Online Social Network Model Based on Local Preferential Attachment

In this paper, we use the edge weights preferential attachment mechanism to build a new local-world evolutionary model for weighted networks. It is different from previous papers that the local-world of our model consists of edges instead of nodes. Each time step, we connect a new node to two existing nodes in the local-world through the edge weights preferential selection. Theoretical analysis and numerical simulations show that the scale of the local-world affect on the weight distribution, the strength distribution and the degree distribution. We give the simulations about the clustering coefficient and the dynamics of infectious diseases spreading. The weight dynamics of our network model can portray the structure of realistic networks such as neural network of the nematode C. elegans and Online Social Network.

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An Online Social Network model through Twitter to build a social perception variable to measure the violence in Mexico

Revista Perspectiva Empresarial ◽

10.16967/23898186.665 ◽

2020 ◽

Vol 7 (2-1) ◽

pp. 6-18

Author(s):

Manuel Suárez Gutiérrez ◽

José Luis Sánchez Cervantes ◽

Mario Andrés Paredes Valverde

Keyword(s):

Social Network ◽

Network Model ◽

Social Perception ◽

Online Social Network ◽

Time Lapse ◽

High Impact ◽

Specific Time

This paper describes the methodology and the model that used in Twitter to create an indicator that allows us to denote a social perception about violence, a topic of high impact in Mexico. We investigated and validated the keywords that Mexicans used related to this topic, in a specific time-lapse defined by the researchers. We implemented two analysis levels, the first one relative to the sum of tweets, and the second one with a rate of total tweets per 100,000 inhabitan

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Online social network model with renewal and accelerated growth

The Journal of China Universities of Posts and Telecommunications ◽

10.1016/s1005-8885(14)60316-2 ◽

2014 ◽

Vol 21 (4) ◽

pp. 54-63

Author(s):

Zhe WU ◽

Yu-chun GUO ◽

Chang-jia CHEN

Keyword(s):

Social Network ◽

Network Model ◽

Online Social Network ◽

Accelerated Growth

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Ensemble method: Community detection based on game theory

International Journal of Modern Physics B ◽

10.1142/s0217979214502117 ◽

2014 ◽

Vol 28 (30) ◽

pp. 1450211 ◽

Cited By ~ 4

Author(s):

Xia Zhang ◽

Zhengyou Xia ◽

Shengwu Xu ◽

J. D. Wang

Keyword(s):

Game Theory ◽

Social Network ◽

Community Detection ◽

Online Social Network ◽

Cost Effective ◽

Detection Algorithm ◽

Research Area ◽

Detection Model ◽

Model Based ◽

Active Research

Timely and cost-effective analytics over social network has emerged as a key ingredient for success in many businesses and government endeavors. Community detection is an active research area of relevance to analyze online social network. The problem of selecting a particular community detection algorithm is crucial if the aim is to unveil the community structure of a network. The choice of a given methodology could affect the outcome of the experiments because different algorithms have different advantages and depend on tuning specific parameters. In this paper, we propose a community division model based on the notion of game theory, which can combine advantages of previous algorithms effectively to get a better community classification result. By making experiments on some standard dataset, it verifies that our community detection model based on game theory is valid and better.

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Adopting, Networking, and Communicating on Twitter

Social Science Computer Review ◽

10.1177/0894439316672826 ◽

2016 ◽

Vol 35 (6) ◽

pp. 698-712 ◽

Cited By ~ 4

Author(s):

Maurice Vergeer

Keyword(s):

Social Network ◽

South Korea ◽

Cultural Differences ◽

Political Communication ◽

Social Relations ◽

Preferential Attachment ◽

Online Social Network ◽

Mass Medium ◽

Political Candidates ◽

Collectivistic Culture

Twitter is one of the most popular online social network platforms for political communication. This study explains how political candidates in five countries increase their online popularity and visibility by their behavior on Twitter. Also, the study focuses on cultural differences in online social relations by comparing political candidates in five countries in the East and West: South Korea, Japan, United Kingdom, Canada, and the Netherlands. Findings show that signing up to Twitter as early as possible increases one’s online popularity as predicted by the process of preferential attachment. Candidates actively following citizens and sending undirected tweets also increases the group of followers. This doesn’t apply however to conversational tweets, which decreases the number of a candidate’s followers slightly. South Korea, having a collectivistic culture, shows higher levels of reciprocity on Twitter, although this does not increase the group of followers. In other countries, including collectivistic Japan, candidates reciprocate less frequently with citizens, effectively using Twitter more as a mass medium for broadcasting.

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