scholarly journals Improved SIR Advertising Spreading Model and Its Effectiveness in Social Network

2018 ◽  
Vol 129 ◽  
pp. 215-218 ◽  
Author(s):  
Yi Jing ◽  
Liu Peiyu ◽  
Tang Xiaobing ◽  
Liu Wenfeng
Keyword(s):  
Social Network ◽  
Spreading Model

scholarly journals An information spreading model based on relative weight in social network

2015 ◽  
Vol 64 (5) ◽  
pp. 050501
Author(s):  
Wang Jin-Long ◽  
Liu Fang-Ai ◽  
Zhu Zhen-Fang
Keyword(s):  
Social Network ◽  
Relative Weight ◽  
Spreading Model ◽  
Model Based ◽  
Information Spreading

How the node’s vital and tie strength effect rumor spreading on social network

2019 ◽  
Vol 30 (06) ◽  
pp. 1950046
Author(s):  
Liang’an Huo ◽  
Tingting Lin ◽  
Chen Liu ◽  
Xing Fang
Keyword(s):  
Social Network ◽  
Complex Networks ◽  
Numerical Solutions ◽  
Spreading Rate ◽  
Tuning Parameter ◽  
Tie Strength ◽  
Time Step ◽  
Rumor Spreading ◽  
Spreading Model ◽  
Positive Quantity

The spread of rumors on complex networks has attracted wide attention in the field of management. In this paper, the generalized rumor spreading model is modified to take into account the vital of the spreader and the tie strength for the pairwise contacts between nodes in complex networks at degree-dependent spreading rate. Concretely, we introduce the infectivity exponent [Formula: see text], and the degree influenced real exponent [Formula: see text] into the analytical rumor spreading model. Rumor infectivity, [Formula: see text], where [Formula: see text], defines that each spreader node may contact [Formula: see text] neighbors within one time step. The tie strength between two nodes with degrees [Formula: see text] and [Formula: see text] are measured by [Formula: see text], [Formula: see text] is the degree influenced real exponent which depends on the type of complex networks and [Formula: see text] is a positive quantity. We use a tuning parameter [Formula: see text] to combine both the effect of the vital nodes and the strength of connectivity between nodes. We use analytical and numerical solutions to examine the threshold behavior and dynamics of the model on several models of social network. It was found that the infectivity exponent [Formula: see text], the degree influenced real exponent [Formula: see text] and tuning parameter [Formula: see text] affect the rumor threshold, one can adjust the parameters to control the rumor threshold which is absent for the standard rumor spreading model.

The social network

2013 ◽  
Vol 44 (2) ◽  
pp. 22
Author(s):  
ALAN ROCKOFF
Keyword(s):  
Social Network ◽  
The Social

Abstract #1249: Novel Use of Physician Social Network Data to Map the Gap in the Endocrinology Workforce

2015 ◽  
Vol 21 ◽  
pp. 301
Author(s):  
Armand Krikorian ◽  
Lily Peng ◽  
Zubair Ilyas ◽  
Joumana Chaiban
Keyword(s):  
Social Network ◽  
Network Data ◽  
Social Network Data

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

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