Studying the co-evolution of information diffusion,vaccination behavior and disease transmission in multilayer networks with local and global effects

Today,with the rapid development of the internet,a large amount of information often accompanies the rapid transmission of disease outbreaks,and increasing numbers of scholars are studying the relationship between information and the disease transmission process using complex networks.In fact,the disease transmission process is very complex.Besides this information,there will often be individual behavioral measures and other factors to consider.Most of the previous research has aimed to establish a two-layer network model to consider the impact of information on the transmission process of disease,rarely divided into information and behavior,respectively.To carry out a more in-depth analysis of the disease transmission process and the intrinsic influencing mechanism,this paper divides information and behavior into two layers and proposes the establishment of a complex network to study the dynamic co-evolution of information diffusion,vaccination behavior,and disease transmission.This is achieved by considering four influential relationships between adjacent layers in multilayer networks.In the information layer,the diffusion process of negative information is described,and the feedback effects of local and global vaccination are considered.In the behavioral layer,an individual's vaccination behavior is described,and the probability of an individual receiving a vaccination is influenced by two factors:the influence of negative information,and the influence of local and global disease severity.In the disease layer,individual susceptibility is considered to be influenced by vaccination behavior.The state transition equations are derived using the micro Markov chain approach(MMCA),and disease prevalence thresholds are obtained.It is demonstrated through simulation experiments that the negative information diffusion is less influenced by local vaccination behavior,and is mainly influenced by global vaccination behavior;vaccination behavior is mainly influenced by local disease conditions,and is less influenced by global disease conditions;the disease transmission threshold increases with the increasing vaccination rate;and the scale of disease transmission increases with the increasing negative information diffusion rate and decreases with the increasing vaccination rate.Finally,it is found that when individual vaccination behavior considers both the influence of negative information and disease,it can increase the disease transmission threshold and reduce the scale of disease transmission.Therefore,we should resist the diffusion of negative information,increase vaccination proportions,and take appropriate protective measures in time.

Database Search Behaviors: Insight from a Survey of Information Retrieval Practices

This study examines the database search behaviors of individuals, focusing on gender differences and the impact of planning habits on information retrieval. Data were collected from a survey of 198 respondents, categorized by their discipline, schooling background, internet usage, and information retrieval preferences. Key findings indicate that females are more likely to plan their searches in advance and prefer structured methods of information retrieval, such as using library portals and leading university websites. Males, however, tend to use web search engines and self-archiving methods more frequently. This analysis provides valuable insights for educational institutions and libraries to optimize their resources and services based on user behavior patterns.

Influence of Information Technology on Social Spatial Behaviors of Urban Residents——Case of Nanjing City in China

Taking Nanjing as a case, the paper explains the spatial behavior differences existing in the information technology use among different groups of residents and households, by virtue of analyzing the survey data of urban households in the 11 districts of Nanjing, from the social, spatial, life and other non-technical angles. Also it makes various analyses and evaluation quantitatively and qualitatively on the social and spatial effect of information technology. The results show that the new technology is changing the social spatial behaviors of urban residents. New behavioral spaces of urban family such as telecommuting, email and QQ have begun to emerge. With the help of Internet, the communication scope of families has expanded greatly, and more new forms of publicizing community information have begun to emerge. Telecommunication contact forms have been developing swiftly, and their frequencies of contact have been increasing dramatically.

Social Network Information Propagation Model Based on Individual Behavior

In this paper, we discuss building an information dissemination model based on individual behavior. We analyze the individual behavior related to information dissemination and the factors that affect the sharing behavior of individuals, and we define and quantify these factors. We consider these factors as characteristic attributes and use a Bayesian classifier to classify individuals. Considering the forwarding delay characteristics of information dissemination, we present a random time generation method that simulates the delay of information dissemination. Given time and other constraints, a user might not look at all the information that his/her friends published. Therefore, this paper proposes an algorithm to predict information visibility, i.e., it estimates the probability that an individual will see the information. Based on the classification of individual behavior and combined with our random time generation and information visibility prediction method, we propose an information dissemination model based on individual behavior. The model can be used to predict the scale and speed of information propagation. We use data sets from Sina Weibo to validate and analyze the prediction methods of the individual behavior and information dissemination model based on individual behavior. A previously proposedinformation dissemination model provides the foundation for a subsequent study on the evolution of the network and social network analysis. Predicting the scale and speed of information dissemination can also be used for public opinion monitoring.

Effects of evacuation assistant's leading behavior on the evacuation efficiency: Information transmission approach

Evacuation assistants are expected to spread the escape route information and lead evacuees toward the exit as quickly as possible. Their leading behavior influences the evacuees＇ movement directly, which is confirmed to be a decisive factor of the evacuation efficiency. The transmission process of escape information and its function on the evacuees＇ movement are accurately presented by the proposed extended dynamic communication field model. For evacuation assistants and eevacuees, their sensitivity parameter of static floor field（SFF）, kL S, and kS, are fully discussed. The simulation results e indicate that the appropriate kL Sis associated with the maximum kSof evacuees. The optimal combinations of kL Sand e kSwere found to reach the highest evacuation efficiency. There also exists an optimal value for evacuation assistants＇ information transmission radius.

Research on the Model of Consumer Health Information Seeking Behavior via Social Media

Purpose: We aim to create a model of consumer health information seeking behavior via social media, then to have a better understand of it. After that further efforts should be made to provide targeted recommendations for media managers to promote health communication via social media. Methods: Our custom model was derived from literature review, empirical research was tested by the use of questionnaire investigation, and then the collected data were analyzed by structural equation model tool SmartPLS. Finally, the custom model was modified according to the experimental results of SmartPLS. Results: A total of 239 (66.39%) of the respondents were female and 121 (33.61%) were male. The maximum of two stages of age were 18 - 29 (70.56%), 30 - 39 (13.89%). Wechat (60.28%), QQ Zone (55.22%), Micro-blog (48.89%) were the most commonly used social media to obtain health information. About 44.72% of respondents used social media to obtain health information multiple times a day. The whole numerical values of AVE, cronbach’s alpha, CR and square roots of AVE were above the benchmarks of themselves and showed great reliability and validity. All the 11 hypotheses had obvious statistical significance, the P-value of eight path coefficients exhibited <0.001, one path coefficient exhibited <0.01 and two path coefficients exhibited <0.05. Conclusions: A suitable model of consumer health information seeking behavior via social media was created and some inner relationships were found. Namely, gratification of health information and its platform had a positive effect on attitudes toward health information seeking behavior. Health information literacy and health status were proved to have a significant influence on attitudes toward health information seeking behavior, subject norms and perceived behavioral control respectively. In addition, attitudes toward the health information seeking behavior, subject norms and perceived behavioral control were proved to positively associate with health information seeking behavior intention.

Developing the information-seeking behavior scale for undergraduates

Purpose: The aim of this paper is to develop a standardized and reliable measurement tool for assessing information-seeking behavior of undergraduate students.Design/methodology/approach: Based on information literacy and information-seeking behavior theories, expert advice and students' interview, items of undergraduates' informationseeking behavior indicators were selected. With the analysis of homogeneity reliability, item analysis and factor analysis, this study constructs an assessment system to evaluate reliability and validity of the scale.Findings: The information-seeking behavior scale for undergraduates has divided undergraduates' information-seeking behavior into seven dimensions, which include 46 items. The reliability analysis of Cronbach's α was 0.910, and the coefficient of split-half reliability was0.817. The results of factor analysis showed that Kaiser-Meyer-Olkin(KMO) was 0.864,which indicates 55.536% of the total variation could be explained by the above seven dimensions.Research limitations: Due to a small sample size and limited sample distribution, further research need be conducted in an expanded sample size in order to explore the application scope of this evaluation system; in addition, the stability of the scale also need be confirmed.Practical implications: The paper sets up an information-seeking behavior evaluation system for undergraduates and explores the characteristics of their information-seeking behavior.This study provides guidance for the development of future information literacy education and the improvement of the information literacy level of undergraduates.Originality/value: An information-seeking behavior scale for undergraduates has been developed, which comprehensively covers information need, information source, information evaluation, information retrieval, information management, information utilization and information morality. The scale is proved to have good reliability, validity, popularity anddiscrimination that it is qualified to be an assessment tool of information-seeking behavior for Chinese undergraduates.

Cluster DetectionMethod of Endogenous Security Abnormal Attack Behavior in Air Traffic Control Network

In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set for ATC cybersecurity attacks is constructed by setting the feature states,adding recursive features,and determining the feature criticality.The expected information gain and entropy of the feature data are computed to determine the information gain of the feature data and reduce the interference of similar feature data.An autoencoder is introduced into the AI(artificial intelligence)algorithm to encode and decode the characteristics of ATC network security attack behavior to reduce the dimensionality of the ATC network security attack behavior data.Based on the above processing,an unsupervised learning algorithm for clustering detection of ATC network security attacks is designed.First,determine the distance between the clustering clusters of ATC network security attack behavior characteristics,calculate the clustering threshold,and construct the initial clustering center.Then,the new average value of all feature objects in each cluster is recalculated as the new cluster center.Second,it traverses all objects in a cluster of ATC network security attack behavior feature data.Finally,the cluster detection of ATC network security attack behavior is completed by the computation of objective functions.The experiment took three groups of experimental attack behavior data sets as the test object,and took the detection rate,false detection rate and recall rate as the test indicators,and selected three similar methods for comparative test.The experimental results show that the detection rate of this method is about 98%,the false positive rate is below 1%,and the recall rate is above 97%.Research shows that this method can improve the detection performance of security attacks in air traffic control network.

AMachine Learning Approach to User Profiling for Data Annotation of Online Behavior

The user’s intent to seek online information has been an active area of research in user profiling.User profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and motivations.Determining user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content presentation.The user’s complete online experience in seeking information is a blend of activities such as searching,verifying,and sharing it on social platforms.However,a combination of multiple behaviors in profiling users has yet to be considered.This research takes a novel approach and explores user intent types based on multidimensional online behavior in information acquisition.This research explores information search,verification,and dissemination behavior and identifies diverse types of users based on their online engagement using machine learning.The research proposes a generic user profile template that explains the user characteristics based on the internet experience and uses it as ground truth for data annotation.User feedback is based on online behavior and practices collected by using a survey method.The participants include both males and females from different occupation sectors and different ages.The data collected is subject to feature engineering,and the significant features are presented to unsupervised machine learning methods to identify user intent classes or profiles and their characteristics.Different techniques are evaluated,and the K-Mean clustering method successfully generates five user groups observing different user characteristics with an average silhouette of 0.36 and a distortion score of 1136.Feature average is computed to identify user intent type characteristics.The user intent classes are then further generalized to create a user intent template with an Inter-Rater Reliability of 75%.This research successfully extracts different user types based on their preferences in online content,platforms,criteria,and frequency.The study also validates the proposed template on user feedback data through Inter-Rater Agreement process using an external human rater.

The Impact of Social Media on Dietary Behaviors and Body Image of College Students: A Qualitative Approach

Background: The use of social media platforms for health and nutrition information has become popular among college students. Although social media made information readily accessible in different formats, nutritional misinformation promoted by influencers and non-experts caused negative impact on diet behavior and perception of body image. Previous research indicated that extensive use of social media was positively linked to disordered eating behaviors. Social media platforms like Facebook and Instagram that allow users to follow celebrities intensified exposure to influencers’ messages and images and resulted in negative moods and body dissatisfaction. Objective: This paper aims to explore the impact of social media on college students’ dietary behaviors and body image. Participants: 18 undergraduate students from a public university in the Southern United States were recruited through a mass email. Methods: A cross-sectional qualitative study of three focus groups was conducted. The focus groups were based on guiding open-ended questions. Atlas.ti was used to code and analyze the data using inductive and deductive codes. Results: Three main themes were identified. The conditions theme included elements that explain why and how social media influences the participants’ actions. The actions theme included eating behavior, physical activity, and dietary supplement intake. The consequences theme describes anticipated or actual outcomes of actions such as body image and ideal weight. Conclusions: Social media has had a negative influence on diet behaviors and a positive influence on physical activity. Evidence-based nutrition and weight management information is needed to thwart potential misinformation.

Information behavior in the mobile environment:A study of undergraduate smartphone users in China

Purpose:As smartphones become ubiquitous,it is important to understand emerging information behavior as a result of wide spread use of smartphones.The purpose of this study is to investigate information behavior in the mobile environment by studying undergraduate smartphone users in China.Design/methodology/approach:This study is based on a survey of 205 undergraduate students in China.Findings:Smartphones are used predominantly for accessing news and connecting to social media,rather than for academic purposes such as accessing library resources or researching.While students use smartphones for reading e-books,much of this reading is recreational during their spare time.Research limitations:The inherent limitations of self-reported measures and the small sample size of this study mean that the results cannot be generalized across different age groups and cultures.Practical implications:When targeting users on the move,information professionals should be aware that the needs and behaviors of smartphone readers are significantly different compared to users of fixed devices,and should provide services in a mobile-friendly way.Originality/value:The younger generation is accustomed to instant information access.For libraries to relevant,they must redesign their services.It is important for libraries to leverage the strengths of mobile technology and to balance traditional services with mobile delivery.Even though many mobile users will use desktop or laptop computers to access library resources,they will benefit from the availability of mobile-friendly library services.

The relationship of Web2.0 technologies and information behavior

This paper discussed how Web 2.0 technologies relate to human’s information behavior.Firstly,an overview of information behavior is given by previous studies,meanwhile,which has found differences between information seeking and information searching.While featured web2.0-based tools improve user’s communication experience,especially reflecting on information seeking and information sharing.It is possible that web 2.0 applications provide an interactive platform to promote human’s information behavior effectively.

Method of Designing Generators of Pseudorandom Sequences for Information Protection Based on Shift Register with Non-Linear Feedback Function

This paper proposes an efficient, high-tech method of construction of pseudorandom binary sequences generators with a repetition period 2n?for n-bit shift register with a nonlinear feedback function. The developed method is illustrated by constructing a nonlinear function feedback shift register. It is proved that the offered method requires the realization of a memory size proportional to n2?that allows making successful use of suitable generators for practical use on the shift register of the longer word.

Understanding information seeking behavior of rural women:Field studies in China

Purpose:The purpose of this research is to investigate Chinese rural women’s information needs and information seeking behavior,with an emphasis on exploration of the intervening variables that influence information needs and information seeking behavior.Design/methodology/approach:The sample consisted of 27 women from 9 villages in Gansu Province,Anhui Province and Tianjin City,China.Data were collected through in-depth individual interview.Both quantitative and qualitative methods were employed to analyze the data.Findings:Chinese rural women’s needs are basically tied to agricultural technologies,employment and health information.Social network,rather than the Internet,serves as the most frequently used information channel.Women’s cognitive ability,social role and their living environment are the 3 intervening variables that have an impact on their information needs and their information seeking behavior.Research limitations:This qualitative research is based on a small sample and conducted on specific socio-economic settings in China,which may restrict the generalization and application of relevant findings in other settings and countries.Practical implications:The study results will help librarians and information professionals better understand Chinese rural women’s information needs and information seeking behavior in an effort to find ways to solve problems they may encounter in their information seeking process.Originality/value:This paper introduced an analysis framework that provides an integrated perspective on understanding information needs and information seeking behavior of Chinese women in rural areas.

Information behaviors of Chinese K-12physical education teachers:A survey study

Purpose: Given the unique characteristics of physical education(PE) teaching in K-12education,PE teachers' information behaviors deserve special attention.This article reports a survey study of PE teachers' information behaviors,covering information literacy skills and behaviors of information seeking and information use.Design/methodology/approach:A questionnaire survey was conducted of K-12 PE teachers in the Tianjin municipal region of China,with a response rate of 61.9%.Findings:PE teachers lack skills with information retrieval systems in general.The Internet continues to be their primary information source,and they rely more on personal collection and colleagues than the school library for teaching materials.They rarely develop a searching strategy,employ querying tactics,or use advanced search functions,and they tend to be content with finding a few relevant articles.Research limitations:The survey is limited to the Tianjin municipal region in scope.Though attempting to reach 210 participants from 40 schools,it yielded only 130 valid responses.A larger survey covering more regions and with greater responses may be useful.Practical implications:Insights from this study inform the educational and on-job training of K-12 PE teachers to improve their information literacy skills.Originality/value:Little research exists on PE teachers' behaviors of information seeking.This study bridges the gap and enriches our understanding of K-12 teachers' information behaviors.

Introduction to information seeking behavior—A review of literature and field practice directions

The article tries to discover the major authors in the field of information seeking behavior via social network analysis. It is to be accomplished through a literature review and also by focusing on a graphic map showing the seven most productive coauthors in this field. Based on these seven authors' work, five probable research directions about information seeking behavior are discerned and presented.

Collaborative information seeking: An investigation of community members' behavior

Purpose： This article reports on an experiment that tested community members＇ collaborative information seeking （CIS） behavior, with an emphasis on how community type and task difficulty can affect user behavior and user awareness in collaboration.Design/methodology/approach： We carried out a laboratory study with 18 participants in 9 pairs using an experimental CIS system. Data were collected from questionnaires, Web logs and semi-structured interviews. Descriptive statistics and two-way analysis of variance （ANOVA） were used for data analysis. Findings： Compared with non-community members, community participants had a better understanding of search tasks and were aware of the ways of completing tasks successfully. They did not depend on the information retrieval system when constructing search queries and would adopt diversified cooperation strategies. They were more likely to recommend information to their partners. However, no significant difference was found between subject- based community and interest-based community in CIS practices and user awareness in collaboration. In addition, task difficulty only influenced user preference of issuing queries and confidence of completing search tasks. Research limitations： Our work was limited by the community type we chose and the small group size, which could affect the generalizability of our findings and should be addressed in future studies. Practical implications： The study results will help inform information system designers as they design collaborative systems to facilitate social communication in the information seeking process. Originality/value： Few studies have investigated community participants＇ information seeking practices. This study provides insights into community-based CIS behavior. The findings will help us understand social interactions among community members during their information seeking process.

An initial study of information seeking behavior of researchers as faculty/student team members

Purpose:This study was carried out to uncover the characteristics of information seeking behavior of researchers as faculty/student team members.Design/methodology/approach:An inventory encompassing 6 dimensions of information seeking behavior was developed:Information awareness,information acquisition,information evaluation,information organization and management,information utilization and information ethics.Data was collected on 306 respondents from 52 faculty/student teams in Central South University in China and analyzed using SPSS 18.0 software.Findings:Significant differences were found among researchers with different genders in information awareness and in different academic disciplines in information acquisition and information utilization.The survey shows the characteristics of information seeking behavior of different gender groups and different teams:1) male participants got higher scores in all of the 6 dimensions of information seeking behavior;2) small teams performed best,followed by middle-sized teams and large teams;3) faculty/doctoral student teams possessed better information seeking skills than faculty/master’s student teams or faculty/doctoral and master’s student teams:4) medical teams achieved the highest level in all of the 6 dimensions of information seeking behavior,whereas natural science teams the lowest level.Medical and engineering teams were rated higher than other teams in information acquisition and information utilization.Research limitations:The small population size and doctoral students accounting for only a small portion of the respondents in the sample limit the generalization of our findings.Practical implications:The findings of this study have some implications for research and practice,especially for educational institutions,library science and information literacy training.Originality/value:This paper is the first to describe and analyze the characteristics of information seeking behavior of researchers as faculty/student team members.

An empirical study of everyday life information seeking behavior of urban low-income residents in the Haizhu District of Guangzhou, China

This paper reports an investigation on everyday life information seeking behavior of urban low-income group in the Haizhu District of Guangzhou City. Empirical data were collected via in-depth interviews with low-income urban residents and were analyzed using qualitative methods. This paper discusses the research findings based on the more noticeable results of information seeking behavior among these people. Our approach touches on a focused study of such issues as what the role of information seeking in their everyday life is, what information they care about, which information channels they prefer to use, which factors influence their information seeking behavior, how difficult it is to seek the information they need, and how they use public libraries. Based on our research findings, we propose that public libraries should provide customized information services for urban low-income residents according to the unique characteristics of their information seeking behavior in everyday life.

Subtle role of latency for information diffusion in online social networks

Information diffusion in online social networks is induced by the event of forwarding information for users, and latency exists widely in user spreading behaviors. Little work has been done to reveal the effect of latency on the diffusion process. In this paper, we propose a propagation model in which nodes may suspend their spreading actions for a waiting period of stochastic length. These latent nodes may recover their activity again. Meanwhile, the mechanism of forwarding information is also introduced into the diffusion model. Mean-field analysis and numerical simulations indicate that our model has three nontrivial results. First, the spreading threshold does not correlate with latency in neither homogeneous nor heterogeneous networks, but depends on the spreading and refractory parameter. Furthermore, latency affects the diffusion process and changes the infection scale. A large or small latency parameter leads to a larger final diffusion extent, but the intrinsic dynamics is different. Large latency implies forwarding information rapidly, while small latency prevents nodes from dropping out of interactions. In addition, the betweenness is a better descriptor to identify influential nodes in the model with latency, compared with the coreness and degree. These results are helpful in understanding some collective phenomena of the diffusion process and taking measures to restrain a rumor in social networks.