Spread Of Information Research Articles

Tell me what to do first: how behavioural skills drive users’ intention to adopt online health information

PurposeTo gain a deeper understanding of users’ health information adoption and to promote the effectiveness of health information spread in the context of online limited information, this paper aims to examine how the information-motivation-behavioural (IMB) skills model can be used to organize online health information by experimenting how different IMB elements (information, motivation and behavioural skills) affect users’ intention to adopt health information.Design/methodology/approachThe authors conducted an experiment with 48 participants who received health articles with various combinations and sequences of IMB elements, analysing the impact on information adoption intention to share and practice. The authors also examined the mediation effect of information usefulness and the moderating effect of perceived health status.FindingsThe authors found that: users’ adoption intention of information was influenced by the order of used IMB elements, not the number of elements used; users were more likely to adopt information that started with behavioural skills rather than the model-prescribed IMB sequence; and perceived usefulness mediated the relationship between IMB elements and users’ adoption intention, which means users with different levels of health status all pay more attention to information usefulness and practicability.Originality/valueThe study contributes to research on health communication by showing how the IMB model can be applied online to enhance the effectiveness of health information dissemination. It can also help online health communities arrange more effective and engaging health messages to promote users’ willingness to adopt.

PENERAPAN PRINSIP DEMOKRASI DALAM SISTEM PEMILIHAN UMUM DI INDONESIA PERSPEKTIF FIQH SIYASAH

Since the reform era began in 1998 in Indonesia, political transformation has been significant. This period not only marked the end of the authoritarian government under President Soeharto, but also paved the way for changes in the political and constitutional system in Indonesia. This change not only changes the way of life of the people, but also changes the constitutional system of the Indonesian nation through amendments to the 1945 Constitution of the Republic of Indonesia. Article 1 paragraph (2) of the 1945 Constitution reads, "Sovereignty is in the hands of the people and is implemented according to the Constitution. In the Indonesian state administration there are also Islamic constitutional values, this can be seen by the concept of deliberation, equality and justice which is running as it should. This research aims to review the application of democratic principles in general elections and how Islamic state administration is reviewed (fiqh siyasah ) in the implementation of general elections in Indonesia. Through a normative juridical approach, this research analyzes the regulations governing the democracy and election system in Indonesia, including the 1945 Constitution and the Election Law. Research highlights the importance of implementing democratic principles such as popular sovereignty, equal rights, free and secret elections, and accountability and transparency in the electoral process. However, challenges such as money politics, identity politics and the spread of false information are still problems in the implementation of elections. This research suggests steps to improve the electoral system to ensure that democracy can function effectively and produce results that are more representative of the will of the people and that it is in accordance with Islamic constitutional principles (fiqh siyasah)

Modelling co-evolution of resource feedback and social network dynamics in human-environmental systems

Games with environmental feedback have become a crucial area of study across various scientific domains, modelling the dynamic interplay between human decisions and environmental changes, and highlighting the consequences of our choices on natural resources and biodiversity. In this work, we propose a co-evolutionary model for human-environment systems that incorporates the effects of knowledge feedback and social interaction on the sustainability of common pool resources (CPRs). The model represents consumers as agents who adjust their resource extraction based on the resource’s state. These agents are connected through social networks, where links symbolize either affinity or aversion among them. The interplay between social dynamics and resource dynamics is explored, with the system’s evolution analyzed across various network topologies and initial conditions. We find that knowledge feedback can independently sustain CPRs. However, the impact of social interactions on sustainability is dual-faceted: it can either support or impede sustainability, influenced by the network’s connectivity and heterogeneity. A notable finding is the identification of a critical network mean degree, beyond which a depletion/repletion transition parallels an absorbing/active state transition in social dynamics, i.e. individual agents and their connections are/are not prone to being frozen in their social states. Furthermore, the study examines the evolution of the social network, revealing the emergence of two polarized groups where agents within each community have the same affinity. Finally, we observe an inverse relationship between system complexity and sustainability. Comparative analyses using Monte–Carlo simulations and rate equations are employed, along with analytical arguments, to reinforce the study’s findings. The model successfully captures key aspects of the human-environment system, offering valuable insights to understand how both the spread of information and social dynamics may impact the sustainability of CPRs.

Detection of network false information based on artificial intelligence models

There is often some false information in social platforms to mislead public opinion. Due to the rapid development of the Internet, the spread of false information on the Internet has become easier, which has brought many losses to people's economy and life. In this paper, the relevant research on false information based on bidirectional convolutional networks is analyzed, and the method is divided into four stages: data preprocessing, model architecture, training process and prediction process. Then, the relevant research on rumor detection by propagation tree kernel model are analyzed. Finally, this paper delineates a comprehensive framework that amalgamates enhanced Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and a hybridized Black Widow Optimization (BWO) with Moth Optimization Algorithm (MOA) (referred to as HM-BWO) for the accurate detection of network-based false information. This paper analyzes and discusses the challenges of poor universality and insufficient detection speed encountered by the current rumor detection research and puts forward the idea of introducing migration model to solve the problem of poor universality and Spark to solve the problem of insufficient detection speed. This article provides a good overview of the field of online disinformation.

ANALYSIS OF DIGITAL CULTURAL BEHAVIOR IN GEN Z STUDENTS OF UINSU COMMUNICATION SCIENCE

This journal discusses that digital culture has a significant role in the daily life of Generation Z students of UINSU Communication Sciences. Positive experiences using communication technology include the ease of interacting and obtaining information, but there are also risks such as the spread of false information and negative content. It is important to understand the meaning of the use of digital cultural communication through framing theory and phenomenological approaches so that Generation Z can use technology responsibly and intelligently. This study discusses the analysis of digital cultural behavior in Generation Z of UINSU Communication Science students. This study uses a qualitative descriptive approach with an in-depth interview method. The results of the study show that the motives for using Generation Z's digital communication are varied, with positive and negative experiences. The use of digital technology allows them to connect with people remotely, but it also carries risks such as the spread of false information.

Development of website-based learning media on the material of kingdoms in Indonesia and regional heroes phase B

The development and advancement of technology has many positive and negative impacts and changes in various fields, especially in the field of education in Indonesia. This also raises new challenges from the many challenges that already exist. in the era of globalization now the spread of information is very fast, one of which is through internet websites, this must be utilized properly and maximally for the world of education, with many benefits expected to make it easier for students to receive information to add insight and enrichment of material, thus the media used for students to learn must also develop creatively and innovatively. The purpose of this research is to develop website-based learning media in phase B IPAS subjects.

Legal Analysis of the Consumer Protection Law in the Promotion of Alcohol with Ethnic and Religious Elements by Holywings on Instagram

Promotional efforts are crucial to a company's marketing strategy. However, Holywings' promotion offering free alcoholic beverages to individuals named Muhammad and Maria violates Law Number 1 of 2024 on electronic information and transactions, specifically Article 28, paragraph 2. This article prohibits spreading information that incites hatred or enmity based on ethnicity, religion, race, and inter-group distinctions (SARA). This research analyzes promotion regulations under this law and the responsibilities of businesses concerning promotions involving ethnic and religious elements, as outlined in Law Number 8 of 1999 on Consumer Protection. Using a normative juridical approach, this study examines literature, secondary data, and statutes to address the legal issues. The research employs qualitative analysis to systematically gather and analyze data, aiming to compile relevant theories, concepts, legal principles, and regulations. The result indicate that legal protection for consumers regarding promotions with ethnic and religious elements is upheld by Article 4, letter g of the Consumer Protection Law, ensuring fair, honest, and non-discriminatory treatment. Additionally, Article 17, Paragraph 1, Letter f prohibits business actors from engaging in such advertising, while Articles 19 and 20 outline their accountability.

The social force model: a behavioral modeling approach for information propagation during significant events

Information diffusion otherwise known as the propagation, spread or dissemination of information occurs when a piece of information flows from a particular individual/community to another in a social network. Studies related to information propagation involve problems regarding the factors that affect the information propagation, how the information is disseminated, the speed of propagation, etc. Researchers have proposed information propagation models to understand the phenomenon and to answer these questions. These models have been effectively used in applications such as behavior analysis, public health care, etc. Although several studies are carried out in this field, the literature demands identifying the most influential factors of propagation in real time in cases of sudden unexpected significant disasters/epidemics/pandemics, since the existing propagation models seem unfit during such circumstances. In this paper, a novel information propagation model which predicts the top propagators of information related to a particular context is proposed. This model utilizes the past few weeks' data during a sudden outbreak of a disaster and identifies the most influential attributes of a user profile to predict the top propagators of the future. The proposed Social Force Model is inspired by a model used in studying the fear propagation pattern in pedestrian dynamics in real-life situation [Cornes FE, Frank GA, Dorso CO. Fear propagation and the evacuation dynamics. Simul Model Pract Theory. 2019;95:112–133.]. We have effectively mapped the various forces which constitute the Social Force Model such as the Desired Force, the Social Force and the Granular Force with respect to the online social network context in order to discover the key spreaders of information during a specific context. Apart from identifying the propagators, the proposed model discovers the key attributes by analyzing the behavior of users based on their past activities in the online social network.

Digital Literacy In Detecting Hoaxes In Instagram Media (Analysis Study Of Communication Science Students, State Islamic University Of North Sumatra)

Abstract This article explores the urgency of digital literacy in detecting hoaxes on social media, especially Instagram, among students of Communication Sciences of the State Islamic University of North Sumatra (UINSU). This research identifies crucial problems in the spread of false information or hoaxes that have the potential to divide society and damage information integrity. This study uses a qualitative methodology, this research adopts an ethnographic approach and a constructive paradigm to gain a deep understanding of how students perceive and respond to the information they find on social media. The location of this study is Campus 4 Tuntungan UINSU, and the resource persons were selected through purposive sampling based on their experience and activeness in using Instagram as well as their involvement in digital literacy issues. Primary data sources are obtained from in-depth interviews and participatory observations, while secondary data sources include relevant document studies. The data analysis technique used is the Miles, Huberman, and Saldana analytical model which includes data reduction, data presentation, and conclusion drawn. The validity test of the data was carried out through source triangulation. The results of the study show that even though students have access to digital literacy tools, there is still a tendency to trust and spread unverified content. The conclusion of the study emphasizes that digital literacy is not only important as a tool to verify information and avoid the spread of hoaxes, but also as a means to increase critical awareness of media content.

Profiles of physical education teachers: an analysis on social networks

The present study aimed to observe, analyze and correlate online materials, from profiles on the social network Instagram, which showed different patterns of Physical Education teachers and their influences. For this, the investigated of this study were two users who have profiles focused on the practice of Physical Education, and had their profiles observed, with investigation of the netnographic type, and later separated into post-determined categories. With the result we observed how the two distinct profiles attribute distinct meaning to health. From this analysis, one can observe and conclude that social networks have great influence on the body pattern that is stipulated by society, since Instagram is a great ally in the spread of information.

Research on the dynamic spread of information in social networks based on relationship strength theory and feedback mechanism

Introduction: Studying the main factors and related paths of rumor propagation contributes to the precise governance of rumor information in social networks. Most existing network representation learning methods do not fit with real-world information propagation networks well, and the network cannot effectively model the temporal characteristics and dynamic evolution features of rumor information propagation.Methods: Our study proposes a new dynamic network representation model for information propagation. Additionally, the study introduces a feedback mechanism where the latest node representations are fed back to neighboring nodes.Results: The method solves the problem of delayed network representation and improves network representation performance.Discussion: We conducted experimental simulations, and the results indicate that a higher level of trust contributes to stable group relationships and converging opinions, reducing the likelihood of opinion dispersion. Furthermore, novelty of topics, and interactivity between users, and opinion leaders exhibit distinct characteristics in guiding public opinion. The viewpoint evolution of the newly constructed dynamic network representation model aligns more closely with viewpoint evolution in real-world social networks.

FURTHER DISCUSSION ON INVESTMENT LAW, CYBERSECURITY LAW AND RECOMMENDATIONS FOR ATTRACTING FOREIGN INVESTMENT (FDI)

The purpose of this article is to present Further Discussion on Investment Law, Cybersecurity Law and Recommendations for Attracting Foreign Investment (FDI). Based on collects statisti-cal data from the statistical yearbooks of the provinces/cities from 2010 to 2021. We found FDI inflows have a positive impact on labor productivity in Vietnamese localities. Specifically, locali-ties have (i) the larger the proportion of FDI in progress in the total investment capital of the economy, (ii) the larger the number of projects, the more accumulated FDI in operation, (iii) FDI sector activity and (iv) the larger the share of net revenue of the FDI sector, the higher the labor productivity. Moreover, investors need to pay attention to cybersecurity law: Acts of distorting history, denying revolutionary achievements, and sabotaging the great unity bloc whole nation, offending religion, discriminating on gender, racial discrimination; Acts of spreading information harmful to organizations and individuals, including: false information causing confusion among the people, causing damage to socio-economic activities, causing difficulties for activities. actions of state agencies or official duty performers, infringing upon the lawful rights and interests of other agencies, organizations and individuals

Quantifying the uncertainty of LLM hallucination spreading in complex adaptive social networks

Large language models (LLMs) are becoming a significant source of content generation in social networks, which is a typical complex adaptive system (CAS). However, due to their hallucinatory nature, LLMs produce false information that can spread through social networks, which will impact the stability of the whole society. The uncertainty of LLMs false information spread within social networks is attributable to the diversity of individual behaviors, intricate interconnectivity, and dynamic network structures. Quantifying the uncertainty of false information spread by LLMs in social networks is beneficial for preemptively devising strategies to defend against threats. To address these challenges, we propose an LLMs hallucination-aware dynamic modeling method via agent-based probability distributions, spread popularity and community affiliation, to quantify the uncertain spreading of LLMs hallucination in social networks. We set up the node attributes and behaviors in the model based on real-world data. For evaluation, we consider the spreaders, informed people, discerning and unwilling non-spreaders as indicators, and quantified the spreading under different LLMs task situations, such as QA, dialogue, and summarization, as well as LLMs versions. Furthermore, we conduct experiments using real-world LLM hallucination data combined with social network features to ensure the validity of the proposed quantifying scheme.

Disinformation and Narrative Building: A Study on Chinese Local Applications

The current research aimed to measure the impact of information source, information channel, information verification,and information community response on narrative building in China. The motivation of this research was to provide recommendations to reduce the spread of fake information on social media platforms, which can harm the community. The population of this study was Chinese, and a sample of 390 respondents was considered for research findings. Partial Least Square – Structural Equation Model (PLS-SEM) was used to analyze data. The research empirically confirmed that information sources, information channels, information verification, and information community response are significant in narrative building in China. The findings of this research contributed to the inconclusive discussion by the previous studies in the literature. The study practically recommends the findings focus on information source, channel, verification, and community response before working on it

Social contagion on higher-order networks: The effect of relationship strengths

We study the role and impact of interpersonal relationships on the dissemination of information, emotions, and behaviors through social higher-order networks. Namely, we introduce a novel model that explicitly accounts for strong and weak relationships on social contagion, and that integrates binary and ternary interactions among individuals. The model captures the dynamics of complex group interactions, and the differential impact that these relationship strengths have on the spread of contagion within various network structures. Our study reveals that in non-preferential structures, strong relationships significantly accelerate contagion, enhancing infection rates especially when weak relationship infection rates are low. Conversely, in preferential and mixed structures, the influence of strong relationships is more subdued, with network architecture playing a more dominant role in contagion dynamics. Our results thus offer various hints for managing social contagion. For instance, enhancing positive interactions within specific network structures, such as increasing connectivity in preferential networks or stabilizing influential nodes in non-preferential networks, can significantly promote a rapid spread of positive information and healthy behaviors.

How Can News Media Influence the Future People to Help Save the Earth?

With the development of science and technology, the forms of news media are constantly innovating and enriching. From traditional newspapers and television to today s Internet, social media, etc., the communication channels are increasingly diversified. The emergence of these new media makes news information spread faster, more widely, and has greater influence on the public. Therefore, how news media can use these new media platforms to spread environmental protection concepts and guide the public to participate in actions to save the earth is a question worthy of our in-depth exploration. Based on this, how can news media influence people s participation in saving the Earth in the future? Explore for reference by relevant practitioners.

Impact of community structure on the spread of epidemics on time-varying multiplex networks.

Community structure plays a crucial role in realistic networks and different communities can be created by groups of interest and activity events, and exploring the impact of community properties on collective dynamics is an active topic in the field of network science. Here, we propose a new coupled model with different time scales for online social networks and offline epidemic spreading networks, in which community structure is added into online social networks to investigate its role in the interacting dynamics between information diffusion and epidemic spreading. We obtain the analytical equations of epidemic threshold by MMC (Microscopic Markov Chain) method and conduct a large quantities of numerical simulations using Monte Carlo simulations in order to verify the accuracy of the MMC method, and more valuable insights are also obtained. The results indicate that an increase in the probability of the mobility of an individual can delay the spread of epidemic-related information in the network, as well as delaying the time of the peak of the infection density in the network. However, an increase in the contact ability of mobile individuals produces a facilitating effect on the spread of epidemics. Finally, it is also found that the stronger the acceptance of an individual to information coming from a different community, the lower the infection density in the network, which suggests that it has an inhibitory effect on the disease spreading.

Pest categorisation of Coniella castaneicola.

The European Commission requested the EFSA Panel on Plant Health to conduct a pest categorisation of Coniella castaneicola (Ellis & Everh) Sutton, following commodity risk assessments of Acer campestre, A. palmatum, A. platanoides, A. pseudoplatanus, Quercus petraea and Q. robur plants from the UK, in which C. castaneicola was identified as a pest of possible concern to the EU. When first described, Coniella castaneicola was a clearly defined fungus of the family Schizoparmaceae, but due to lack of a curated type-derived DNA sequence, current identification based only on DNA sequence is uncertain and taxa previously reported to be this fungus based on molecular identification must be confirmed. The uncertainty on the reported identification of this species translates into uncertainty on all the sections of this categorisation. The fungus has been reported on several plant species associated with leaf spots, leaf blights and fruit rots, and as an endophyte in asymptomatic plants. The species is reported from North and South America, Africa, Asia, non-EU Europe and Oceania. Coniella castaneicola is not known to occur in the EU. However, there is a key uncertainty on its presence and geographical distribution worldwide and in the EU due to its endophytic nature, the lack of systematic surveys and possible misidentifications. Coniella castaneicola is not included in Commission Implementing Regulation (EU) 2019/2072 and there are no interceptions in the EU. Plants for planting, fresh fruits and soil and other growing media associated with infected plant debris are the main pathways for its entry into the EU. Host availability and climate suitability in parts of the EU are favourable for the establishment and spread of the fungus. Based on the scarce information available, the introduction and spread of C. castaneicola in the EU is not expected to cause substantial impacts, with a key uncertainty. Phytosanitary measures are available to prevent its introduction and spread in the EU. Because of lack of documented impacts, Coniella castaneicola does not satisfy all the criteria that are within the remit of EFSA to assess for this species to be regarded as potential Union quarantine pest.

Out of time order correlation of the Hubbard model with random local disorder.

The out-of-time-order correlator (OTOC) serves as a powerful tool for investigating quantum information spreading and chaos in complex systems. We present a method employing non-equilibrium dynamical mean-field theory and coherent potential approximation combined with diagrammatic perturbation on the Schwinger-Keldysh contour to calculate the OTOC for correlated fermionic systems subjected to both random disorder and electron interaction. Our key finding is that random disorder enhances the OTOC decay in the Hubbard model for the metallic phase in the weakly interacting limit. However, the current limitation of our perturbative solver restricts the applicability to weak interaction regimes.

Influence of Environmental Social Governance (ESG), Profitability and Capital Structure on Firm Value

The faster information spreads, the more important it is for companies to publicize the good and minimize problems that can harm the company's reputation and value. Environmental pollution cases and issues are the reasons why positive information is very attractive to investors. Therefore, this study aims to test (1) Does Environmental Social Governance affect firm value, (2) Does Profitability affect firm value, (3) Does Capital structure affect Firm Value and (4) Does Environmental Social Governance, profitability and Capital structure jointly affect firm value in Indonesia. In this study, the population used was industrial sector companies totaling 56 companies and those used as samples in this study were 49 companies that were consecutively listed on the Indonesia Stock Exchange for 3 years in 2020-2022. The sample of this study was determined by random sampling method. The type of research and data used is quantitative with secondary data. The analysis method used is multiple linear regression analysis and uses SPSS 26 software. The results showed that (1) Environmental Social Governance variables affect firm value, (2) Profitability variables affect firm value, (3) Capital structure affects firm value and (4) Environmental Social Governance, profitability and Capital structure together affect firm value.