated with the user account. Each user has an account, and all its content and interactive data are stored in the data structure related to its account, so that user participation is more personalized and controllable. In order to meet the needs of multiple users and frequent interactions in the ecology, the ecological underlying data are created based on a key–value type data structure and stored by LevelDB database. The key–value type data structure is very simple and efficient, and it can be applied to fast ecological storage and large data retrieval; it is very useful for managing user accounts and data elements [38]. At the same time, LevelDB is a lightweight, embedded database suitable for being embedded in the blockchain node or applications, and it can handle a large number of read and write operation; it can also adapt to the media ecological need for rapid response to user requests [39].

3.6. Security Analysis

CMEM-BC uses a consensus mechanism based on a node efficiency named PoE [28]. In the PoE consensus mechanism, the efficiency of nodes is a comprehensive reflection of the interaction between nodes including node participation, credit degree, and number of accounting times. The PoE consensus mechanism is based on node efficiency, combined with a verifiable random function, node importance algorithm, and information half-life. Below is an analysis of common security attacks on blockchain systems.

3.6.1. The 51% Resource Attack

The 51% resource attack refers to a malicious node that attempts to disrupt the system’s balance by controlling 51% of the system’s resources, thereby influencing the system’s normal and orderly development [40]. The consensus mechanism in CMEM-BC is based on the participation system, credit system, and interaction relationships in the ecosystem, combined with PageRank sorting, half-life algorithm, and verifiable random function to generate candidate consensus nodes and accounting nodes. Throughout the process, the nodes’ control over resources is not fully controllable, and the generation of accounting nodes has a certain randomness based on system resources. Malicious nodes cannot launch an attack by accumulating 51% of the resources, so CMEM-BC can effectively resist 51% resource attacks.

3.6.2. Witch Attack

A witch attack typically refers to a network node in a distributed system that continually changes its identity through disguises, causing other nodes in the same system to mistakenly believe that it is a different node. The attacking node uses these disguised node identities to disrupt the normal operation of the distributed system [41].

In CMEM-BC, a malicious node attempting to impersonate another must replicate the same characteristics of the media ecology, including participation, credibility, and interaction patterns, which significantly raises the difficulty of successful masquerading. Additionally, during the accounting cycle, the data provided by a node must be verified by other candidate consensus nodes based on its public and private key pairs. This verification process helps prevent impersonation by ensuring robust identity authentication, making CMEM-BC resilient against such attacks.

3.6.3. Selfish Mining Attack

A selfish mining attack is a deceptive blockchain mining strategy in which one miner or a group of miners obtain the right to record transactions, creating a new block, but do not broadcast it. Instead, they construct a private branch of their own and expand this private branch using their advantage in the consensus competition. Their goal is not to destroy the entire blockchain system but to obtain additional benefits by exploiting their advantage in the consensus process and rendering the consensus work of honest nodes meaningless [42].

In CMEM-BC, accounting rights are assigned sequentially by candidate consensus nodes based on verifiable random numbers derived from a randomly generated seed number for each cycle. If node A, which is responsible for generating the random number, experiences delays, it will be replaced by node B, which can generate the number on time. As a result, node A cannot ensure it will gain accounting rights in the subsequent cycle. Additionally, nodes cannot create forks in the blockchain by delaying block publication. This mechanism enables CMEM-BC to withstand selfish mining attacks.

Through the above analysis, we can conclude that CMEM-BC can resist most blockchain attack methods, such as 51% resource attack, witch attack, and selfish mining attack.

4. Results and Discussion

4.1. Model Experiment

For a decentralized content circulation system such as blockchain convergence media, node entry and exit management, internode communication, and data element circulation have their technical particularities, which are the key links of the model. To verify the utility of CMEM-BC, this study conducted simulation experiments on the node management mechanism and value circulation mechanism of two key links of CMEM-BC.

After the node joins the ecology, it can obtain the node certificate of the blockchain convergence media ecology, and the nodes holding the certificate can initiate communication. In order to verify the effectiveness of a dynamic node addition of an exit smart contract in the ecology, this study carried out a simulation experiment of a dynamic addition of exits between nodes and carried out the communication between nodes. The pseudo-code used in the experiment is shown in Algorithm 4.

Algorithm 4 Node dynamic access, exit, and inter-node communication verification

import: Node base information

output: Simulation of dynamic access exit and verification of communication between nodes

1:  # Ecological node communication request

2:  def  communicate(sender_node, receiver_node, certificate):

3:    if  validate_certificate(receiver_node, certificate):

4:      if (cetificate not in CLS) # If the certificate is not in the CLS list

5:       # TODO: Perform the communication operation

6:       # The communication node verifies the digital certificate

7:  def  validate_certificate(node, certificate):

8:    # TODO: Use the certificate authority public key to decrypt and verify the digital certificate

9:    return True

10:  # Communication node verifies the node signature

11:  def  verify_signature(node):

12:    # TODO: To verify the validity of the node signature by using the public key

13:    return True # Placeholder for signature verification

14:  # Example call

15:  if  __name__ == “__main__”:

16:    apply_to_join(“node1”, “pub_key_1”, “priv_key_1”, “address_1”, “Node 1”, “node1_signature”)

17:    apply_to_join(“node2”, “pub_key_2”, “priv_key_2”, “address_2”, “Node 2”, “node2_signature”)

18:    apply_to_join(“node3”, “pub_key_3”, “priv_key_3”, “address_3”, “Node 3”, “node3_signature”)

19:    # Node 1 initiates a communication application to Node 2

20:    certificate = nodes[0].certificate

21:    communicate(nodes[0], nodes[1], certificate)

22:    # Update the participation rate and credit rating information of the participating nodes

23:    update_scores(nodes[0], p0, c0)

24:    update_scores(nodes[1], p1, c1)

25:    update_scores(nodes[2], p2, c2)

26:    supernode.initiate_exit (node [2]) # Regulatory initiated application for mandatory exit from Node 3

27:    Exit _ ecosystem (node [0]) # node 1 actively initiated the application

28:    communicate(nodes[0], nodes[1], certificate)

29:    communicate(nodes[2], nodes[1], certificate)

The simulation experiments of dynamic node access and exit and trusted communication between nodes showed that the NDAE mechanism can well manage node access and exit in the ecology, realize the application management of trusted nodes in the ecology, and realize the management of nodes’ active exit from the ecology, and can force the exit management of untrusted or inactive nodes, ensuring the integration of blockchain media from the bottom of the ecology. At the same time, effective communication can be established between ecological nodes, while non-ecological nodes cannot initiate effective communication. The safety of state operation and maintenance improves the enthusiasm of ecological nodes to a certain extent and activates the entire ecological activity, which can improve the operation and maintenance efficiency of the ecology.

In order to verify the effectiveness of the smart contract of the data element value circulation in the ecology, this study carried out the simulation experiment of data element value circulation. The pseudo-code of the smart contract of data element value circulation used in the experiment is shown in Algorithm 5.

Algorithm 5 Smart contract simulation of data elements value circulation

import: Basic information of data elements and basic information of ecological nodes

output: Data elements value circulation information

1:  # Instance combination

2:  data_element_contract = DataElementContract()

3:  user_contract = UserContract()

4:  # Create a data feature

5:  data_element_contract.create_data_element(“owner_address”, 100, “Sample data”)

6:  # Register a user

7:  user_contract.register_user(“user_address”)

8:  # Obtain the user information

9:  user_info = user_contract.get_user_info(“user_address”)

10:  # Condition 1 Ecological nodes automatically perform data element sharing

11:  if condition 1:

12:    user_info.share_data_element(data_element_contract, “data_element_id”, “other_user_address”)

13:    broadcast (“Data feature sharing transaction”);

14:    if PoE(): # The consensus mechanism is approved by the system

15:      # TODO: System incentive

16:  # Meet Conditions 2 Ecological nodes automatically perform data element disclosure

17:  if condition 2:

18:    user_info.make_data_element_public(data_element_contract, “data_element_id”)

19:    broadcast (“Data Element disclosure transaction”);

20:    if PoE(): # The consensus mechanism is approved by the system

21:      # TODO: System incentive

22:  # Condition 3 Ecological nodes automatically execute data element transactions

23:  if condition 3:

24:    user_info.buy_shared_data_element(data_element_contract, “shared_data_element_id”)

25:    broadcast (“Data Flement Transaction”);

26:    if PoE(): # The consensus mechanism is approved by the system

27:      # TODO: System incentive

In the laboratory simulation environment, the smart contract of data element value circulation based on Algorithm 5 is used to randomly initiate 10,000 times of three types of value circulation requests between nodes in CMEM-BC. Simulation experiments show that all requests completed the predetermined circulation of the data element value and completed the blockchain storage of data element circulation transactions after passing the consensus mechanism.

4.2. Ecological Architecture

The ecological architecture of blockchain media ecology refers to the overall architecture of the interaction between blockchain technology and convergence media to realize decentralized content management, distributed storage and circulation, etc. According to the basic functions of blockchain media ecology, CMEM-BC can be divided into the following six layers of architecture [43,44]:

(1)

Basic data layer. The basic and data layer is the foundation of the whole convergence media ecology, including the transaction data stored on the blockchain and the data element stored in the IPFS system. These data are stored on the blockchain in a distributed, immutable manner, ensuring the integrity and credibility of the data.

(2)

Network layer. The network layer establishes the communication and connection between the blockchain nodes. The P2P (point-to-point) network is adopted in the blockchain convergence media ecology. This layer ensures the information transmission and synchronization between each node and enables the whole system to update the data in real time.

(3)

Core consensus layer. The core consensus layer defines the consensus mechanism on the blockchain. The consensus layer ensures that the nodes agree on the data on the blockchain, prevents the attacks of malicious nodes, and maintains the security of the blockchain. The present model adopts the efficiency proof consensus mechanism (PoE) based on node efficiency [28].

(4)

Value incentive layer. The value incentive layer is a level used to reward participants, usually using tokens or node attributes to measure value. This layer ensures that content creators, content consumption, ecological regulators, and other participants are motivated to actively participate in the ecology, thus promoting the growth and development of the ecology.

(5)

Smart contract layer. The smart contract layer includes the writing, deployment, and execution of smart contracts. Smart contracts are automated, programmable code used to execute consensus business logic, ensuring reliable execution of contracts, and providing transparent operation and maintenance rules [45]. In this paper, the model mainly studies the dynamic entry and exit of nodes, the value circulation of data elements, and the intelligent contract of the incentive strategy of data element sharing, so as to realize the access, exit, and communication management of nodes in the ecology, promoting the value circulation of data element and the implementation of the incentive for participating in the sharing of nodes.

(6)

Application layer. The application layer is the first layer closest to the user, including integrating media applications, user interface, etc., making it more convenient for users to participate in ecological affairs. The application layer can improve the ecological user experience.

The hierarchy architecture diagram of CMEM-BC is shown in Figure 6.

4.3. Ecological Model

The convergence media ecological model based on blockchain involves a wide range of research contents. This paper focuses on the above aspects according to the characteristics of the convergence media ecology. According to the model construction and the main research content, this paper summarizes the convergence media ecological model based on blockchain as shown in Figure 7.

In order to summarize the characteristics, advantages, and disadvantages of the CMEM-BC model, this paper studies other research models related to blockchain or convergence media, and conducts a qualitative comparative research on them from the aspects of blockchain type, consensus mechanism type, node attributes, etc. This paper lists four relatively representative research models, and the details are shown in

Table 1. Comparison of CMEM-BC with blockchain or convergence media models.

Index	COBATS [46]	Google AdWords [47]	OAMVB [48]	AC-BMS [49]	CMEM-BC
Based on blockchain	True	False	True	True	True
Based on convergence media	False	True	False	False	True
Blockchain type	Alliance chain	None	Alliance chain	Private chain	Alliance chain
Consensus mechanism	PoS and PBFT	None	Improved PBFT	PBFT	PoE
Smart contract	False	False	False	True	True
Excitation mechanism	True	False	True	False	True
Participation system	False	True	False	False	True
Credit system	True	False	False	False	True
Artificial intelligence	False	True	False	True	True
Machine learning	False	True	False	False	False

. The comparison results show that the research model in this paper has some originality, which is more suitable for the application of convergence media ecology from the perspective of functionality. However, there are still many shortcomings in this model compared with other solutions, such as the use of artificial intelligence, machine learning, and other auxiliary technologies that need to be further studied to achieve more intelligent operation and maintenance.

5. Conclusions

Currently, the media industry is undergoing a rapid transformation in the context of the convergence media’s development, evolving from full coverage of new media towards comprehensive media integration. This transition has sparked significant changes in content production, presentation formats, communication mechanisms, and operational management within the industry. However, the convergence media ecosystem also confronts challenges such as difficulties in information tracing, declining industry credibility, inefficiencies in data circulation, challenges in data security and user privacy protection, and room for improvement in operational efficiency.

Based on an analysis of the existing issues within the convergence media ecosystem, this paper integrates the advantages of blockchain technology in the media industry to design a convergence media ecosystem model based on blockchain (CMEM-BC). The paper delves into the fundamental elements of CMEM-BC, encompassing the classification of ecological nodes, data elements, and block structure within the model. Furthermore, it explores and designs the operational and maintenance system of CMEM-BC, grounded in participation, credibility, and credibility influence. Additionally, the node management mechanism, value circulation mechanism, and storage mechanism of CMEM-BC are researched and designed. Functional simulation experiments conducted on CMEM-BC demonstrate that nodes can dynamically join or exit the blockchain-based convergence media ecosystem based on their level of participation, credibility, and willingness. Effective communication can be established among ecological nodes, facilitating the value circulation of data elements among them. Moreover, after passing the ecological consensus mechanism, the blockchain storage of data element circulation transactions can be achieved. Comparisons and analyses with similar models reveal that CMEM-BC possesses a certain degree of originality and is more suitable for application in convergence media ecosystems from a functional perspective.

CMEM-BC can provide practical advice and support for professionals and the media industry, addressing fundamental issues like tracing difficulties, data security, user privacy protection, etc. First, CMEM-BC ensures the authenticity and credibility of data in the production, distribution, and consumption of content, which is critical for news reporting and content moderation in the media industry. Second, through the automated execution of smart contracts, professionals can establish a trusting relationship directly with users, thereby reducing the cost of communication and collaboration. Finally, CMEM-BC can also effectively solve the problem of copyright protection and ensure that the ownership of original content is not infringed, and professionals can receive a more equitable distribution of revenue, thus promoting the development of innovation in the media industry. Nonetheless, CMEM-BC is not yet fully mature in practical applications, and it may encounter problems of reduced operating efficiency when applied on a large scale. In addition, the current use of CMEM-BC users is insufficient, and the use of the system will face greater challenges. Finally, the current data types of the CMEM-BC operation are not comprehensive enough, and the robustness of the system will be challenged in the face of new data types. In the future, CMEM-BC needs to increase the optimization of system stability and operation scale, expand the type of system operation and maintenance data, increase the promotion of users’ usage range, and constantly optimize the system performance in order to adapt to the rapid development of convergence media.