scholarly journals Influences of Influential Users

2014 ◽  
Author(s):  
Jing Ren ◽  
Zhiyong Cheng ◽  
Jialie Shen ◽  
Feida Zhu
Keyword(s):  
Influential Users

Predicting Influential Users in Online Social Network Groups

2021 ◽  
Vol 15 (3) ◽  
pp. 1-50
Author(s):  
Andrea De Salve ◽  
Paolo Mori ◽  
Barbara Guidi ◽  
Laura Ricci ◽  
Roberto Di Pietro
Keyword(s):  
Online Social Networks ◽  
Online Social Network ◽  
Research Perspective ◽  
Ex Post ◽  
Time Period ◽  
Future Time Period ◽  
Academic Researchers ◽  
Influential Users ◽  
Analytical Tools ◽  
Share Information

The widespread adoption of Online Social Networks (OSNs), the ever-increasing amount of information produced by their users, and the corresponding capacity to influence markets, politics, and society, have led both industrial and academic researchers to focus on how such systems could be influenced . While previous work has mainly focused on measuring current influential users, contents, or pages on the overall OSNs, the problem of predicting influencers in OSNs has remained relatively unexplored from a research perspective. Indeed, one of the main characteristics of OSNs is the ability of users to create different groups types, as well as to join groups defined by other users, in order to share information and opinions. In this article, we formulate the Influencers Prediction problem in the context of groups created in OSNs, and we define a general framework and an effective methodology to predict which users will be able to influence the behavior of the other ones in a future time period, based on historical interactions that occurred within the group. Our contribution, while rooted in solid rationale and established analytical tools, is also supported by an extensive experimental campaign. We investigate the accuracy of the predictions collecting data concerning the interactions among about 800,000 users from 18 Facebook groups belonging to different categories (i.e., News, Education, Sport, Entertainment, and Work). The achieved results show the quality and viability of our approach. For instance, we are able to predict, on average, for each group, around a third of what an ex-post analysis will show being the 10 most influential members of that group. While our contribution is interesting on its own and—to the best of our knowledge—unique, it is worth noticing that it also paves the way for further research in this field.

Determining Influential Users in Internet Social Networks

2009 ◽  
Author(s):  
Michael Trusov ◽  
Anand V. Bodapati ◽  
Randolph E. Bucklin
Keyword(s):  
Social Networks ◽  
Influential Users

Profiling the Users of High Influence on Social Media in the Context of Public Events

2021 ◽  
Vol 32 (2) ◽  
pp. 36-49
Author(s):  
Lu An ◽  
Junyang Hu ◽  
Manting Xu ◽  
Gang Li ◽  
Chuanming Yu
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Emergency Management ◽  
Emotional Support ◽  
Opinion Leader ◽  
Negative Effects ◽  
The Public ◽  
Public Events ◽  
Social Media Platforms ◽  
Influential Users

The highly influential users on social media platforms may lead the public opinion about public events and have positive or negative effects on the later evolution of events. Identifying highly influential users on social media is of great significance for the management of public opinion in the context of public events. In this study, the highly influential users of social media are divided into three types (i.e., topic initiator, opinion leader, and opinion reverser). A method of profiling highly influential users is proposed based on topic consistency and emotional support. The event of “Jiankui He Editing the Infants' Genes” was investigated. The three types of users were identified, and their opinion differences and dynamic evolution were revealed. The comprehensive profiles of highly influential users were constructed. The findings can help emergency management departments master the focus of attention and emotional attitudes of the key users and provide the method and data support for opinion management and decision-making of public events.

scholarly journals Finding influential users of web event in social media

2018 ◽  
Vol 31 (3) ◽  
pp. e5029 ◽  
Author(s):  
Qichen Ma ◽  
Xiangfeng Luo ◽  
Hai Zhuge
Keyword(s):  
Social Media ◽  
Influential Users

scholarly journals Influence Maximization in Social Networks using Deterministic Crowding Algorithm

2019 ◽  
Vol 8 (11) ◽  
pp. 4258-4265
Keyword(s):  
Social Network ◽  
Information Diffusion ◽  
Influence Maximization ◽  
Maximization Problem ◽  
Linear Threshold ◽  
The Social ◽  
Spread Of Influence ◽  
Influential Users ◽  
High Influence ◽  
Influence Maximization Problem

In a social network the individuals connected to one another become influenced by one another, while some are more influential than others and able to direct groups of individuals towards a move, an idea and an entity. These individuals are named influential users. Attempt is made by the social network researchers to identify such individuals because by changing their behaviors and ideologies due to communications and the high influence on one another would change many others' behaviors and ideologies in a given community. In information diffusion models, at all stages, individuals are influenced by their neighboring people. These influences and impressions thereof are constructive in an information diffusion process. In the Influence Maximization problem, the goal is to finding a subset of individuals in a social network such that by activating them, the spread of influence is maximized. In this work a new algorithm is presented to identify most influential users under the linear threshold diffusion model. It uses explicit multimodal evolutionary algorithms. Four different datasets are used to evaluate the proposed method. The results show that the precision of our method in average is improved 4.8% compare to best known previous works.

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