2017 2nd International Conference on Artificial Intelligence and Engineering Applications (AIEA 2017)
ISBN: 978-1-60595-485-1
Rumor Spreading: A Survey
MEILING JIN, FENGMING LIU and CHUIYUN ZHOU
ABSTRACT
It is the key factor to restrain rumor spreading, purify the environment of network and promote network harmony that deep studying the rumor spreading. The paper first discussed the serious harmfulness of rumor spreading to society. Then, from the social media types, model research methods, model structure, research theory and whether the relationship considered the trust, the paper made the classified research and discussion of the network dissemination; finally, the paper made a prospect of the future research of rumor spreading and put forward some further research ideas.
KEYWORDS
Rumor spread, Model, Review.
INTRODUCTION
The definition of the rumor still has many different theories, but the researcher's generalization of the rumor is unified in the following 3 points: 1) information. A rumor is a message that is a discrepancy between the facts of someone, something, or a problem. 2) Transmission. Rumors will be circulated in a certain number of people in a certain range and believed by many. 3) Unknown. Rumors are unconfirmed messages or information that the results are not necessarily false and sometimes prove to be true. Therefore, rumor is not only a diffusion process of information, but also a process of explanation and comment. This process is characterized by anonymity, timeliness, bursting, repeatability, and irritation.
The existence of rumors has a strong harmfulness to the social harmony. For rumors, the relatively systematic and scientific study began in the period of World War II, when Knapp collected and sorted out 1000 wartime rumors over 1942 years, and classified which by systematic analysis according to the different purposes and contents of rumor[1]. This study lays an important foundation for the relevant theoretical research of rumor. In order to suppress the spreading of rumors, and promote social harmony better, people study the rumor mainly from the rumor-making, rumor spreading, rumor recognition and other aspects of research, among them, the rumors spreading is the most extensive research.
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Meiling Jin, [email protected], Fengming Liu, [email protected], School of Management Science and Engineering, Shandong Normal University, Ji’nan 250014, China,
In this paper, the research of rumor spreading is considered synthetically, which classifies the research of rumor propagation from 5 aspects of social media type, model research method, model structure, research theory and whether the trust relationship is involved.
ORGANIZATION OF THE TEXT STARTING WITH SOCIAL MEDIA TYPES
Social media is a tool and platform for people to share ideas, insights, experiences and viewpoints with each other. In the basic form, social media include microblog, micro-letters, wikis, podcasts, forums, social networks, content communities, etc. As a new type of online media which can give users great participation in space, social media has the basic characteristics of participation, sharing, communication, community and connectivity compared with traditional media. In the 2016 Chinese social media impact report, CCTV market research Company (CTR) Media and consumer behavior general manager Li said: "The trust of social media users to traditional media has declined, this phenomenon in the social media users are particularly prominent. New media platforms, represented by micro-letters and the Internet, are increasingly trusted by young social media users." At the same time, the report points out that if Chinese social media users are compared with social media users in the US, UK, France and Brazil, the Chinese are ranked third. This has prompted more and more researchers to study the spreading and suppression of rumors in different social media.
At present, the research on rumor spread is mainly focused on micro-blogging, and there is little research on other social media such as micro-letter. The micro-blogging community users are abstracted into nodes in the network, which constructed the micro-blogging information propagation network, and the scale of rumor propagation is reduced by reducing the effective infection rate and decreasing the distribution entropy of network degree [2]. Xiang Zhuoyuan, etc. [3] based on the spread of rumors in micro-blog put forward the SIR-CO model with the mechanism of suspicion and anti-rumor; Liu [4] based on the infectious disease of the basic model made the audience expanded to 5 categories: ignorant, contacts, communicators, silence, lost interest, and introduced the interest attenuation functions. Considering the increasing size of micro-blogging and the increasing of new connections between nodes, a new SIR Rumor propagation model based on Weibo is proposed in the BA scale-free network [5]. Xiong, considering the network topology and propagation mechanism in micro-blogging, established a new rumor propagation model [6].
Taking the positive and negative effects of the media, rumor accepts, the effect of trust into account, Liao builds up the rumor-receiving function, and presents a CASR (Credulous- Affected- Spreader- Rationals) rumor propagation model based on the rumor-accepting probability function [7]. There are not only the ordinary individual user, but also the public user among the micro-letter user, therefore, Tan Zhihua separated the public users from the micro-credit personal users to build a micro-letter two-layer network [8]; And, for micro-letters, rumors are mainly spreaded through the circle of friends, its dissemination process presented three stages of development: brewing, outbreak and quell, which has a great destructive for the society [9].
Therefore, the research of rumor spreading to internet forums is also possible to reduce rumor spreading and to develop a more harmonious atmosphere for the society. Among them, Xu Yaijie[10] studied the spreading and restraining of rumor in Network forum, which pointed out that the epidemic SIR model cannot fully characterize the spreading of rumor, so by improving the classical SIR model, the SEIR (State of health s, latent state E, state I, Immune State R) model based on trust mechanism is proposed.
FROM RESEARCH METHODS
The mean field theory, which replaces the single effect tax with the average effect, can simplify the complex problem effectively, so it is widely used in mathematics, chemistry and physics research, and is also the most widely used method for the study of rumor spreading. The mean field theory plays an important role in the topological structure and model analysis of stochastic networks, small world networks and scale-free networks. For example, M. Nekovee used the mean field equation to describe the IMC rumor propagation model in complex social networks, and used numerical simulations to compare them in random graphs and scale-free networks. Finally, it is found that the scale-free network is more practical for the study of rumor propagation [11]; in complex networks, rumors also have the nature of the counter-offensive and the self-resistance. Therefore, Yongli Zan based on this kind of nature proposed the SICR (Susceptible–Infective–Counterattack–Refractory) model and the improved SICR rumor propagation model, and used the mean field theory method to describe the dynamic characteristics of the model in homogeneous network, and discussed the influence of the parameters of the self-resistance on the rumor propagation [12].
The theory of seepage is mainly used in connectivity problem, and the spread of epidemics and rumors are directly related to connectivity problems. All kinds of evolution of rumor propagation can be described by seepage, but the theory of seepage mainly considers the randomness of nodal joint, so the percolation theory is mainly used in random network [13]. The percolation in stochastic network is the process of large-scale increase of the connectivity of the system with the increase of the number of connecting edges of the system. In the reality network, in addition to the continuously changing of the number of nodes, the number of nodes is also increasing, so the percolation theory is not applicable to the real network.
EXPAND FROM MODEL STRUCTURE
Rumor spreading in social media network is similar to the spread of infectious disease in the population, so most of the rumor propagation models are similar to the epidemic model. Experts studied the propagation mechanism of infectious diseases, establishes simple model, SI model, SIS model, and finally experiences the relative perfect SIR model, and the SIR model is the most widely used one in rumor propagation model.
Qiu, referencing the SIR model, and considering the reality of external forces (such as authority) and internal forces (such as human forgetting nature), pointed out that the spread of the rumor is dependent on time [19]; What’s more, researchers pointed out that the ignorant not only get rumors from their neighbors, but also through other channels, thus the independent propagator is introduced into the SIR propagation model [20].
However, the researchers point out that the model of infectious disease transmission does not fully characterize all the states of the rumor spreading process. Wang added several realistic factors, proposed the Siraru rumor propagation model [21]; Xia introduced the attraction and fuzziness of rumors into the SEIR model, and put forward the SEIR model of considering hesitation mechanism [22]; Considering that the infection state is divided into positive infection and negative infection by analyzing rumor propagation rule, Xue Yibo established the new rumor propagation model: SPNR rumor spreading model [23].
FROM THE THEORY OF STUDY
Applied Mathematical Theory.
For the study of rumor propagation, the first theory applied is based on mathematical methods. The first rumor propagation model based on mathematical theory is D-K model; In view of this, Maki D and Thomson also used mathematical models to carry out theoretical research on rumor propagation [24, 25]; after that, in addition to theoretical analysis, the researchers began to test the proposed model using experimental simulations. Virginia Giorno, based on the classic DK model, introduced the negative concept and put forward a rumor propagation model based on random negation [26]. Based on evolutionary game theory to study rumor propagation, it is found that increasing individual judgment ability can effectively restrain rumor spreading [27]; some scholars classified the audience on the basis of the classical SIR model and built new models [28]. Other than, Huo divided the propagator into highly active and low active states, and used the Routh Stability Criterion to estimate the equilibrium local asymptotic stability, and the global stability of the model is proved by the invariance principle of Lasalle [29].
Applied Physics theory.
depending on the generative function of the statistical physics of the disordered system and the harmonic cavity,it theoretically broke the existence theory of the threshold of rumor propagation[31]. Using stochastic differential equations to describe the characteristics of rumor propagation, it conducted the simulation in BA Network and WS Network, where the results showed that the increase of noise speeds up the spread of rumors and expands the spread of rumors [32].
Applied Computer theory.
With the rapid development of mobile social networks, Zhu [33] proposed that ordinary differential equations are no longer so suitable to describe the rumor spreading of online social networks. Therefore, based on the diffusion equation, a discrete, nonlocal delay propagation model is proposed. Considering the diversity of software, based on the study of the rumor propagation process in malware, the SEIRS-V model is proposed [34]. From the view of the classical SIR model, Tian designed the SSIC model, which can effectively intervene the rumor propagation [35].
Application of complex network theory.
For the study of rumor spreading, the researcher generally studies the rumor spreading by establishing the node and the social network which is the human-human relations [36]. Because the probability of rumor spreading among different individuals is different, and the law of propagation in the network of different topological structures is not the same, the rumor spread begins to converge to the complex network.
THE ROLE OF TRUST MECHANISM IN SPREADING RUMORS
The Sociologist Bonun points out that the intensity of rumors is always proportional to the importance of the rumor and the ambiguity of the event, namely R (Rumor) = (Importance) * A (Ambiguity). Later, some scholars added the factors of the disseminator, namely the public's critical ability, and pointed out that the rumor spreading was mainly affected by the following three points:
1) The relationship between the event and the individual's interest; 2) Personal awareness of event-related information;
3) The thinking rationality that can correctly understand and judge the above two points.
The author believes that the above three points need meeting a condition in essence: the social individual’s deep sense of security and trust. Therefore, many scholars have added the trust factor in the study of rumor spreading. In the study of the rumors spreading on the social network of micro-letters, Liao Liefa [7] put forward a CASR rumor propagation model based on the rumor-accepting probability function, which included the media effect with positive and negative effects, the superposition of rumors and the trust degree factors.
SUMMARY
of them use the mean field theory method; from the model structure, people basically draw on the SIR Classical propagation model of infectious disease. From the research theory, the researchers first applied mathematical methods, but the mean field equation method based on physics is the most widely used method to study rumor propagation. With the rapid development of mobile social networks, some scholars began to study the rumor spread from computer, but the most application and the most fire is the complex network theory. Later, many scholars took the trust factor into account, but the research is not mature enough. Therefore, this paper holds that it is very important to study the mechanism of the influence of the trust factors on the rumor transmission.
Regarding the influence of trust factors on rumor spreading, this article takes the follow two aspects into account: 1): To consider the influence of different trust degree on rumor spreading, and establish the model, then compare the results. 2): To establish a continuous trust function, and couple it to the rumor propagation model, then make the analysis and discussion of the results.
ACKNOWLEDGEMENTS
This work was supported in part by the National Natural Science Foundation of China (No. 61170038, 61472231), the National Social Science Foundation of China (No. 14BTQ049), and a project of International Cooperation in Training of Excellent Backbone Teachers for Advanced University in Shandong Province.
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