Finding influential users in microblogs: state-of-the-art methods and open research challenges

Ishfaq, Umar; Khan, Hikmat Ullah; Iqbal, Shahid; Alghobiri, Mohammed

doi:10.1080/0144929x.2021.1915384

Cited by 11 publications

(3 citation statements)

References 220 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We can utilize or combine SNA metrics to exploit OSN to support decision-making, as it can provide a deeper understanding on how network entities (its users, their posts and embedded concepts) interact all together, as well as to evidence properties of OSN interactions, using SNA metrics. Such metrics allow to gain insights on activity, control information flow, importance, power, prestige (status, popularity) and proximity within a network, as we summarize in Table 1 (Wasserman and Faust 1994;Page et al 1999;Arif 2015;Saint-Charles and Mongeau 2018;Ruas et al 2019;Ishfaq et al 2021):…”

Section: Using Social Network Analysismentioning

confidence: 99%

Getting decision support from context-specific online social networks: a case study

Freire

Antunes

Costa

2022

Soc. Netw. Anal. Min.

View full text Add to dashboard Cite

The combination between online social networks (OSN) and decision processes provides a favorable social data analysis paradigm for efficient decision support and business-processes integration. This paper presents a framework for handling OSN's contents, providing a simpler and effective approach for information retrieval and processing. The objective is to address a decision-making problem, by using that framework to extract, process, structure and analyze the OSN's data. The decision process is not only guided by OSN data, but also by social network analysis methodology and is entirely based on the communications among social media users. Our framework combines two different, though complementary, perspectives: the analysis of the interactions among users and the semantic analysis of their discourses. In addition, it aims to bridge technology and manual-based approaches, thus enhancing the possibilities for making a better use of an OSN, using free-available software. The case study, herein, aims to estimate customers' requests, solely based on their Facebook posts, showing that the unstructured data of the web's discourse can be used to support this kind of decision processes.

show abstract

Section: Using Social Network Analysismentioning

confidence: 99%

Getting decision support from context-specific online social networks: a case study

Freire

Antunes

Costa

2022

Soc. Netw. Anal. Min.

View full text Add to dashboard Cite

show abstract

“…With the prevalence of micro-blogging applications Influence Analysis has been an active area of research over the past decade. A recent and thorough survey on finding influencers is given by Ishfaq et al (2022). To facilitate background understanding we classify below the literature according to their relevancy within this work.…”

Section: Related Workmentioning

confidence: 99%

Social network analytics and visualization: Dynamic topic‐based influence analysis in evolving micro‐blogs

et al. 2022

View full text Add to dashboard Cite

Influence Analysis is one of the well‐known areas of Social Network Analysis. However, discovering influencers from micro‐blog networks based on topics has gained recent popularity due to its specificity. Besides, these data networks are massive, continuous and evolving. Therefore, to address the above challenges we propose a dynamic framework for topic modelling and identifying influencers in the same process. It incorporates dynamic sampling, community detection and network statistics over graph data stream from a social media activity management application. Further, we compare the graph measures against each other empirically and observe that there is no evidence of correlation between the sets of users having large number of friends and the users whose posts achieve high acceptance (i.e., highly liked, commented and shared posts). Therefore, we propose a novel approach that incorporates a user's reachability and also acceptability by other users. Consequently, we improve on graph metrics by including a dynamic acceptance score (integrating content quality with network structure) for ranking influencers in micro‐blogs. Additionally, we analysed the topic clusters' structure and quality with empirical experiments and visualization.

show abstract

“…Later in 2019, a methodological review of detecting opinion leaders in social networks was presented by Bamakan et al [10]. 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.…”

Section: Introductionmentioning

confidence: 99%

Topic-based influential user detection: a survey

Panchendrarajan

Saxena

2022

Appl Intell

View full text Add to dashboard Cite

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.

show abstract

Finding influential users in microblogs: state-of-the-art methods and open research challenges

Cited by 11 publications

References 220 publications

Getting decision support from context-specific online social networks: a case study

Getting decision support from context-specific online social networks: a case study

Social network analytics and visualization: Dynamic topic‐based influence analysis in evolving micro‐blogs

Topic-based influential user detection: a survey

Contact Info

Product

Resources

About