A MODEL FOR BRAND COMPETITION WITHIN A SOCIAL NETWORK

2010 ◽  
Vol 21 (12) ◽  
pp. 1457-1467
Author(s):  
R. HUERTA-QUINTANILLA ◽  
E. CANTO-LUGO ◽  
M. RODRÍGUEZ-ACHACH
Keyword(s):  
Social Network ◽  
Network Topology ◽  
Decision Rules ◽  
Nearest Neighbors ◽  
Product Market ◽  
Economic Benefits ◽  
Model Parameters ◽  
Agent Based ◽  
Absorbing State ◽  
Brand Competition

An agent-based model was built representing an economic environment in which m brands are competing for a product market. These agents represent companies that interact within a social network in which a certain agent persuades others to update or shift their brands; the brands of the products they are using. Decision rules were established that caused each agent to react according to the economic benefits it would receive; they updated/shifted only if it was beneficial. Each agent can have only one of the m possible brands, and she can interact with its two nearest neighbors and another set of agents which are chosen according to a particular set of rules in the network topology. An absorbing state was always reached in which a single brand monopolized the network (known as condensation). The condensation time varied as a function of model parameters is studied including an analysis of brand competition using different networks.

scholarly journals CONDENSATION IN AN ECONOMIC MODEL WITH BRAND COMPETITION

2006 ◽  
Vol 17 (05) ◽  
pp. 749-756 ◽  
Author(s):  
L. CASILLAS ◽  
F. J. ESPINOSA ◽  
R. HUERTA-QUINTANILLA ◽  
M. RODRIGUEZ-ACHACH
Keyword(s):  
Numerical Simulations ◽  
Economic Model ◽  
Nearest Neighbors ◽  
The Other ◽  
Agent Based Model ◽  
Agent Based ◽  
Brand Competition

We present a linear agent based model on brand competition. Each agent belongs to one of the two brands and interacts with its nearest neighbors. In the process the agent can decide to change to the other brand if the move is beneficial. The numerical simulations show that the systems always condenses into a state when all agents belong to a single brand. We study the condensation times for different parameters of the model and the influence of different mechanisms to avoid condensation, like anti monopoly rules and brand fidelity.

scholarly journals Deep Learning Exploration of Agent-Based Social Network Model Parameters

2021 ◽  
Vol 4 ◽  
Author(s):  
Yohsuke Murase ◽  
Hang-Hyun Jo ◽  
János Török ◽  
János Kertész ◽  
Kimmo Kaski
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Model ◽  
Network Models ◽  
Agent Based Modeling ◽  
Training Data ◽  
Model Parameters ◽  
Social Phenomena ◽  
Agent Based ◽  
Input Parameters

Interactions between humans give rise to complex social networks that are characterized by heterogeneous degree distribution, weight-topology relation, overlapping community structure, and dynamics of links. Understanding these characteristics of social networks is the primary goal of their research as they constitute scaffolds for various emergent social phenomena from disease spreading to political movements. An appropriate tool for studying them is agent-based modeling, in which nodes, representing individuals, make decisions about creating and deleting links, thus yielding various macroscopic behavioral patterns. Here we focus on studying a generalization of the weighted social network model, being one of the most fundamental agent-based models for describing the formation of social ties and social networks. This generalized weighted social network (GWSN) model incorporates triadic closure, homophilic interactions, and various link termination mechanisms, which have been studied separately in the previous works. Accordingly, the GWSN model has an increased number of input parameters and the model behavior gets excessively complex, making it challenging to clarify the model behavior. We have executed massive simulations with a supercomputer and used the results as the training data for deep neural networks to conduct regression analysis for predicting the properties of the generated networks from the input parameters. The obtained regression model was also used for global sensitivity analysis to identify which parameters are influential or insignificant. We believe that this methodology is applicable for a large class of complex network models, thus opening the way for more realistic quantitative agent-based modeling.

scholarly journals Analysis of Cooperative Perception in Ant Traffic and Its Effects on Transportation System by Using a Congestion-Free Ant-Trail Model

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2393
Author(s):  
Prafull Kasture ◽  
Hidekazu Nishimura
Keyword(s):  
Average Velocity ◽  
Transportation System ◽  
Self Organization ◽  
Model Parameters ◽  
Agent Based ◽  
Model Simulations ◽  
Mathematical Representations ◽  
Traffic Conditions ◽  
Traffic Jams ◽  
Ant Trail

We investigated agent-based model simulations that mimic an ant transportation system to analyze the cooperative perception and communication in the system. On a trail, ants use cooperative perception through chemotaxis to maintain a constant average velocity irrespective of their density, thereby avoiding traffic jams. Using model simulations and approximate mathematical representations, we analyzed various aspects of the communication system and their effects on cooperative perception in ant traffic. Based on the analysis, insights about the cooperative perception of ants which facilitate decentralized self-organization is presented. We also present values of communication-parameters in ant traffic, where the system conveys traffic conditions to individual ants, which ants use to self-organize and avoid traffic-jams. The mathematical analysis also verifies our findings and provides a better understanding of various model parameters leading to model improvements.

scholarly journals Reproducing scientists’ mobility: a data-driven model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giacomo Vaccario ◽  
Luca Verginer ◽  
Frank Schweitzer
Keyword(s):  
Decision Rules ◽  
Migration Policy ◽  
Large Data ◽  
Global Scale ◽  
Global Network ◽  
Data Sets ◽  
Mobility Patterns ◽  
Agent Based ◽  
Hiring Process ◽  
Geographical Distances

AbstractHigh skill labour is an important factor underpinning the competitive advantage of modern economies. Therefore, attracting and retaining scientists has become a major concern for migration policy. In this work, we study the migration of scientists on a global scale, by combining two large data sets covering the publications of 3.5 million scientists over 60 years. We analyse their geographical distances moved for a new affiliation and their age when moving, this way reconstructing their geographical “career paths”. These paths are used to derive the world network of scientists’ mobility between cities and to analyse its topological properties. We further develop and calibrate an agent-based model, such that it reproduces the empirical findings both at the level of scientists and of the global network. Our model takes into account that the academic hiring process is largely demand-driven and demonstrates that the probability of scientists to relocate decreases both with age and with distance. Our results allow interpreting the model assumptions as micro-based decision rules that can explain the observed mobility patterns of scientists.

Consumers’ redemption behavior of recommended mobile coupons in social network sites

2019 ◽  
Vol 57 (9) ◽  
pp. 2477-2500 ◽  
Author(s):  
Qing Tang ◽  
Fen Liu ◽  
Shan Liu ◽  
Yunfeng Ma
Keyword(s):  
Social Network ◽  
Perceived Risk ◽  
Social Network Sites ◽  
Economic Benefits ◽  
Social Recommendation ◽  
Content Type ◽  
Coupon Redemption ◽  
Mobile Coupons ◽  
Key Drivers ◽  
Trust Propensity

Purpose The purpose of this paper is to explore the key factors that affect consumer redemption intention toward mobile coupons recommended in social network sites (SNS). Design/methodology/approach A research model that integrates recommendation trust, positive utilities, and negative utilities of coupon redemption is developed. With the important role of trust in social recommendation taken into consideration, the key drivers of recommendation trust were analyzed in the model. Data were collected from 210 users with mobile coupon recommendation experience in one of the largest SNS (i.e. WeChat) in China. The authors used partial least squares technique to analyze the model. Findings Recommendation trust and positive utilities (economic benefits and perceived enjoyment) positively affect the intention of mobile coupon redemption. Perceived risk, as a negative utility, negatively influences coupon redemption intention. In addition, swift trust (structure assurance, perceived similarity, trust propensity, and expertise of the recommender), knowledge-based trust (familiarity with the retailers), and emotion-based trust (social tie strength) are key drivers that promote recommendation trust. Originality/value While prior research investigated mobile coupon redemption behavior in which coupons were issued by merchants, limited research analyzed consumer responses toward mobile coupons in social recommendation. This study examines the effects of recommendation trust, positive utilities, and negative utilities on mobile coupon redemption in the context of social recommendation and recognizes the key drivers of recommendation trust.

Building Recommendation Service with Social Networks and Semantic Databases

2014 ◽  
pp. 83-92
Author(s):  
Sašo Karakatič ◽  
Vili Podgorelec ◽  
Marjan Heričko
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Semantic Information ◽  
Additional Data ◽  
Nearest Neighbors ◽  
K Nearest Neighbors ◽  
Web Based ◽  
Semantic Database

In this chapter, it is shown how useful user services can be created through the integration of social networks and semantic databases. The authors developed a recommendation service in a form of a Web-based application, where a user's interests are imported from social network Facebook and linked with additional data from open semantic database Freebase. Based on a custom implementation of k-nearest neighbors algorithm, the developed method is able to find recommendations based on users’ interests enriched with semantic information. The resulting list of found recommendations is then shown to the user in some basic categories like movies, music, games, books, and others.

Motif Analysis and the Periodic Structural Changes in an Organizational Email-Based Social Network

2011 ◽  
pp. 292-302
Author(s):  
Krzysztof Juszczyszyn ◽  
Katarzyna Musial
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Topology ◽  
Structural Changes ◽  
Structural Parameters ◽  
Local Network ◽  
Network Motifs ◽  
Motif Analysis ◽  
University Of Technology ◽  
E Mail

Network motifs are small subgraphs that reflect local network topology and were shown to be useful for creating profiles that reveal several properties of the network. In this work the motif analysis of the e-mail network of the Wroclaw University of Technology, consisting of over 4000 nodes was conducted. Temporal changes in the network structure during the period of 20 months were analysed and the correlations between global structural parameters of the network and motif distribution were found. These results are to be used in the development of methods dedicated for fast estimating of the properties of complex internet-based social networks.

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