Blockchain in Social Networking

Poongodi, T.; Sujatha, R.; Sumathi, D.; Suresh, P.; Balamurugan, B.

doi:10.1002/9781119621201.ch4

Cited by 20 publications

(4 citation statements)

References 34 publications

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“…The world in the last decade has seen several technological advancements such as electronic commerce, digital payments and the internet of things (IoT). Reflections of these developments can be seen in the ways people interact and the way they exchange money [ 1 ]. Owing to the constant trend of change in the last two decades, shifting from paper to virtual currency, a new form of currency, i.e.…”

Section: Introductionmentioning

confidence: 99%

The adoption of cryptocurrency as a disruptive force: Deep learning-based dual stage structural equation modelling and artificial neural network analysis

et al. 2021

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In recent years, the growth of cryptocurrency has undergone an enormous increase in cryptocurrency markets all around the world. Sadly, only insignificant heed has been paid to the unveiling of determinants of cryptocurrency adoption globally, particularly in emerging markets like Malaysia. The purpose of the study is to examine whether the application of deep learning-based dual-stage Partial Least Square-Structural Equation Modelling (PLS-SEM) & Artificial Neural Network (ANN) analysis enable better in-depth research results as compared to single-step PLS-SEM approach and to excavate factors which can predict behavioural intention to adopt cryptocurrency. The Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model were extended with the inclusion of trust and personnel innovativeness. The model was further validated by introducing a new path model compared to the original UTAUT2 model and the moderating role of personal innovativeness between performance expectancy and price value, with a sample of 314 respondents. Contrary to previous technology adoption studies that used PLS-SEM & ANN as single-stage analysis, this study further enhanced the analysis by applying a deep learning-based dual-stage PLS-SEM and ANN method. The application of deep learning-based dual-stage PLS-SEM & ANN analysis is a novel methodological approach, detecting both linear and non-linear associations among constructs. At the same time, it is regarded as a superior statistical approach as compared to traditional hybrid shallow SEM & ANN single-stage analysis. Also, sensitivity analysis provides normalised importance using multi-layer perceptron with the feed-forward-back-propagation algorithm. Furthermore, the deep learning-based dual-stage PLS-SEM & ANN revealed that trust proved to be the strongest predictor in driving user intention. The introduction of this new methodology and the theoretical contribution opens the vistas of the extant body of knowledge in technology-adoption related literature. This study also provides theoretical, practical and methodological contributions.

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Section: Introductionmentioning

confidence: 99%

The adoption of cryptocurrency as a disruptive force: Deep learning-based dual stage structural equation modelling and artificial neural network analysis

et al. 2021

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“…Additionally, blockchain's immutability safeguards against identity theft, providing users with greater control over their personal information. In essence, blockchain serves as a foundational layer for building secure, transparent, and resilient online social networks [21].…”

Section: Blockchain Solutions Of Osn's Security Attacksmentioning

confidence: 99%

Comparative Analysis of Blockchain Platforms for Security Enhancement in Online Social Networks

Mohammed,

Al-Aaraji,

Al-Saleh

2024

ISI

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As people's lives become more reliant on Online Social Networks (OSN), ensuring the security and protection of their personal information has become critical. These platforms expose users to possible security flaws and privacy violations, like identity theft, even while they provide a variety of tools for communication and interest sharing. This paper is a survey paper that examines the security concerns of online social networks, such as Sybil attacks, in which phony identities threaten integrity; identity theft, which exploits personal information; and de-anonymization, which exposes user identities. Furthermore, it provides a thorough examination of Blockchain technology as a dependable solution to these security issues. Furthermore, this study finds the best secure solutions by evaluating various Blockchain platforms such as Steem, Hive, Sapien, and Ethereum. The findings reveal that Blockchain technology provides a robust and effective security framework for safeguarding online social networks, offering enhanced protection against various OSN attacks.

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“…The developers train these NLP algorithms to identify patterns in the language used in promotional content to determine unverifiable or inaccurate information, such as exaggerated or falsified information in sensational headlines [79]. In addition, the NLP can help analyze the tone and sentiment of the disseminated marketing content, thus identifying any misleading news [80,81]. For example, in an advertisement where a product is said to "instantly cure all ailments," NLP algorithms can identify this as a false claim if the product can't achieve these promises.…”

Section: Artificial Intelligence (Ai)mentioning

confidence: 99%

Fake News in Marketing

Silva¹,

Rosário²,

Gestoso³

et al. 2023

Preprint

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Fake news was conventionally assumed to mean fabricated information published in newspapers and other mass media. It was mostly done to increase the paper's sales and was unlikely to have long-term impacts on society. Fake news in marketing concerns intentionally delivering false or misleading information regarding a product or service to influence consumer behavior. Despite the severity of these impacts, we noted that there is very little scientific research on fake news in marketing and consumer behavior. This systematic literature review (LRSB) aims to bridge this knowledge gap by searching and analysing relevant publications on "fake news in marketing" and synthesising data from 117 relevant studies, providing a framework for marketers and business leaders to reduce the spread and impact of online misinformation. The main highlights identify that the implementation and use of social media, shaping a presence on the internet, diffusion, and consumption of fake news have become a serious challenge and a dominant problem in the marketing sector, especially with the growth of digital marketing. Strategically, fake news spread can be categorized into various types, and the use of these tactics can produce short-term benefits such as increased engagement and instant sales, but they can also have severe long-term costs such as reputational damage, loss of revenues and market share, and discouraged investors and shareholders.

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Blockchain in Social Networking

Cited by 20 publications

References 34 publications

The adoption of cryptocurrency as a disruptive force: Deep learning-based dual stage structural equation modelling and artificial neural network analysis

The adoption of cryptocurrency as a disruptive force: Deep learning-based dual stage structural equation modelling and artificial neural network analysis

Comparative Analysis of Blockchain Platforms for Security Enhancement in Online Social Networks

Fake News in Marketing

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