Measuring Reputation and Influence in Online Social Networks: A Systematic Literature Review

Al-Yazidi, Sami; Berri, Jawad; Al‐Qurishi, Muhammad; Al-Alrubaian, Majed

doi:10.1109/access.2020.2999033

Cited by 20 publications

(12 citation statements)

References 154 publications

(214 reference statements)

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“…The analysis of reputation mechanisms in online markets can provide insights into the efficiency of regulatory practices and could be used to test hypotheses on a massive scale (e.g. [260][261][262][263][264]). Historical data and field observations (e.g.…”

Section: Discussionmentioning

confidence: 99%

Networks of reliable reputations and cooperation: a review

Takács

Gross

Testori

et al. 2021

Phil. Trans. R. Soc. B

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Reputation has been shown to provide an informal solution to the problem of cooperation in human societies. After reviewing models that connect reputations and cooperation, we address how reputation results from information exchange embedded in a social network that changes endogenously itself. Theoretical studies highlight that network topologies have different effects on the extent of cooperation, since they can foster or hinder the flow of reputational information. Subsequently, we review models and empirical studies that intend to grasp the coevolution of reputations, cooperation and social networks. We identify open questions in the literature concerning how networks affect the accuracy of reputations, the honesty of shared information and the spread of reputational information. Certain network topologies may facilitate biased beliefs and intergroup competition or in-group identity formation that could lead to high cooperation within but conflicts between different subgroups of a network. Our review covers theoretical, experimental and field studies across various disciplines that target these questions and could explain how the dynamics of interactions and reputations help or prevent the establishment and sustainability of cooperation in small- and large-scale societies. This article is part of the theme issue ‘The language of cooperation: reputation and honest signalling’.

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Section: Discussionmentioning

confidence: 99%

Networks of reliable reputations and cooperation: a review

Takács

Gross

Testori

et al. 2021

Phil. Trans. R. Soc. B

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“…A similar study to determine influential users in OSN was presented by Ishfaq et al [43] and Al-Garadi [4]. A recent review published in 2020 by Al-Yazidi et al [5] presented techniques used to measure both the reputation and influence of users in OSN. The paper discusses features that are important to measure the reputation and influence, importance of measuring reputation and influence and finally the approaches that can be used to measure the reputation and influence.…”

Section: Introductionmentioning

confidence: 90%

Topic-based influential user detection: a survey

Panchendrarajan

Saxena

2022

Appl Intell

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Online Social networks have become an easy means of communication for users to share their opinion on various topics, including breaking news, public events, and products. The content posted by a user can influence or affect other users, and the users who could influence or affect a high number of users are called influential users. Identifying such influential users has a wide range of applications in the field of marketing, including product advertisement, recommendation, and brand evaluation. However, the users’ influence varies in different topics, and hence a tremendous interest has been shown towards identifying topic-based influential users over the past few years. Topic-level information in the content posted by the users can be used in various stages of the topic-based influential user detection (IUD) problem, including data gathering, construction of influence network, quantifying the influence between two users, and analyzing the impact of the detected influential user. This has opened up a wide range of opportunities to utilize the existing techniques to model and analyze the topic-level influence in online social networks. In this paper, we perform a comprehensive study of existing techniques used to infer the topic-based influential users in online social networks. We present a detailed review of these approaches in a taxonomy while highlighting the challenges and limitations associated with each technique. Moreover, we perform a detailed study of different evaluation techniques used in the literature to overcome the challenges that arise in evaluating topic-based IUD approaches. Furthermore, closely related research topics and open research questions in topic-based IUD are discussed to provide a deep understanding of the literature and future directions.

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“…For this reason, the present systematic review aims to identify gaps in research related to CARSs for social networks and provides a comprehensive review of studies published from 2015 till 2020. Moreover, the systematic review covers broader questions than single empirical studies can do [29].…”

Section: Review Methodsmentioning

confidence: 99%

Context-Aware Recommender Systems for Social Networks: Review, Challenges and Opportunities

Suhaim

Berri

2021

IEEE Access

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Context-aware recommender systems dedicated to online social networks experienced noticeable growth in the last few years. This has led to more research being done in this area stimulated by the omnipresence of smartphones and the latest web technologies. These systems are able to detect specific user needs and adapt recommendations to actual user context. In this research, we present a comprehensive review of context-aware recommender systems developed for social networks. For this purpose, we used a systematic literature review methodology which clearly defined the scope, the objective, the timeframe, the methods, and the tools to undertake this research. Our focus is to investigate approaches and techniques used in the development of context-aware recommender systems for social networks and identify the research gaps, challenges, and opportunities in this field. In order to have a clear vision of the research potential in the field, we considered research articles published between 2015 and 2020 and used a research portal giving access to major scientific research databases. Primary research articles selected are reviewed and the recommendation process is analyzed to identify the approach, the techniques, and the context elements employed in the development of the recommendation systems. The paper presents the detail of the review study, provides a synthesis of the results, proposes an evaluation based on measurable evaluation tools developed in this study, and advocates future research and development pathways in this interesting field.

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Measuring Reputation and Influence in Online Social Networks: A Systematic Literature Review

Cited by 20 publications

References 154 publications

Networks of reliable reputations and cooperation: a review

Networks of reliable reputations and cooperation: a review

Topic-based influential user detection: a survey

Context-Aware Recommender Systems for Social Networks: Review, Challenges and Opportunities

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