ProBlock: a novel approach for fake news detection

Sengupta, Eishvak; Nagpal, Renuka; Mehrotra, Deepti; Srivastava, Gautam

doi:10.1007/s10586-021-03361-w

Cited by 17 publications

(9 citation statements)

References 38 publications

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“…Finally, we found that the presence of a call for action is associated with false rumors. Previous studies have also shown that calling for counteraction to create chaos could be the purpose of some rumors (83,84). Whether a rumor contains a call to retweet the information or a call to take counteraction against governmental prevention and curative policies may present an obstacle to implementing these policies.…”

Section: Discussionmentioning

confidence: 99%

Content characteristics predict the putative authenticity of COVID-19 rumors

Zhao

Kang

2022

Front. Public Health

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Rumors regarding COVID-19 have been prevalent on the Internet and affect the control of the COVID-19 pandemic. Using 1,296 COVID-19 rumors collected from an online platform (piyao.org.cn) in China, we found measurable differences in the content characteristics between true and false rumors. We revealed that the length of a rumor's headline is negatively related to the probability of a rumor being true [odds ratio (OR) = 0.37, 95% CI (0.30, 0.44)]. In contrast, the length of a rumor's statement is positively related to this probability [OR = 1.11, 95% CI (1.09, 1.13)]. In addition, we found that a rumor is more likely to be true if it contains concrete places [OR = 20.83, 95% CI (9.60, 48.98)] and it specifies the date or time of events [OR = 22.31, 95% CI (9.63, 57.92)]. The rumor is also likely to be true when it does not evoke positive or negative emotions [OR = 0.15, 95% CI (0.08, 0.29)] and does not include a call for action [OR = 0.06, 95% CI (0.02, 0.12)]. By contrast, the presence of source cues [OR = 0.64, 95% CI (0.31, 1.28)] and visuals [OR = 1.41, 95% CI (0.53, 3.73)] is related to this probability with limited significance. Our findings provide some clues for identifying COVID-19 rumors using their content characteristics.

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Section: Discussionmentioning

confidence: 99%

Content characteristics predict the putative authenticity of COVID-19 rumors

Zhao

Kang

2022

Front. Public Health

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“…Their experiments mainly focus on the feasibility of the average response times of the system rather than how and how well the system identifies fake news. In [50], Sengupta et al propose ProBlock, which is a secure voting system with an emphasis on reviewer privacy.…”

Section: Related Workmentioning

confidence: 99%

Modeling and Mitigating Online Misinformation: a Suggested Blockchain Approach

Yılmaz¹,

Ulusoy²

2023

Preprint

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Misinformation propagation in online social networks has become an increasingly challenging problem. Although many studies exist to solve the problem computationally, a permanent and robust solution is yet to be discovered. In this study, we propose and demonstrate the effectiveness of a blockchain-machine learning hybrid approach for addressing the issue of misinformation in a crowdsourced environment. First, we motivate the use of blockchain for this problem by finding the crucial parts contributing to the dissemination of misinformation and how blockchain can be useful, respectively. Second, we propose a method that combines the wisdom of the crowd with a behavioral classifier to classify the news stories in terms of their truthfulness while reducing the effects of the actions performed by malicious users. We conduct experiments and simulations under different scenarios and attacks to assess the performance of this approach. Finally, we provide a case study involving a comparison with an existing approach using Twitter Birdwatch data. Our results suggest that this solution holds promise and warrants further investigation. CCS Concepts: • Computing methodologies → Neural networks; • Computer systems organization → Dependable and fault-tolerant systems and networks; • Information systems → Crowdsourcing.

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“…The centralized social networks have problems such as data privacy leakage and unrestricted spreading of fake news, which greatly violate user privacy security and affect their ability to discern information ( Cadwalladr & Graham-Harrison, 2018 ). The unique decentralization, consensus mechanism, traceability and other features of blockchain can achieve a trustless and self-managed data interaction environment, which breaks through the technical bottleneck of existing social network management ( Hisseine, Chen & Yang , 2022 ; Sengupta et al , 2021 ). With the combination of blockchain technology and social networks, several social media platforms have emerged, such as Steemit , Lit , HyperSpace , Sapien , SocialX , FORESTING and Minds ( Guidi, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Recognition of opinion leaders in blockchain-based social networks by structural information and content contribution

Wang,

Tan,

Shi

2023

PeerJ Computer Science

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Exploring the influence of social network users in the blockchain environment and identifying opinion leaders can help understand the information dissemination characteristics of blockchain social networks, direct the discovery of quality content, and avoid the spread of rumors. Members of blockchain-based social networks are given new responsibilities by token awards and consensus voting, which alters how users connect to the network and engage with one another. Based on blockchain theory and the relevant theories of opinion leaders in social networks, this article combines structural information and content contributions to identify opinion leaders. Firstly, user influence indicators are defined from the perspective of network structure and behavioral characteristics of user contributions. Then, ECWM is constructed, which combines the entropy weight method and the criteria importance through intercriteria correlation (CRITIC) weighting method to address the correlation and diversity among indicators. Furthermore, an improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), called ECWM-TOPSIS, is proposed to identify opinion leaders in blockchain social networks. Moreover, to verify the effectiveness of the method, we conducted a comparative analysis of the proposed algorithm on the blockchain social platform Steemit by using two different methods (voting score and forwarding rate). The results show that ECWM-TOPSIS produces significantly higher performance than other methods for all selected top N opinion leaders.

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ProBlock: a novel approach for fake news detection

Cited by 17 publications

References 38 publications

Content characteristics predict the putative authenticity of COVID-19 rumors

Content characteristics predict the putative authenticity of COVID-19 rumors

Modeling and Mitigating Online Misinformation: a Suggested Blockchain Approach

Recognition of opinion leaders in blockchain-based social networks by structural information and content contribution

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