Prediction of online social networks users' behaviors with a game theoretic approach

Zhan, F. Benjamin; Laines, Gabriella; Deniz, Sarah; Paliskara, Sahan; Ochoa, Irvin; Guerra, Idania; Tayeb, Shahab; Chiu, Carter; Pirouz, Matin; Ploutz, Elliott; Zhan, Justin; Gewali, Laxmi; Oh, Paul

doi:10.1109/ccnc.2018.8319308

Cited by 16 publications

(4 citation statements)

References 3 publications

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“…Instagram is considered to be one of the fastest-growing social media. As of April 2017, there were approximately 700 million users on Instagram (Zhan et al, 2018). A defining feature of Instagram is that it allows users to beautify their photos by applying a range of enhancement filters.…”

Section: Introductionmentioning

confidence: 99%

The Effects of Instagram Use, Social Comparison, and Self-Esteem on Social Anxiety: A Survey Study in Singapore

Jiang

Ngien

2020

Social Media + Society

138

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Social media have been growing rapidly during the past decade. However, it remains unclear whether social media make people more emotionally healthy or less. This study aims to explore the effect of Instagram use on individuals’ social anxiety. With a general basis of the three-stage model of interactive media use for health promotion, we conducted a cross-sectional online survey study ( N = 388) in the context of Singapore and empirically tested a mediation pathway linking Instagram use to social anxiety. The results indicated that Instagram use did not directly increase social anxiety. Instead, social comparison, a proximal outcome, and self-esteem, an intermediate outcome played mediating roles, supporting the complete mediation effects. This finding provides important theoretical and practical implications for the design of health campaigns and education in this digital era to enhance the positive effect of social media on health and emotional well-being.

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Section: Introductionmentioning

confidence: 99%

The Effects of Instagram Use, Social Comparison, and Self-Esteem on Social Anxiety: A Survey Study in Singapore

Jiang

Ngien

2020

Social Media + Society

138

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“…Such game-theoretic approaches have proved their merit in academic literature to analyze community online behaviors on social media platforms. [11][12][13][14][15].…”

Section: Proposed Methodologymentioning

confidence: 99%

The Accidental Checkmate: Understanding the Intent behind sharing Misinformation on Social Media

Agarwal¹

2020

Preprint

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The bloom of COVID19 has resulted in the explosion of ripple pollens which have severely affected the world community in the terms of their multi-axial impact. These pollens, despite being indistinguishable, have a varied set of characteristics in terms of their origin and contribution towards the overall declining homeostasis of human beings. The most prominent of these pollens are misinformation. Various studies have been conducted, performed, and stochastically replicated to build ML-based models to accurately detect misinformation and its variates on the common modalities of spread. However, the recent independent analysis conducted on the prior studies reveals how the current fact-checking systems fail and fall flat in fulfilling any practical demands that the misinfodemic of COVID19 brought for us. While the scientific community broadly accepts the pandemic-like resemblance of the rampant misinformation spread, we must also make sure that our response to the same is multi-faceted, interdisciplinary, and doesn’t stand restricted. As crucial it is to chart the features of misinformation spread, it is also important to understand why it spreads in the first place? Our paper deals with the latter question through a game-theory based approach. We implement a game with two social media users or players who aim at increasing their outreach on their social media handles whilst spreading misinformation knowingly. We take five independent parameters from 100 Twitter handles that have shared misinformation during the period of COVID19. Twitter was chosen as it is a prominent social media platform accredited to the major modality for misinformation spread. The outreach increment on the user’s Twitter handles were measured using various features provided by Twitter - number of comments, number of retweets, and number of likes. Later, using a computational neuroscientific approach, we map each of these features with the type of neural system they trigger in a person’s brain. This helps in understanding how misinformation whilst being used as an intentional decoy to increase outreach on social media, also, affects the human social cognition system eliciting pseudo-responses that weren’t intended otherwise leading to realizing possible neuroscientific correlation as to how spreading misinformation on social media intentionally/unintentionally becomes a strategic maneuver to increased reach and possibly a false sense of accomplishment.

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“…Game theory helps forecast and explain user behavior on social networks by looking at their incentives and motives. Zhan et al . (2018) show how game theory may be used to forecast user behavior on social networks and spot possible problems, such the propagation of false information or the creation of echo chambers.…”

Section: Introductionmentioning

confidence: 99%

Trading excess consumption certificates on the blockchain using the cooperative game theory

Ergün

2023

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PurposeThe purpose of this study is to propose a decentralized multi-party cross-trading scheme based on a certificate transaction mechanism for the transaction of excess consumption certificates (ECCs) of renewable energy. The aim is to address the problems associated with the existing centralized transaction mode and to promote the development of the green electricity industry.Design/methodology/approachThe proposed scheme involves calculating the quotation difference for the same type of certificate transaction based on the quotations of all users of both buyers and sellers. The transaction volume is then determined based on the order of quotation difference from large to small, and the total interests of cooperation are calculated. The nucleolus method is adopted to allocate the total interests to each member of the alliance and calculate the final transaction price. The blockchain technology is used for the transaction to achieve accurate traceability and efficient supervision, and a corresponding smart contract is designed and simulated in the Ethereum consortium chain.FindingsThe results of the simulation show the rationality and effectiveness of the proposed scheme. The decentralized multi-party cross-trading scheme can overcome the problems associated with the existing centralized transaction mode, such as low transaction efficiency, difficulty in obtaining the optimal transaction strategy and efficient supervision. The proposed scheme can promote the development of the green electricity industry by stimulating users' demand potential for green electricity.Originality/valueThe proposed scheme is original in its use of a certificate transaction mechanism to facilitate the trading of ECCs of renewable energy. The scheme adopts a decentralized multi-party cross-trading approach that overcomes the problems associated with the existing centralized transaction mode. The use of the nucleolus method for the allocation of total interests to each member of the alliance is also original. Finally, the use of blockchain technology for accurate traceability and efficient supervision of the transaction is an original contribution to the field.

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Prediction of online social networks users' behaviors with a game theoretic approach

Cited by 16 publications

References 3 publications

The Effects of Instagram Use, Social Comparison, and Self-Esteem on Social Anxiety: A Survey Study in Singapore

The Effects of Instagram Use, Social Comparison, and Self-Esteem on Social Anxiety: A Survey Study in Singapore

The Accidental Checkmate: Understanding the Intent behind sharing Misinformation on Social Media

Trading excess consumption certificates on the blockchain using the cooperative game theory

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