scholarly journals A framework for information dissemination in social networks using Hawkes processes

2016 ◽  
Vol 103 ◽  
pp. 86-107 ◽  
Author(s):  
J.C. Louzada Pinto ◽  
T. Chahed ◽  
E. Altman
Keyword(s):  
Social Networks ◽  
Information Dissemination ◽  
Hawkes Processes

The model of information dissemination on social networks under epidemic-related panic

2021 ◽  
Author(s):  
Fuzhong Nian ◽  
Xin Guo ◽  
JinZhou Li
Keyword(s):  
Social Networks ◽  
Individual Differences ◽  
Infection Rate ◽  
Information Dissemination ◽  
Self Regulation ◽  
Cumulative Effect ◽  
Herd Effect ◽  
Collective Wisdom ◽  
Leading Role

Inspired by infectious disease dynamics and modern psychology, this paper aims at constructing a multi-dimensional function to get the model of information dissemination on social networks under epidemic-related panic base on the characteristics of individual differences and global characteristics, like emotional cumulative effect, herd effect, time-sensitive decline effect, cognitive level, intimacy, personal influence, etc. The results show that the psychological effect has a significant effect on the increase of the spread of panic news; When netizens are in an emotional atmosphere, their emotional self-regulation ability is limited; when the infection rate is relatively low, the characteristics of individual differences play a leading role in affecting the spreading process. When the infection rate is high enough, the herd effect and emotional cumulative effect play a major role in promoting information dissemination; In a society with a higher rate of emotional contact, it is easier to form a kind of collective wisdom, which can help the collective quickly identify rumors. Moreover, in this kind of society, the role of opinion leaders is limited, and timely refutation of rumors can significantly reduce the spread of panic news.

Mechanism analysis of competitive information asynchronous dissemination on social networks

2019 ◽  
Vol 30 (11) ◽  
pp. 1950094 ◽  
Author(s):  
Jianye Yu ◽  
Junjie Lv ◽  
Yuanzhuo Wang ◽  
Jingyuan Li
Keyword(s):  
Social Networks ◽  
Information Diffusion ◽  
Information Dissemination ◽  
Evolutionary Game ◽  
Real Data ◽  
Game Model ◽  
Mechanism Analysis ◽  
Sina Weibo ◽  
Human Behaviors ◽  
Information Spread

Information dissemination groups, especially those disseminating the same kind of information such as advertising, product promotion, etc., compete with each other when their information spread on social networks. Most of the existing methods analyze the dissemination mechanism mainly upon the information itself without considering human characteristics, e.g. relation networks, cooperation/defection, etc. In this paper, we introduce a framework of social evolutionary game (SEG) to investigate the influence of human behaviors in competitive information dissemination. Coordination game is applied to represent human behaviors in the competition of asynchronous information diffusion. We perform a series of simulations through a specific game model to analyze the mechanism and factors of information diffusion, and show that when the benefits of competitive information is around 1.2 times of the original one, it can compensate the loss of reputation caused by the change of strategy. Furthermore, through experiments on a dataset of two films on Sina Weibo, we described the mechanism of competition evolution over real data of social network, and validated the effectiveness of our model.

scholarly journals Evolution Model of Spatial Interaction Network in Online Social Networking Services

Entropy ◽  
2019 ◽  
Vol 21 (4) ◽  
pp. 434
Author(s):  
Jian Dong ◽  
Bin Chen ◽  
Pengfei Zhang ◽  
Chuan Ai ◽  
Fang Zhang ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Networking ◽  
Information Dissemination ◽  
Preferential Attachment ◽  
Spatial Interaction ◽  
Interaction Network ◽  
Evolution Model ◽  
Social Networking Services ◽  
The City ◽  
Real City

The development of online social networking services provides a rich source of data of social networks including geospatial information. More and more research has shown that geographical space is an important factor in the interactions of users in social networks. In this paper, we construct the spatial interaction network from the city level, which is called the city interaction network, and study the evolution mechanism of the city interaction network formed in the process of information dissemination in social networks. A network evolution model for interactions among cities is established. The evolution model consists of two core processes: the edge arrival and the preferential attachment of the edge. The edge arrival model arranges the arrival time of each edge; the model of preferential attachment of the edge determines the source node and the target node of each arriving edge. Six preferential attachment models (Random-Random, Random-Degree, Degree-Random, Geographical distance, Degree-Degree, Degree-Degree-Geographical distance) are built, and the maximum likelihood approach is used to do the comparison. We find that the degree of the node and the geographic distance of the edge are the key factors affecting the evolution of the city interaction network. Finally, the evolution experiments using the optimal model DDG are conducted, and the experiment results are compared with the real city interaction network extracted from the information dissemination data of the WeChat web page. The results indicate that the model can not only capture the attributes of the real city interaction network, but also reflect the actual characteristics of the interactions among cities.

The Unified Model for Acceptance and Use of Health Information on Online Social Networks

2016 ◽  
Vol 7 (1) ◽  
pp. 31-47 ◽  
Author(s):  
Waransanang Boontarig ◽  
Borworn Papasratorn ◽  
Wichian Chutimaskul
Keyword(s):  
Social Networks ◽  
Health Information ◽  
Online Social Networks ◽  
Information Dissemination ◽  
Source Credibility ◽  
Unified Model ◽  
Dissemination Strategy ◽  
Facilitating Conditions ◽  
Emotional Value ◽  
Beliefs And Attitudes

Online social networks provide a novel opportunity to improve public health through effective health information dissemination. Developing a dissemination strategy, however, requires an understanding of individuals' beliefs and attitudes about using both the technology and information. Previous research has focused primarily on either technology adoption or information adoption behaviors. This study aims to bridge the gap by developing a unified model of acceptance and use of information technology for predicting intention to use health information through online social networks. Empirical results show that Performance Expectancy, Facilitating Conditions, Perceived Emotional Value, Trust, Relevance, Accuracy, Understandability, and Source Credibility influence the adoption behavior. Also, individuals tend to accept health information regardless of their attitudes toward the communication channel.

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