scholarly journals Analyzing, Modeling, and Simulation for Human Dynamics in Social Network

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Yunpeng Xiao ◽  
Bai Wang ◽  
Yanbing Liu ◽  
Zhixian Yan ◽  
Xian Chen ◽  
...  
Keyword(s):  
Social Network ◽  
Human Behavior ◽  
Large Scale ◽  
Empirical Studies ◽  
Real Life ◽  
Power Law Distribution ◽  
Human Dynamics ◽  
Individual Level ◽  
Real Life Data ◽  
Dynamic Phenomena

This paper studies the human behavior in the top-one social network system in China (Sina Microblog system). By analyzing real-life data at a large scale, we find that the message releasing interval (intermessage time) obeys power law distribution both at individual level and at group level. Statistical analysis also reveals that human behavior in social network is mainly driven by four basic elements:social pressure,social identity,social participation, andsocial relationbetween individuals. Empirical results present the four elements' impact on the human behavior and the relation between these elements. To further understand the mechanism of such dynamic phenomena, a hybrid human dynamic model which combines “interest” of individual and “interaction” among people is introduced, incorporating the four elements simultaneously. To provide a solid evaluation, we simulate both two-agent and multiagent interactions with real-life social network topology. We achieve the consistent results between empirical studies and the simulations. The model can provide a good understanding of human dynamics in social network.

scholarly journals A Hybrid Human Dynamics Model on Analyzing Hotspots in Social Networks

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Yunpeng Xiao ◽  
Bai Wang ◽  
Bin Wu ◽  
Zhixian Yan ◽  
Shousheng Jia ◽  
...  
Keyword(s):  
Social Networks ◽  
Empirical Studies ◽  
Real Life ◽  
Model Parameters ◽  
Dynamics Model ◽  
Optimal Model ◽  
Human Dynamics ◽  
Modern Age ◽  
Unique Source ◽  
Dynamic Phenomena

The increasing development of social networks provides a unique source for analyzing human dynamics in the modern age. In this paper, we analyze the top-one Internet forum in China (“Tianya Club”) and identify the statistical properties of hotspots, which can promptly reflect the crowd events in people's real-life. Empirical observations indicate that the interhotspot distribution follows a power law. To further understand the mechanism of such dynamic phenomena, we propose a hybrid human dynamic model that combines “memory” of individual and “interaction” among people. To build a rich simulation and evaluate this hybrid model, we apply three different network datasets (i.e., WS network, BA network, and Karate-Club). Our simulation results are consistent with the empirical studies, which indicate that the model can provide a good understanding of the dynamic mechanism of crowd events using such social networking data. We additionally analyze the sensitivity of model parameters and find the optimal model settings.

scholarly journals Novel Node Centrality-Based Efficient Empirical Robustness Assessment for Directed Network

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Xiaolong Deng ◽  
Hao Ding ◽  
Yong Chen ◽  
Cai Chen ◽  
Tiejun Lv
Keyword(s):  
Social Network ◽  
Vulnerability Assessment ◽  
Online Social Networks ◽  
Information Transfer ◽  
Large Scale ◽  
Real Life ◽  
Clustering Coefficient ◽  
Network Robustness ◽  
Directed Network ◽  
Online Social Media

In recent years, while extensive researches on various networks properties have been proposed and accomplished, little has been proposed and done on network robustness and node vulnerability assessment under cascades in directed large-scale online community networks. In essential, an online directed social network is a group-centered and information spread-dominated online platform which is very different from the traditional undirected social network. Some further research studies have indicated that the online social network has high robustness to random removals of nodes but fails to the intentional attacks, particularly to those attacks based on node betweenness or node directed coefficient. To explore on the robustness of directed social network, in this article, we have proposed two novel node centralities of ITG (information transfer gain-based probability clustering coefficient) and I M p v (directed path-based node importance centrality). These two new centrality models are designed to capture this cascading effect in directed online social networks. Furthermore, we also propose a new and highly efficient computing method based on iterations for I M p v . Then, with the abundant experiments on the synthetic signed network and real-life networks derived from directed online social media and directed human mobile phone calling network, it has been proved that our ITG and I M p v based on directed social network robustness and node vulnerability assessment method is more accurate, efficient, and faster than several traditional centrality methods such as degree and betweenness. And we also have proposed the solid reasoning and proof process of iteration times k in computation of I M p v . To the best knowledge of us, our research has drawn some new light on the leading edge of robustness on the directed social network.

MULTICRITERIAL RANKING APPROACH FOR EVALUATING BANK BRANCH PERFORMANCE

2004 ◽  
Vol 03 (02) ◽  
pp. 321-335 ◽  
Author(s):  
FUAD ALESKEROV ◽  
HASAN ERSEL ◽  
REHA YOLALAN
Keyword(s):  
Commercial Bank ◽  
Large Scale ◽  
Real Life ◽  
Multiple Criteria ◽  
Ranking Methods ◽  
Bank Branch ◽  
Bank Branches ◽  
Life Data ◽  
Real Life Data

14 ranking methods based on multiple criteria are suggested for evaluating the performance of the bank branches. The methods are explained via an illustrative example, and some of them are applied to a real-life data for 23 retail bank branches in a large-scale private Turkish commercial bank.

Mining Mobile Phone Messages in Mobile Social Network

2012 ◽  
Vol 457-458 ◽  
pp. 130-133
Author(s):  
Wen Cui
Keyword(s):  
Social Network ◽  
Large Scale ◽  
Essential Role ◽  
Empirical Studies ◽  
Mining Method ◽  
Mobile Social Network ◽  
Coverage Ratio ◽  
Short Period ◽  
Large Scale Dataset ◽  
Point To Point

A mobile social network plays an essential role as the spread of information and relationship. Mining the popular P2P messages in a short period of time is very valuable. Traditional mining method is not suitable for this very large scale dataset. In this paper, we present a mining approach based on MapReduce parallel framework. We use our metric to analyze point-to-point (p2p) messages within an organization to extract social hierarchy. We analyze the behavior of the communication patterns with taking into account the actual communication messages sent by users. Experimental results show that the final dataset of popular messages is very small with high sending coverage ratio. Empirical studies on a large real-world mobile social network show that performance of our algorithm.

Spontaneous Collective Action: Peripheral Mobilization During the Arab Spring

2017 ◽  
Vol 111 (2) ◽  
pp. 379-403 ◽  
Author(s):  
ZACHARY C. STEINERT-THRELKELD
Keyword(s):  
Social Network ◽  
Collective Action ◽  
Information Diffusion ◽  
Large Scale ◽  
Authoritarian Regimes ◽  
Individual Level ◽  
The Core ◽  
Wide Range ◽  
Models Of Disease ◽  
The Arab Spring

Who is responsible for protest mobilization? Models of disease and information diffusion suggest that those central to a social network (the core) should have a greater ability to mobilize others than those who are less well-connected. To the contrary, this article argues that those not central to a network (the periphery) can generate collective action, especially in the context of large-scale protests in authoritarian regimes. To show that those in the core of a social network have no effect on levels of protest, this article develops a dataset of daily protests across 16 countries in the Middle East and North Africa over 14 months from 2010 through 2011. It combines that dataset with geocoded, individual-level communication from the same period and measures the number of connections of each person. Those on the periphery are shown to be responsible for changing levels of protest, with some evidence suggesting that the core’s mobilization efforts lead to fewer protests. These results have implications for a wide range of social choices that rely on interdependent decision making.

scholarly journals Four dimensions characterize comprehensive trait judgments of faces

2019 ◽  
Author(s):  
Chujun Lin ◽  
Umit Keles ◽  
Ralph Adolphs
Keyword(s):  
Large Scale ◽  
Real Life ◽  
Three Dimensions ◽  
Prior Work ◽  
Four Dimensions ◽  
Individual Level ◽  
Level Data ◽  
Trait Words ◽  
Psychological Dimensions

People readily attribute many traits to faces: some look beautiful, some competent, some aggressive1. These snap judgments have important consequences in real life, ranging from success in political elections to decisions in courtroom sentencing2,3. Modern psychological theories argue that the hundreds of different words people use to describe others from their faces are well captured by only two or three dimensions, such as valence and dominance4, a highly influential framework that has been the basis for numerous studies in social and developmental psychology5–10, social neuroscience11,12, and in engineering applications13,14. However, all prior work has used only a small number of words (12 to 18) to derive underlying dimensions, limiting conclusions to date. Here we employed deep neural networks to select a comprehensive set of 100 words that are representative of the trait words people use to describe faces, and to select a set of 100 faces. In two large-scale, preregistered studies we asked participants to rate the 100 faces on the 100 words (obtaining 2,850,000 ratings from 1,710 participants), and discovered a novel set of four psychological dimensions that best explain trait judgments of faces: warmth, competence, femininity, and youth. We reproduced these four dimensions across different regions around the world, in both aggregated and individual-level data. These results provide a new and most comprehensive characterization of face judgments, and reconcile prior work on face perception with work in social cognition15 and personality psychology16.

A novel genetic algorithm-based improvement model for online communities and trust networks

2021 ◽  
Vol 40 (1) ◽  
pp. 1597-1608
Author(s):  
Ilker Bekmezci ◽  
Murat Ermis ◽  
Egemen Berki Cimen
Keyword(s):  
Genetic Algorithm ◽  
Social Networks ◽  
Social Network ◽  
Online Communities ◽  
Real Life ◽  
Statistical Properties ◽  
Clustering Coefficient ◽  
Data Sets ◽  
Life Data ◽  
Real Life Data

Social network analysis offers an understanding of our modern world, and it affords the ability to represent, analyze and even simulate complex structures. While an unweighted model can be used for online communities, trust or friendship networks should be analyzed with weighted models. To analyze social networks, it is essential to produce realistic social models. However, there are serious differences between social network models and real-life data in terms of their fundamental statistical parameters. In this paper, a genetic algorithm (GA)-based social network improvement method is proposed to produce social networks more similar to real-life data sets. First, it creates a social model based on existing studies in the literature, and then it improves the model with the proposed GA-based approach based on the similarity of the average degree, the k-nearest neighbor, the clustering coefficient, degree distribution and link overlap. This study can be used to model the structural and statistical properties of large-scale societies more realistically. The performance results show that our approach can reduce the dissimilarity between the created social networks and the real-life data sets in terms of their primary statistical properties. It has been shown that the proposed GA-based approach can be used effectively not only in unweighted networks but also in weighted networks.

Incidents in high-volume elongated crowd facilities: A simulation-based study

SIMULATION ◽  
2018 ◽  
Vol 95 (9) ◽  
pp. 823-843
Author(s):  
Ahmed Abdelghany ◽  
Hani Mahmassani ◽  
Khaled Abdelghany ◽  
Hasan Al-Ahmadi ◽  
Wael Alhalabi
Keyword(s):  
Large Scale ◽  
Real Life ◽  
Linear Structure ◽  
High Volume ◽  
Heterogeneous Traffic ◽  
Individual Level ◽  
Stop And Go ◽  
Simulation Based ◽  
The Individual ◽  
Inefficient Operation

This paper presents the main findings of a simulation-based study to evaluate incidents in pedestrian/crowd tunnels and similar elongated confined facilities, with high-volume heterogeneous traffic. These incidents, when occur, imposes hazardous conditions that always result in significant number of fatalities. The aim of this study is to understand how these facilities perform under different irregular scenarios and possibly identify potential causes of accidents. The problem of studying incidents in large-scale high-volume pedestrian facilities is that these incidents are difficult to expect or replicate. Thus, studying these facilities through real-life scenarios is almost impossible. Accordingly, a micro-simulation assignment model for multidirectional pedestrian movement is used for this purpose. The model adopts a Cellular Automata (CA) discrete system, which allows detailed representation of the pedestrians’ walkways in the tunnel. The modeling approach captures crowd dynamics through representation of behavioral decisions of heterogeneous pedestrians at the individual level. Several experiments are conducted to study the pedestrian flow in the proposed tunnel considering different operational scenarios including demand levels, heterogeneous traffic, evacuation scenario, and tunnel blockage. Results show that flow of large pedestrian volumes through a long confined linear structure, such as a tunnel, are subject to the same flow dynamics as we observe with vehicular traffic. In particular, they are subject to the formation of “clumps” and shock waves that can rapidly propagate and lead to inefficient operation, including flow breakdown with stop-and-go waves.

scholarly journals Quantifying segregation in an integrated urban physical-social space

2019 ◽  
Vol 16 (160) ◽  
pp. 20190536 ◽  
Author(s):  
Yang Xu ◽  
Alexander Belyi ◽  
Paolo Santi ◽  
Carlo Ratti
Keyword(s):  
Social Network ◽  
Large Scale ◽  
Social Space ◽  
Human Mobility ◽  
Economic Status ◽  
Physical Space ◽  
Two Dimensions ◽  
Time Resolved ◽  
Individual Level ◽  
The Individual

Our knowledge of how cities bring together different social classes is still limited. Much effort has been devoted to investigating residential segregation, mostly over well-defined social groups (e.g. race). Little is known of how mobility and human communications affect urban social integration. The dynamics of spatial and social-network segregation and individual variations along these two dimensions are largely untapped. In this article, we put forward a computational framework based on coupling large-scale information on human mobility, social-network connections and people’s socio-economic status (SES), to provide a breakthrough in our understanding of the dynamics of spatio-temporal and social-network segregation in cities. Building on top of a social similarity measure, the framework can be used to depict segregation dynamics down to the individual level, and also provide aggregate measurements at the scale of places and cities, and their evolution over time. By applying the methodology in Singapore using large-scale mobile phone and socio-economic datasets, we find a relatively higher level of segregation among relatively wealthier classes, a finding that holds for both social and physical space. We also highlight the interplay between the effect of distance decay and homophily as forces that determine communication intensity, defining a notion of characteristic ‘homophily distance’ that can be used to measure social segregation across cities. The time-resolved analysis reveals the changing landscape of urban segregation and the time-varying roles of places. Segregations in physical and social space are weakly correlated at the individual level but highly correlated when grouped across at least hundreds of individuals. The methodology and analysis presented in this paper enable a deeper understanding of the dynamics of human segregation in social and physical space, which can assist social scientists, planners and city authorities in the design of more integrated cities.

scholarly journals Experts as facilitators for the implementation of social media in the library? A social network approach

2014 ◽  
Vol 32 (3) ◽  
pp. 529-545 ◽  
Author(s):  
Hadewijch Vanwynsberghe ◽  
Elke Boudry ◽  
Ruben Vanderlinde ◽  
Pieter Verdegem
Keyword(s):  
Social Media ◽  
Social Network ◽  
Large Scale ◽  
Public Libraries ◽  
Empirical Studies ◽  
Social Capital Theory ◽  
Capital Theory ◽  
Content Type ◽  
The Social ◽  
Social Network Approach

Purpose – Based on the social capital theory, the authors assume that personal and professional experts are both relevant to people's competence development. However, to date, there is little empirical evidence of how professional experts can support, or impede, people in learning how to deal with social media. The purpose of this paper is to examine the role and position of social media experts in the distribution of information on social media within the library as organization. Design/methodology/approach – The paper draws upon social network and qualitative methods, within three public libraries located in Belgium. Findings – The findings suggest that as the most central actors, social media experts in a library play a significant role in either supporting or constraining the distribution of information on social media. Research limitations/implications – While the sample size was chosen to conduct a mixed methods study that would explore how the position of a social media expert in an organization such as the library facilitates or prevents the exchange of social media information, the authors acknowledge the need for large-scale empirical studies that can substantiate the findings in larger and more diverse samples. Originality/value – This unique study explores how the role and position social media experts in Belgian public libraries can support, or impede, librarians in learning how to deal with social media. This study is useful for other public libraries who want to implement social media, establish a social media policy and/or provide social media training.

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