The research on propagation modeling and governance strategies of online rumors based on behavior–attitude

PurposeThe purpose of this paper is to achieve effective governance of online rumors through the proposed rumor propagation model and immunization strategy.Design/methodology/approachThe paper leverages the agent-based modeling (ABM) method to model individuals from two aspects, behavior and attitude. Based on the analysis and research of online data, we propose a rumor propagation model, namely the Untouched view transmit removed-Susceptible hesitate agree disagree (Unite-Shad), and devise an immunization strategy, namely the Gravity Immunization Strategy (GIS). A graph-based framework, namely Pregel, is used to carry out the rumor propagation simulation experiments. Through the experiments, the rationality of the Unite-Shad and the effectiveness of the GIS are verified.FindingsThe study discovers that the inconsistency between human behaviors and attitudes in rumor propagation can be explained by the Unite-shad model. Besides, the GIS, which shows better performance in small-world networks than in scale-free networks, can effectively suppress rumor propagation in the early stage.Research limitations/implicationsThis paper provides an effective immunization strategy for rumor governance. Specifically, the Unite-Shad model reveals the mechanism of rumor propagation, and the GIS provides an effective governance method for selecting immune nodes.Originality/valueThe inconsistency of human behaviors and attitudes in real scenes is modeled in the Unite-Shad model. Combined with the model, the definition of diffusion domain is proposed and a novel immunization strategy, namely GIS, is designed, which is significant for the social governance of rumor propagation.

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Rumor Propagation Model for Complex Network with Non-Uniform Propagation Rates

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.596.868 ◽

2014 ◽

Vol 596 ◽

pp. 868-872 ◽

Cited By ~ 1

Author(s):

Rui Sun ◽

Wan Bo Luo

Keyword(s):

Mean Field Theory ◽

Mean Field ◽

Propagation Rate ◽

Propagation Model ◽

Scale Free Network ◽

Propagation Characteristics ◽

Affecting Factors ◽

Scale Free ◽

Rumor Propagation ◽

Free Network

Considering propagation characteristics and affecting factors of rumor in real-world complex networks, this paper described different propagation rates of different nodes by introducing the rumor acceptability function. Based on mean-field theory, this paper presented a rumor propagation model with non-uniform propagation rate, and then simulated the behaviour of rumor propagation on scale-free network and calculated the propagation thresholds by corresponding dynamics equation. Theoretical analysis and simulation results show that nodes with different rumor acceptability could lead to slowing the spread of rumors, make positive propagation threshold arise, and effectively contain the outbreak and reduce the risk of rumors.

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Embedding funding consultation in library services

Library Hi Tech ◽

10.1108/lht-06-2017-0127 ◽

2018 ◽

Vol 36 (3) ◽

pp. 378-399 ◽

Cited By ~ 3

Author(s):

Jiang Wu ◽

Jingxuan Cai ◽

Miao Jin ◽

Ke Dong

Keyword(s):

Network Analysis ◽

Small World ◽

Knowledge Flow ◽

Lower Probability ◽

Library Services ◽

Flow Network ◽

Content Type ◽

Scale Free ◽

Interdisciplinary Knowledge ◽

Funding Application

Purpose Although interdisciplinary research is an increasing trend in scientific funding projects, they are suffering from a lower probability of being funded. The purpose of this paper is to analyze the current situation on successful case of funding application and provides suggestions on how libraries can expand services to help scientific funding application. Design/methodology/approach This paper utilizes the co-occurrences of disciplinary application codes to construct an interdisciplinary knowledge flow network. Based on 193517 sponsored projects of the National Natural Science Foundation of China, the authors study the interdisciplinary flow of knowledge and investigate the evolution of network structure using social network analysis. Findings Results show that the interdisciplinary knowledge flow network is not only a small-world network but also a scale-free network. Two main knowledge flow paths across scientific departments exist, showing the heterogeneity of knowledge distributions across scientific disciplines. The authors also find that if two disciplines in the same scientific department both have a wide influence to other disciplines, they are more prone to link together and create a knowledge chain. Originality/value Funding consultation currently has not occupied an advisory role either in library services or in the research team. This paper conducts a co-occurrences network analysis of interdisciplinary knowledge flow in scientific funding projects. Considering the complexity of funding application and the advantage of traditional library services on information collection, integration, and utilization, the authors conclude the possibility and necessity of embedding funding consultation in traditional library services.

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Cross-network propagation model of public opinion information and its control in coupled double-layer online social networks

Aslib Journal of Information Management ◽

10.1108/ajim-04-2021-0126 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Yun Li ◽

Jiakun Wang

Keyword(s):

Social Networks ◽

Public Opinion ◽

Double Layer ◽

Online Social Networks ◽

Early Stage ◽

Intervention Strategy ◽

Propagation Model ◽

Content Type ◽

Propagation Law ◽

Network Propagation

PurposeIn modern society, considering the multi-channel of public opinion information (public opinion) propagation and its strong influence on social development, it is necessary to study its propagation law and discuss the intervention strategy in online social networks (OSN).Design/methodology/approachFirst, a conceptual model of double-layer OSN was constructed according to their structural characteristics. Then, a cross-network propagation model of public opinion in double-layer OSN was proposed and discussed its spreading characteristics through numerical simulations. Finally, the control strategy of public opinion, especially the timing and intensity of intervention were discussed.FindingsThe results show that the double-layer OSN promotes the propagation of public opinion, and the propagation of public opinion in double-layer OSN has the characteristics of that in two single-layer OSN. Compared with the intervention intensity, the regulator should give the priority to the timing of intervention and try to intervene in the early stage of public opinion propagation.Practical implicationsThis study may help the regulators to respond to the propagation of public opinion in OSN more actively and reasonably.Originality/valueThis research has a deep comprehension of the cross-network propagation rules of public opinion and manages the propagation of public opinion.

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Utilising social network analysis to study the characteristics and functions of the co-occurrence network of online tags

Online Information Review ◽

10.1108/oir-11-2012-0124 ◽

2014 ◽

Vol 38 (2) ◽

pp. 232-247 ◽

Cited By ~ 12

Author(s):

Ma Feicheng ◽

Li Yating

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Small World ◽

Online Resources ◽

Social Tagging ◽

The Internet ◽

Content Type ◽

Categorical Analysis ◽

Scale Free

Purpose – This paper aims to explore the characteristics of the co-occurrence network of online tags and propose new approaches of applying social network analysis by utilising social tagging in order to organise data. Design/methodology/approach – The authors collected online resources labelled “tag” from 7 November 2004 to 31 October 2011 from the CiteULike website, comprising 684 papers and their URLs, titles and data on tagging (users, times, and tags). They examined the co-occurrence network of online tags by using the analyses of social networks, including the analysis of coherence, the analysis of centricity and core to periphery categorical analysis. Findings – Some features of the co-occurrence of online tags are as follows: the internet is subject to the “small world” phenomenon, as well as being “scale-free”. The structure of the internet reflects stable areas of core knowledge. In addition to five possible applications of social network analysis, social tagging has the greatest significance in organising online resources. Originality/value – This research finds that co-occurrence of tags online is an effective way to organise and index data. Some suggestions are provided on the organisation of online resources.

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Modeling Network Public Opinion Propagation with the Consideration of Individual Emotions

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17186681 ◽

2020 ◽

Vol 17 (18) ◽

pp. 6681

Author(s):

Peihua Fu ◽

Bailu Jing ◽

Tinggui Chen ◽

Jianjun Yang ◽

Guodong Cong

Keyword(s):

Public Opinion ◽

Attitude Change ◽

Rapid Development ◽

Small World ◽

Inhibitory Effect ◽

Propagation Model ◽

Clustering Coefficient ◽

Factors Affecting ◽

Scale Free ◽

Network Public Opinion

The occurrence of popular social events causes fluctuations and changes of public emotions, while the rapid development of online social platforms and networks has made individual interactions more intense and further escalated public emotions into public opinion. However, there is a lack of consideration of individual emotions in the current research on online public opinion. Based on this, this paper firstly expounds the quantitative representation of attitude and emotion, analyzes the formation and propagation process of online public opinion by combining individual’s expression willingness, individual’s expression ability, attitude perception value, attitude change probability and other factors, and constructs a network public opinion propagation model that takes individual emotion into consideration. Finally, the main factors affecting the formation and propagation of network public opinion are discussed through simulation experiments. The results demonstrate that: (1) fear is conducive to the formation of online public opinion, but the speed is relatively slow; sadness is not conducive to the formation, but once enough people participate in the exchange of views, the formation of online public opinion will be faster; (2) the influence of online public opinion on individual emotions expands with the increase of the number of individual interactions; (3) different network structures impact differently on the propagation of public opinion. Among them, BA (BA network is a scale-free network model proposed by Barabasi and Albert in order to explain the generation mechanism of power law, BA model has two characteristics: growth and priority connection mechanism) and ER (ER network is a network with random connectivity proposed by Erdös-Renyi) random networks can promote the propagation of online public opinion, which is prone to “one-sided” online public opinion. WS small-world networks (proposed by Watts and Strogatz. It is a kind of network with short average path length and high clustering coefficient) and fully-connected networks have an inhibitory effect on the spread of online public opinion, easily maintaining the multi-dimensional nature of online public opinion.

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Agent-Based Simulation of Rumor Propagation on Social Network Based on Active Immune Mechanism

Journal of Systems Science and Information ◽

10.21078/jssi-2017-571-14 ◽

2017 ◽

Vol 5 (6) ◽

pp. 571-584 ◽

Cited By ~ 2

Author(s):

Jianhong Chen ◽

Qinghua Song ◽

Zhiyong Zhou

Keyword(s):

Social Network ◽

Online Social Network ◽

Propagation Model ◽

Immune Mechanism ◽

Scale Free Network ◽

Propagation Process ◽

Agent Based ◽

Scale Free ◽

Rumor Propagation ◽

Free Network

AbstractTo simulate the rumor propagation process on online social network during emergency, a new rumor propagation model was built based on active immune mechanism. The rumor propagation mechanisms were analyzed and corresponding parameters were defined. BA scale free network and NW small world network that can be used for representing the online social network structure were constructed and their characteristics were compared. Agent-based simulations were conducted on both networks and results show that BA scale free network is more conductive to spreading rumors and it can facilitate the rumor refutation process at the same time. Rumors paid attention to by more people is likely to spread quicker and broader but for which the rumor refutation process will be more effective. The model provides a useful tool for understanding and predicting the rumor propagation process on online social network during emergency, providing useful instructions for rumor propagation intervention.

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Research on the Methods of Identifying Key Node Based on Classical Networks

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.530-531.489 ◽

2014 ◽

Vol 530-531 ◽

pp. 489-495

Author(s):

Song Hua Wang

Keyword(s):

Matrix Method ◽

Random Network ◽

Small World ◽

Propagation Model ◽

Simulation Experiments ◽

Scale Free ◽

Node Importance ◽

Different Types ◽

Free Network ◽

Evaluation Matrix

Identifying the most important node is a research hotspot in complex networks. For different types of network there are different methods to cope with. In this paper, we use five methods: degree method, betweenness method, node contraction method, node importance evaluation matrix method, K-shell decomposition method to identify the key node and compare the effects through SIR propagation model. In the simulation experiments, we use three artificial networks: random network (ER), small-world network (NW) and scale-free network (BA). The experimental results show that the nodes identified by node importance evaluation matrix method and K-shell method are more important. Besides, in BA the infection velocity is faster and the infection scale is larger than in ER and NW.

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Greedy immunization strategy in weighted scale-free networks

Engineering Computations ◽

10.1108/ec-11-2012-0285 ◽

2014 ◽

Vol 31 (8) ◽

pp. 1627-1634 ◽

Cited By ~ 1

Author(s):

Zhang-Hui Liu ◽

Guo-Long Chen ◽

Ning-Ning Wang ◽

Biao Song

Keyword(s):

Greedy Algorithm ◽

Design Methodology ◽

Experimental Results ◽

Scale Free Network ◽

Immunization Strategy ◽

Content Type ◽

Network Partition ◽

Scale Free ◽

Scale Free Networks ◽

Free Network

Purpose – The purpose of this paper is to present a new immunization strategy for effectively solving the control of the spread of the virus. Design/methodology/approach – Inspired by the idea of network partition, taking two optimization targets which are the scale of sub-network and the sum of the strengths of the sub-network's nodes into account at the same time, a new immunization strategy based on greedy algorithm in the scale-free network is presented. After specifying the number of nodes through the immunization, the network is divided into the scale of sub-network and the sum of the strength of the sub-network's nodes as small as possible. Findings – The experimental results show that the proposed algorithm has the better performance than targeted immunization which is supposed to be highly efficient at present. Originality/value – This paper proposes a new immunization strategy based on greedy algorithm in the scale-free network for effectively solving the control of the spread of the virus.

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