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CRB:A new rumor blocking algorithm in online social networks based on competitive spreading model and influence maximization
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作者 董晨 徐桂琼 孟蕾 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第8期588-604,共17页
The virtuality and openness of online social platforms make networks a hotbed for the rapid propagation of various rumors.In order to block the outbreak of rumor,one of the most effective containment measures is sprea... The virtuality and openness of online social platforms make networks a hotbed for the rapid propagation of various rumors.In order to block the outbreak of rumor,one of the most effective containment measures is spreading positive information to counterbalance the diffusion of rumor.The spreading mechanism of rumors and effective suppression strategies are significant and challenging research issues.Firstly,in order to simulate the dissemination of multiple types of information,we propose a competitive linear threshold model with state transition(CLTST)to describe the spreading process of rumor and anti-rumor in the same network.Subsequently,we put forward a community-based rumor blocking(CRB)algorithm based on influence maximization theory in social networks.Its crucial step is to identify a set of influential seeds that propagate anti-rumor information to other nodes,which includes community detection,selection of candidate anti-rumor seeds and generation of anti-rumor seed set.Under the CLTST model,the CRB algorithm has been compared with six state-of-the-art algorithms on nine online social networks to verify the performance.Experimental results show that the proposed model can better reflect the process of rumor propagation,and review the propagation mechanism of rumor and anti-rumor in online social networks.Moreover,the proposed CRB algorithm has better performance in weakening the rumor dissemination ability,which can select anti-rumor seeds in networks more accurately and achieve better performance in influence spread,sensitivity analysis,seeds distribution and running time. 展开更多
关键词 online social networks rumor blocking competitive linear threshold model influence maximization
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Influencer identification of dynamical networks based on an information entropy dimension reduction method
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作者 段东立 纪思源 袁紫薇 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第4期375-384,共10页
Identifying critical nodes or sets in large-scale networks is a fundamental scientific problem and one of the key research directions in the fields of data mining and network science when implementing network attacks,... Identifying critical nodes or sets in large-scale networks is a fundamental scientific problem and one of the key research directions in the fields of data mining and network science when implementing network attacks, defense, repair and control.Traditional methods usually begin from the centrality, node location or the impact on the largest connected component after node destruction, mainly based on the network structure.However, these algorithms do not consider network state changes.We applied a model that combines a random connectivity matrix and minimal low-dimensional structures to represent network connectivity.By using mean field theory and information entropy to calculate node activity,we calculated the overlap between the random parts and fixed low-dimensional parts to quantify the influence of node impact on network state changes and ranked them by importance.We applied this algorithm and the proposed importance algorithm to the overall analysis and stratified analysis of the C.elegans neural network.We observed a change in the critical entropy of the network state and by utilizing the proposed method we can calculate the nodes that indirectly affect muscle cells through neural layers. 展开更多
关键词 dynamical networks network influencer low-dimensional dynamics network disintegration
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The Research on Social Networks Public Opinion Propagation Influence Models and Its Controllability 被引量:9
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作者 Lejun Zhang Tong Wang +3 位作者 Zilong Jin Nan Su Chunhui Zhao Yongjun He 《China Communications》 SCIE CSCD 2018年第7期98-110,共13页
Public opinion propagation control is one of the hot topics in contemporary social network research. With the rapid dissemination of information over the Internet, the traditional isolation and vaccination strategies ... Public opinion propagation control is one of the hot topics in contemporary social network research. With the rapid dissemination of information over the Internet, the traditional isolation and vaccination strategies can no longer achieve satisfactory results. A positive guidance technology for public opinion diffusion is urgently needed. First, based on the analysis of influence network controllability and public opinion diffusion, a positive guidance technology is proposed and a new model that supports external control is established. Second, in combination with the influence network, a public opinion propagation influence network model is designed and a public opinion control point selection algorithm(POCDNSA) is proposed. Finally, An experiment verified that this algorithm can lead to users receiving the correct guidance quickly and accurately, reducing the impact of false public opinion information; the effect of CELF is no better than that of the POCDNSA algorithm. The main reason is that the former is completely based on the diffusion cascade information contained in the training data, but does not consider the specific situation of the network structure and the diffusion of public opinion information in the closed set. thus, the effectiveness and feasibility of the algorithm is proven. The findings of this article therefore provide useful insights for the implementation of public opinion control. 展开更多
关键词 social network public opinion propagation control influence network
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Genetic Determination and Exogenous Influence in Sex Differentiation in Crustacean 被引量:4
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作者 吴长功 相建海 《Developmental and Reproductive Biology》 2002年第2期137-144,共8页
The mechanisms of sex determination and the influence of exogenous factors on sex differentiation in crustacean were reviewed in the paper.Most of crustecea have not obviously sex chromosome.Androgenic gland was repor... The mechanisms of sex determination and the influence of exogenous factors on sex differentiation in crustacean were reviewed in the paper.Most of crustecea have not obviously sex chromosome.Androgenic gland was reported as the most important sex differentiation factors,implanting or cuting AG can change the sexal characterization of larval in crustacean.Although sex differentiation of crustacean is determined by gene,it is affected by exogenous factors such as parasite,photoperiod,temperature or hormone.Most cultured species have different body weight and length between male and female,this can be used in aquaculture to produce all male or female crusteceans to improve the production. 展开更多
关键词 genetic determination exogenous influence sex differentiation CRUSTACEAN
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Recent Advances in the Modelling and Analysis of Opinion Dynamics on Influence Networks 被引量:14
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作者 Brian D.O.Anderson Mengbin Ye 《International Journal of Automation and computing》 EI CSCD 2019年第2期129-149,共21页
A fundamental aspect of society is the exchange and discussion of opinions between individuals, occurring in situations as varied as company boardrooms, elementary school classrooms and online social media. After a ve... A fundamental aspect of society is the exchange and discussion of opinions between individuals, occurring in situations as varied as company boardrooms, elementary school classrooms and online social media. After a very brief introduction to the established results of the most fundamental opinion dynamics models, which seek to mathematically capture observed social phenomena, a brief discussion follows on several recent themes pursued by the authors building on the fundamental ideas. In the first theme, we study the way an individual′s self-confidence can develop through contributing to discussions on a sequence of topics, reaching a consensus in each case,where the consensus value to some degree reflects the contribution of that individual to the conclusion. During this process, the individuals in the network and the way they interact can change. The second theme introduces a novel discrete-time model of opinion dynamics to study how discrepancies between an individual′s expressed and private opinions can arise due to stubbornness and a pressure to conform to a social norm. It is also shown that a few extremists can create "pluralistic ignorance", where people believe there is majority support for a position but in fact the position is privately rejected by the majority. Last, we consider a group of individuals discussing a collection of logically related topics. In particular, we identify that for topics whose logical interdependencies take on a cascade structure,disagreement in opinions can occur if individuals have competing and/or heterogeneous views on how the topics are related, i.e., the logical interdependence structure varies between individuals. 展开更多
关键词 OPINION dynamics social netWORKS influence netWORKS AGENT-BASED models multi-agent SYSTEMS netWORKED SYSTEMS
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Mining Topical Influencers Based on the Multi-Relational Network in Micro-Blogging Sites 被引量:4
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作者 丁兆云 贾焰 +1 位作者 周斌 韩毅 《China Communications》 SCIE CSCD 2013年第1期93-104,共12页
In micro-blogging contexts such as Twitter,the number of content producers can easily reach tens of thousands,and many users can participate in discussion of any given topic.While many users can introduce diversity,as... In micro-blogging contexts such as Twitter,the number of content producers can easily reach tens of thousands,and many users can participate in discussion of any given topic.While many users can introduce diversity,as not all users are equally influential,it makes it challenging to identify the true influencers,who are generally rated as being interesting and authoritative on a given topic.In this study,the influence of users is measured by performing random walks of the multi-relational data in micro-blogging:retweet,reply,reintroduce,and read.Due to the uncertainty of the reintroduce and read operations,a new method is proposed to determine the transition probabilities of uncertain relational networks.Moreover,we propose a method for performing the combined random walks for the multi-relational influence network,considering both the transition probabilities for intra-and inter-networking.Experiments were conducted on a real Twitter dataset containing about 260 000 users and 2.7million tweets,and the results show that our method is more effective than TwitterRank and other methods used to discover influencers. 展开更多
关键词 social network topical influence PAGERANK multi-relational network influencers micro-blogging
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A New Evaluation Algorithm for the Influence of User in Social Network 被引量:6
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作者 JIANG Wei GAO Mengdi +1 位作者 WANG Xiaoxi WU Xianda 《China Communications》 SCIE CSCD 2016年第2期200-206,共7页
Online social networks have gradually permeated into every aspect of people's life.As a research hotspot in social network, user influence is of theoretical and practical significant for information transmission, ... Online social networks have gradually permeated into every aspect of people's life.As a research hotspot in social network, user influence is of theoretical and practical significant for information transmission, optimization and integration. A prominent application is a viral marketing campaign which aims to use a small number of targeted infl uence users to initiate cascades of infl uence that create a global increase in product adoption. In this paper, we analyze mainly evaluation methods of user infl uence based on IDM evaluation model, Page Rank evaluation model, use behavior model and some other popular influence evaluation models in currently social network. And then, we extract the core idea of these models to build our influence evaluation model from two aspects, relationship and activity. Finally, the proposed approach was validated on real world datasets,and the result of experiments shows that our method is both effective and stable. 展开更多
关键词 social networks influence opinionleaders
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Identifying influential nodes in social networks via community structure and influence distribution difference 被引量:3
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作者 Zufan Zhang Xieliang Li Chenquan Gan 《Digital Communications and Networks》 SCIE CSCD 2021年第1期131-139,共9页
This paper aims to effectively solve the problem of the influence maximization in social networks.For this purpose,an influence maximization method that can identify influential nodes via the community structure and t... This paper aims to effectively solve the problem of the influence maximization in social networks.For this purpose,an influence maximization method that can identify influential nodes via the community structure and the influence distribution difference is proposed.Firstly,the network embedding-based community detection approach is developed,by which the social network is divided into several high-quality communities.Secondly,the solution of influence maximization is composed of the candidate stage and the greedy stage.The candidate stage is to select candidate nodes from the interior and the boundary of each community using a heuristic algorithm,and the greedy stage is to determine seed nodes with the largest marginal influence increment from the candidate set through the sub-modular property-based Greedy algorithm.Finally,experimental results demonstrate the superiority of the proposed method compared with existing methods,from which one can further find that our work can achieve a good tradeoff between the influence spread and the running time. 展开更多
关键词 Social network Community detection influence maximization network embedding influence distribution difference
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Analysis of User's Weight in Microblog Network Based on User Influence and Active Degree 被引量:3
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作者 Jie Lian Yun Liu +2 位作者 Zhen-Jiang Zhang Jun-Jun Cheng Fei Xiong 《Journal of Electronic Science and Technology》 CAS 2012年第4期368-377,共10页
Based on user's in-degree distribution, traditional ranking algorithms of user's weight usually neglect the considerations of the differences among user's followers and the features of user's tweets. In order to a... Based on user's in-degree distribution, traditional ranking algorithms of user's weight usually neglect the considerations of the differences among user's followers and the features of user's tweets. In order to analyze the factors which impact on user's weight, under the analysis of the data collected from SINA Microblog network, this paper discovers that user influence and active degrees are the dominant factors for this issue. The proposed algorithm evaluates user influence by user's follower number, the influence of user's followers and the reciprocity between users. User's active degree is modeled by user's participation and the quality of user's tweets. The models are tested by different data groups to confirm the parameters for the final calculation. Eventually, this paper compares the computational results with the user's ranking order given by the SINA official application. The performance of this algorithm presents a stronger stability on the fluctuant range of the value of user's weight. 展开更多
关键词 HITS algorithm SINA Microblog user influence user rank.
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Theoretical Investigation of Influence of Mechanical Stress on Magnetic Properties of Ferromagnetic/Antiferromagnetic Bilayers Deposited on Flexible Substrates 被引量:1
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作者 白宇浩 王霞 +1 位作者 穆林平 许小红 《Chinese Physics Letters》 SCIE CAS CSCD 2016年第8期118-122,共5页
Effect of mechanical stress on magnetic properties of an exchange-biased ferromagnetic/antiferromagnetic bilayer deposited on a flexible substrate is investigated. The hysteresis loops with different magnitudes and or... Effect of mechanical stress on magnetic properties of an exchange-biased ferromagnetic/antiferromagnetic bilayer deposited on a flexible substrate is investigated. The hysteresis loops with different magnitudes and orientations of the stress can be classified into three types. The corresponding physical conditions for each type of the loop are deduced based on the principle of minimal energy. The equation of the critical stress is derived, which can judge whether the loops show hysteresis or not. Numerical calculations suggest that except for the magnitude of the mechanical stress, the relative orientation of the stress is also an important factor to tune the exchange bias effect. 展开更多
关键词 of for Theoretical Investigation of influence of Mechanical Stress on Magnetic Properties of Ferromagnetic/Antiferromagnetic Bilayers Deposited on Flexible Substrates is been on from that into
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Influence fast or later:Two types of influencers in social networks 被引量:1
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作者 Fang Zhou Chang Su +1 位作者 Shuqi Xu Linyuan Lv 《Chinese Physics B》 SCIE EI CAS CSCD 2022年第6期46-55,共10页
In real-world networks,there usually exist a small set of nodes that play an important role in the structure and function of networks.Those vital nodes can influence most of other nodes in the network via a spreading ... In real-world networks,there usually exist a small set of nodes that play an important role in the structure and function of networks.Those vital nodes can influence most of other nodes in the network via a spreading process.While most of the existing works focused on vital nodes that can maximize the spreading size in the final stage,which we call final influencers,recent work proposed the idea of fast influencers,which emphasizes nodes’spreading capacity at the early stage.Despite the recent surge of efforts in identifying these two types of influencers in networks,there remained limited research on untangling the differences between the fast influencers and final influencers.In this paper,we firstly distinguish the two types of influencers:fast-only influencers and final-only influencers.The former is defined as individuals who can achieve a high spreading effect at the early stage but lose their superiority in the final stage,and the latter are those individuals that fail to exhibit a prominent spreading performance at the early stage but influence a large fraction of nodes at the final stage.Further experiments are based on eight empirical datasets,and we reveal the key differences between the two types of influencers concerning their spreading capacity and the local structures.We also analyze how network degree assortativity influences the fraction of the proposed two types of influencers.The results demonstrate that with the increase of degree assortativity,the fraction of the fast-only influencers decreases,which indicates that more fast influencers tend to keep their superiority at the final stage.Our study provides insights into the differences and evolution of different types of influencers and has important implications for various empirical applications,such as advertisement marketing and epidemic suppressing. 展开更多
关键词 social networks fast influencers final influencers spreading dynamics degree assortativity
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Influence of obstacle on electromagnetic wave propagation in evaporation duct with experiment verification 被引量:1
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作者 史阳 杨坤德 +1 位作者 杨益新 马远良 《Chinese Physics B》 SCIE EI CAS CSCD 2015年第5期323-328,共6页
In this paper, the influence of obstacle on electromagnetic wave propagation in an evaporation duct is investigated, both from numerical simulation and experimental observation. A comparison of electromagnetic wave pr... In this paper, the influence of obstacle on electromagnetic wave propagation in an evaporation duct is investigated, both from numerical simulation and experimental observation. A comparison of electromagnetic wave propagation in evaporation duct with and without obstacle for a typical case is presented. The presence of obstacle causes a significant increase in path loss. The obstacle has significant impact on electromagnetic wave propagation when the frequency is higher than 5 GHz and when the evaporation duct height is higher than 10 m. The influence of an island on electromagnetic wave propagation was observed in the experiment held in the South China Sea, October 2012. The experiment result shows that the island causes about 30-40 dB increase in path loss. The discrepancy between model and measurement is analyzed and the errors of transmitting antenna height and relative humidity are the possible causes of the discrepancy. 展开更多
关键词 evaporation duct influence of obstacle electromagnetic wave propagation evaporation duct experiment
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A Positive Influence Maximization Algorithm in Signed Social Networks 被引量:1
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作者 Wenlong Zhu Yang Huang +2 位作者 Shuangshuang Yang Yu Miao Chongyuan Peng 《Computers, Materials & Continua》 SCIE EI 2023年第8期1977-1994,共18页
The influence maximization(IM)problem aims to find a set of seed nodes that maximizes the spread of their influence in a social network.The positive influence maximization(PIM)problem is an extension of the IM problem... The influence maximization(IM)problem aims to find a set of seed nodes that maximizes the spread of their influence in a social network.The positive influence maximization(PIM)problem is an extension of the IM problem,which consider the polar relation of nodes in signed social networks so that the positive influence of seeds can be the most widely spread.To solve the PIM problem,this paper proposes the polar and decay related independent cascade(IC-PD)model to simulate the influence propagation of nodes and the decay of information during the influence propagation in signed social networks.To overcome the low efficiency of the greedy based algorithm,this paper defines the polar reverse reachable(PRR)set and devises a signed reverse influence sampling(SRIS)algorithm.The algorithm utilizes the ICPD model as well as the PRR set to select seeds.There are two phases in SRIS.One is the sampling phase,which utilizes the IC-PD model to generate the PRR set and a binary search algorithm to calculate the number of needed PRR sets.The other is the node selection phase,which uses a greedy coverage algorithm to select optimal seeds.Finally,Experiments on three real-world polar social network datasets demonstrate that SRIS outperforms the baseline algorithms in effectiveness.Especially on the Slashdot dataset,SRIS achieves 24.7% higher performance than the best-performing compared algorithm under the weighted cascade model when the seed set size is 25. 展开更多
关键词 Positive influencemaximization polar relation information decay reverse influence sampling
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An Influence Maximization Algorithm Based on Improved K-Shell in Temporal Social Networks 被引量:1
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作者 Wenlong Zhu Yu Miao +2 位作者 Shuangshuang Yang Zuozheng Lian Lianhe Cui 《Computers, Materials & Continua》 SCIE EI 2023年第5期3111-3131,共21页
Influence maximization of temporal social networks(IMT)is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread.To solve the IMT ... Influence maximization of temporal social networks(IMT)is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread.To solve the IMT problem,we propose an influence maximization algorithm based on an improved K-shell method,namely improved K-shell in temporal social networks(KT).The algorithm takes into account the global and local structures of temporal social networks.First,to obtain the kernel value Ks of each node,in the global scope,it layers the network according to the temporal characteristic of nodes by improving the K-shell method.Then,in the local scope,the calculation method of comprehensive degree is proposed to weigh the influence of nodes.Finally,the node with the highest comprehensive degree in each core layer is selected as the seed.However,the seed selection strategy of KT can easily lose some influential nodes.Thus,by optimizing the seed selection strategy,this paper proposes an efficient heuristic algorithm called improved K-shell in temporal social networks for influence maximization(KTIM).According to the hierarchical distribution of cores,the algorithm adds nodes near the central core to the candidate seed set.It then searches for seeds in the candidate seed set according to the comprehensive degree.Experiments showthatKTIMis close to the best performing improved method for influence maximization of temporal graph(IMIT)algorithm in terms of effectiveness,but runs at least an order of magnitude faster than it.Therefore,considering the effectiveness and efficiency simultaneously in temporal social networks,the KTIM algorithm works better than other baseline algorithms. 展开更多
关键词 Temporal social network influence maximization improved K-shell comprehensive degree
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Mathematical Modeling in Social Network Analysis: Using TOPSIS to Find Node Influences in a Social Network 被引量:4
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作者 William P Fox Sean F. Everton 《Journal of Mathematics and System Science》 2013年第10期531-541,共11页
In a social network analysis the output provided includes many measures and metrics. For each of these measures and metric, the output provides the ability to obtain a rank ordering of the nodes in terms of these meas... In a social network analysis the output provided includes many measures and metrics. For each of these measures and metric, the output provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning disrupting or deceiving a given network. All is fine when all the measures indicate the same node as the key or influential node. What happens when the measures indicate different key nodes? Our goal in this paper is to explore two methodologies to identify the key players or nodes in a given network. We apply TOPSIS to analyze these outputs to find the most influential nodes as a function of the decision makers' inputs as a process to consider both subjective and objectives inputs through pairwise comparison matrices. We illustrate our results using two common networks from the literature: the Kite network and the Information flow network from Knoke and Wood. We discuss some basic sensitivity analysis can may be applied to the methods. We find the use of TOPSIS as a flexible method to weight the criterion based upon the decision makers' inputs or the topology of the network. 展开更多
关键词 Social network analysis multi-attribute decision making Analytical hierarchy process (AHP) weighted criterion TOPSIS node influence
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The Influence of the Exchange-Correlation Functional on the Non-Interacting Kinetic Energy and Its Implications for Orbital-Free Density Functional Approximations
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作者 FINZEL Kati BULTINCK Patrick 《物理化学学报》 SCIE CAS CSCD 北大核心 2018年第6期650-655,共6页
In this work it is shown that the kinetic energy and the exchange-correlation energy are mutual dependent on each other.This aspect is first derived in an orbital-free context.It is shown that the total Fermi potentia... In this work it is shown that the kinetic energy and the exchange-correlation energy are mutual dependent on each other.This aspect is first derived in an orbital-free context.It is shown that the total Fermi potential depends on the density only,the individual parts,the Pauli kinetic energy and the exchange-correlation energy,however,are orbital dependent and as such mutually influence each other.The numerical investigation is performed for the orbital-based non-interacting Kohn-Sham system in order to avoid additional effects due to further approximations of the kinetic energy.The numerical influence of the exchange-correlation functional on the non-interacting kinetic energy is shown to be of the orderof a few Hartrees.For chemical purposes,however,the energetic performance as a function of the nuclear coordinates is much more important than total energies.Therefore,the effect on the bond dissociation curve was studied exemplarily for the carbon monoxide.The data reveals that,the mutual influence between the exchange-correlation functional and the kinetic energy has a significant influence on bond dissociation energies and bond distances.Therefore,the effect of the exchange-correlation treatment must be considered in the design of orbital-free density functional approximations for the kinetic energy. 展开更多
关键词 The influence of the EXCHANGE-CORRELATION FUNCTIONAL the Non-Interacting Kinetic Energy Density FUNCTIONAL APPROXIMATIONS
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Coupled multiphysical model for investigation of influence factors in the application of microbially induced calcite precipitation 被引量:1
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作者 Xuerui Wang Pavan Kumar Bhukya +1 位作者 Dali Naidu Arnepalli Shuang Chen 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第6期2232-2249,共18页
The study presents a comprehensive coupled thermo-bio-chemo-hydraulic(T-BCH)modeling framework for stabilizing soils using microbially induced calcite precipitation(MICP).The numerical model considers relevant multiph... The study presents a comprehensive coupled thermo-bio-chemo-hydraulic(T-BCH)modeling framework for stabilizing soils using microbially induced calcite precipitation(MICP).The numerical model considers relevant multiphysics involved in MICP,such as bacterial ureolytic activities,biochemical reactions,multiphase and multicomponent transport,and alteration of the porosity and permeability.The model incorporates multiphysical coupling effects through well-established constitutive relations that connect parameters and variables from different physical fields.It was implemented in the open-source finite element code OpenGeoSys(OGS),and a semi-staggered solution strategy was designed to solve the couplings,allowing for flexible model settings.Therefore,the developed model can be easily adapted to simulate MICP applications in different scenarios.The numerical model was employed to analyze the effect of various factors,including temperature,injection strategies,and application scales.Besides,a TBCH modeling study was conducted on the laboratory-scale domain to analyze the effects of temperature on urease activity and precipitated calcium carbonate.To understand the scale dependency of MICP treatment,a large-scale heterogeneous domain was subjected to variable biochemical injection strategies.The simulations conducted at the field-scale guided the selection of an injection strategy to achieve the desired type and amount of precipitation.Additionally,the study emphasized the potential of numerical models as reliable tools for optimizing future developments in field-scale MICP treatment.The present study demonstrates the potential of this numerical framework for designing and optimizing the MICP applications in laboratory-,prototype-,and field-scale scenarios. 展开更多
关键词 MULTIPHYSICS Microbially induced calcite precipitation(MICP) Coupled thermo-bio-chemo-hydraulic(TBCH) model OpenGeoSys(OGS) influence factors
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Hydrolysis kinetics of atrazine and influence factors
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作者 LEI Zhi-fang YE Chang-ming WANG Xing-jun 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2001年第1期99-103,共5页
The hydrolysis kinetics of atrazine in distilled water and leaching water from soil, and they influence factors were studied by incubation at 35degreesC and HPLC analysis method. The kinetic process of atrazine hydrol... The hydrolysis kinetics of atrazine in distilled water and leaching water from soil, and they influence factors were studied by incubation at 35degreesC and HPLC analysis method. The kinetic process of atrazine hydrolysis can be described by the first-order reaction law. The results showed that the hydrolysis rate constants k in leaching water and distilled water were 1.606 x 10(-3)/d and 1.055 x 10(-3)/d, respectively; the half-life of atrazine hydrolysis in distilled water at pH 3, pH 4.5 and pH 8 were 373 days, 522 days and 657 days respectively. The results also showed that the proton in reaction solution can catalyze the atrazine hydrolysis; humic acid and NH4+ etc. substances in aqueous solution can facilitate atrazine hydrolysis; rate constants of atrazine hydrolysis with humic acid and NH4NO3 were 2.431 X 10(-3)/d and 1.498 X 10(-3)/d respectively which were 2.3 and 1.42 times of control(1.055 X 10(-3)/d); anion NO3- can inhibit catalysis of humic acid to atrazine hydrolysis. 展开更多
关键词 ATRAZINE hydrolysis kinetics influence factors
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Maximizing Influence in Temporal Social Networks:A Node Feature-Aware Voting Algorithm
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作者 Wenlong Zhu Yu Miao +2 位作者 Shuangshuang Yang Zuozheng Lian Lianhe Cui 《Computers, Materials & Continua》 SCIE EI 2023年第12期3095-3117,共23页
Influence Maximization(IM)aims to select a seed set of size k in a social network so that information can be spread most widely under a specific information propagation model through this set of nodes.However,most exi... Influence Maximization(IM)aims to select a seed set of size k in a social network so that information can be spread most widely under a specific information propagation model through this set of nodes.However,most existing studies on the IM problem focus on static social network features,while neglecting the features of temporal social networks.To bridge this gap,we focus on node features reflected by their historical interaction behavior in temporal social networks,i.e.,interaction attributes and self-similarity,and incorporate them into the influence maximization algorithm and information propagation model.Firstly,we propose a node feature-aware voting algorithm,called ISVoteRank,for seed nodes selection.Specifically,before voting,the algorithm sets the initial voting ability of nodes in a personalized manner by combining their features.During the voting process,voting weights are set based on the interaction strength between nodes,allowing nodes to vote at different extents and subsequently weakening their voting ability accordingly.The process concludes by selecting the top k nodes with the highest voting scores as seeds,avoiding the inefficiency of iterative seed selection in traditional voting-based algorithms.Secondly,we extend the Independent Cascade(IC)model and propose the Dynamic Independent Cascade(DIC)model,which aims to capture the dynamic features in the information propagation process by combining node features.Finally,experiments demonstrate that the ISVoteRank algorithm has been improved in both effectiveness and efficiency compared to baseline methods,and the influence spread through the DIC model is improved compared to the IC model. 展开更多
关键词 Temporal social networks influence maximization voting strategy interactive properties SELF-SIMILARITY
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Influence Diffusion Model in Multiplex Networks
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作者 Senbo Chen Wenan Tan 《Computers, Materials & Continua》 SCIE EI 2020年第7期345-358,共14页
The problem of influence maximizing in social networks refers to obtaining a set of nodes of a specified size under a specific propagation model so that the aggregation of the node-set in the network has the greatest ... The problem of influence maximizing in social networks refers to obtaining a set of nodes of a specified size under a specific propagation model so that the aggregation of the node-set in the network has the greatest influence.Up to now,most of the research has tended to focus on monolayer network rather than on multiplex networks.But in the real world,most individuals usually exist in multiplex networks.Multiplex networks are substantially different as compared with those of a monolayer network.In this paper,we integrate the multi-relationship of agents in multiplex networks by considering the existing and relevant correlations in each layer of relationships and study the problem of unbalanced distribution between various relationships.Meanwhile,we measure the distribution across the network by the similarity of the links in the different relationship layers and establish a unified propagation model.After that,place on the established multiplex network propagation model,we propose a basic greedy algorithm on it.To reduce complexity,we combine some of the characteristics of triggering model into our algorithm.Then we propose a novel MNStaticGreedy algorithm which is based on the efficiency and scalability of the StaticGreedy algorithm.Our experiments show that the novel model and algorithm are effective,efficient and adaptable. 展开更多
关键词 StaticGreedy social networks influence maximization multiplex networks
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