Warranted assertibility and the Internet: A theoretical model for an online proto-research community

In this paper, we suggest that research platforms on the present Internet should offer more diverse pathways for distributed communication, to cope with the idiosyncrasies of a post-truth society. Present platforms adhere to a first-order cybernetic approach, using rule-based systems and algorithms to guide the activity of researchers, and expose them to new research findings and articles based on their preferences. The larger Internet, however, supports communities such as Reddit, that offer opportunities for pragmatic problem-solving that mirrors the ideas of second- order cybernetics, but show much potential for incivility. We first test this assumption using 704 comments responding to 25 top posts pulled from the CoronavirusUS subreddit, using a Python script. Our analyses indicate that a substantial percentage of posts in the subreddit display higher-order reflectivity (what we label transformative critical reflection) which predicts the number of upvotes received by these posts. We also found that karma, or user reputation, is not predicted by interaction between high-order reflectivity and upvotes. This suggests that posts are gauged by quality rather than users’ reputations. From these results, we infer that such communication can be mirrored in online proto-research communities, and streamlined by laying down regulations, appointing moderators, and using algorithms to guide distributed communication, and combat the propensity for chaos arising from emancipation. We lay out our design/vision for such a community, based on a dual-layered reformulation of the Open Source Educative Processes framework.

Reliable Reputation Review and Secure Energy Transaction of Microgrid Community Based on Hybrid Blockchain

A growing number of prosumers have entered the local power market in response to an increase in the number of residential users who can afford to install distributed energy resources. The traditional microgrid trading platform has many problems, such as low transaction efficiency, the high cost of market maintenance, opaque transactions, and the difficulty of ensuring user privacy, which are not conducive to encouraging users to participate in local electricity trading. A blockchain-based mechanism of microgrid transactions can solve these problems, but the common single-blockchain framework cannot manage user identity. This study thus proposes a mechanism for secure microgrid transactions based on the hybrid blockchain. A hybrid framework consisting of private blockchain and consortium blockchain is first proposed to complete market transactions. The private blockchain stores the identifying information of users and a review of their transactions, while the consortium blockchain is responsible for storing transaction information. The block digest of the private blockchain is stored in the consortium blockchain to prevent information on the private blockchain from being tampered with by the central node. A reputation evaluation algorithm based on user behavior is then developed to evaluate user reputation, which affects the results of the access audit on the private blockchain. The higher a user’s reputation score is, the more benefits he/she can obtain in the transaction process. Finally, an identity-based proxy signcryption algorithm is proposed to help the intelligent management device with limited computing power obtain signcryption information in the transaction process to protect the transaction information. A system analysis showed that the secure transaction mechanism of the microgrid based on the hybrid blockchain boasts many security features, such as privacy, transparency, and imtamperability. The proposed reputation evaluation algorithm can objectively reflect all users’ behaviors through their reputation scores, and the identity-based proxy signcryption algorithm is practical.

User Reputation Calculation for Service-Oriented Environments

All the cloud based applications work on serviceoriented architectures and collaborate with multiple components from other services to execute discreet application logic. In this environment there are a lot of Web services facilitated to the customer to make the systems. As the potential of the same Web service will change with respect to users' needs. On an average a user will be heavily relied on tools to aid their activities on the internet vice versa the Service provider are also dependent on the users profile and what services are being used in the system. A User Reputation model offers a solution to the Service providers in supporting their service decision based on the User Profile. This model takes usage ratings as data and produces a personalised score. We suggest a new Cumulative separation on the basis of Tags and popularity estimation method and showcase its enhanced filtration ability.

Reputation System for Increased Engagement in Public Transport Oriented-Applications

Increasing user engagement is one of the biggest challenges when a new application is developed. An engaged user is one who finds a product valuable; highly engaged users generate profit. This study focuses on increasing user engagement in a transport application, via a user reputation score feature. The score is to reward application users and activity organisers, as well as to motivate beginners by offering a high reputation score in the first days of use. The algorithms are based on exponential and logarithmic functions, and were first tested on synthetic data. Real-world tests have shown that the algorithms behave as expected, but the COVID-19 pandemic created a disturbance which prevented any user from achieving the maximum score and many users from registering altogether. Data show positive results, although the real number of users is not sufficient to certify a correct behaviour. Further tests will be carried out when transport activities return to normal.

How do network attributes impact information virality in social networks?

Purpose Social media platforms play a key role in information propagation and there is a need to study the same. This study aims to explore the impact of the number of close communities (represented by cliques), the size of these close communities and its impact on information virality. Design/methodology/approach This study identified 6,786 users from over 11 million tweets for analysis using sentiment mining and network science methods. Inferential analysis has also been established by introducing multiple regression analysis and path analysis. Findings Sentiments of content did not have a significant impact on the information virality. However, there exists a stagewise development relationship between communities of close friends, user reputation and information propagation through virality. Research limitations/implications This paper contributes to the theory by introducing a stagewise progression model for influencers to manage and develop their social networks. Originality/value There is a gap in the existing literature on the role of the number and size of cliques on information propagation and virality. This study attempts to address this gap.

A Study on Information Technology Freelancer Matching with Exploiting Blockchain in Gig Economy

In this paper, we propose a freelancer matching of a recommended recruitment system in a situation in which the freelance type employment market defined by peer-to-peer transactions, mutual evaluation of freelancers and clients, time flexibility of service providers, and the use of service providers' tools and assets are expanding. In order to increase the reliability and accuracy of recommendation through reputation, we propose a reputation ranking technique for reputation system, which is a kind of personalized recommendation system, based on the blockchain technology. We propose a reputation system model suitable for recruitment matching service. We have aims to study the method of implicitly extracting user reputation information based on two factors suitable for word of mouth among information source reliability factors. In other words, this paper defines a method for automatically extracting two reliability factors of freelancers from past reputation information, and proposes a method for effectively predicting freelancer applicant’ reputation information using only the information of high-reliability evaluators.

Countermeasures of interest flooding attack in named data networking: A survey

Named data networking (NDN) is a typical representation and implementation of information-centric networking and serves as a basis for the next-generation Internet. However, any network architectures will face information security threats. An attack named interest flooding attack (IFA), which is evolved, has becomes a great threat for NDN in recent years. Attackers through insert numerous forged interest packets into an NDN network, making the cache memory of NDN router(s) overrun, interest packets for the intended users. To take a comprehensive understanding of recent IFA detection and mitigation approaches, in this paper, we compared nine typical approaches to resolving IFA attacks for NDN, which are interest traceback, token bucket with per interface fairness, satisfaction-based interest acceptance, satisfaction-based push back, disabling PIT exhaustion, interest flow control method based on user reputation and content name prefixes, interest flow balancing method focused on the number of requests on named data networking, cryptographic route token, Poseidon local, and Poseidon distributed techniques. In addition, we conducted a simulation using Poseidon, a commonly used IFA resolution approach. The results showed that Poseidon could resolve IFA issues effectively.

A Study of the Factors That Influence the Willingness of Users to Leave Comments on E-Commerce Platforms

This study aims to better understand the elements of e-commerce platforms that cause users to be more willing to leave behind comments. The authors summarize the literature of influencing factors and construct an influencing factor model for user comments. Self-expression questionnaires were used to provide data for structural equation modeling (SEM). They found that user reputation, perceived moral responsibility, and emotional tendency each exert a positive impact on the willingness to comment; that reciprocity psychology moderates the correlation between moral responsibility and commenting willingness; and that platform feedback moderates the correlation between economic reward and emotional tendency. This study helps merchants better understand when users are more likely to leave comments helpful to improving customer satisfaction levels.