Spread Of Information Research Articles

Probing scrambling and operator size distributions using random mixed states and local measurements

The dynamical spreading of quantum information through a many-body system, typically called scrambling, is a complex process that has proven to be essential to describe many properties of out-of-equilibrium quantum systems. Scrambling can, in principle, be fully characterized via the use of out-of-time-ordered correlation functions, which are notoriously hard to access experimentally. In this work, we put forward an alternative toolbox of measurement protocols to experimentally probe scrambling by accessing properties of the operator size probability distribution, which tracks the size of the support of observables in a many-body system over time. Our measurement protocols require the preparation of separable mixed states together with local operations and measurements, and combine the tools of randomized operations, a modern development of near-term quantum algorithms, with the use of mixed states, a standard tool in NMR experiments. We demonstrate how to efficiently probe the probability-generating function of the operator distribution and discuss the challenges associated with obtaining the moments of the operator distribution. We further show that manipulating the initial state of the protocol allows us to directly obtain the individual elements of the distribution for small system sizes. Published by the American Physical Society 2024

Estimating the Expected Influence Capacities of Nodes in Complex Networks under the Susceptible-Infectious-Recovered Model

In recent years, epidemic modeling in complex networks has found many applications, including modeling of information or gossip spread in online social networks, modeling of malware spread in communication networks, and the most recent model of the COVID-19 pandemic. If the information disseminated is accurate, for example, maximizing its distribution is desirable, whereas if it is a rumor or a virus, its spread should be minimized. In this context, it is very important to identify super-spreaders that maximize or minimize propagation. Lately, studies for detecting super-spreaders have gained momentum. Most of the studies carried out aim to distinguish the influences of nodes under a specific propagation model (such as SIR) using network centrality measures and subsequently, to rank the nodes accordingly. However, in this study, we developed an algorithm that approximates the expected influence of nodes under the popular SIR model. By considering the behavior of the SIR model and only the shortest paths between nodes, the algorithm ranks the nodes according to this approximated value. Our developed algorithm is named the Expected Value Estimation (EVE). We compared the performance of EVE, using different SIR settings on real-world datasets, with that of many current well-known centrality measures. The experimental studies demonstrated that the solution quality (ranking capability) of EVE is superior to that of its competitors.

Information shock, market reaction, and stock message board information diffusion

We investigate the market reaction to information shocks in the Chinese stock market and study the process of information diffusion among investors on the stock message board. We find that investors tend to overreact to information shocks and the communications on the stock message board facilitate this overreaction. Further analysis shows that stock market overreaction is more significant in response to small and medium-cap shocks, and the degree of overreaction decreass with increasing liquidity. Our empirical results provide significant evidence of how information spreads among retail investors from the perspective of investor overconfidence and information asymmetry.

Impact of Social Media on Society: A Literature Review

This manuscript explores the profound impact of social media on society, with a focus on social behavior, politics, and cultural norms. Employing a systematic literature review, including diverse sources, case studies, and real-world examples, the study provides a nuanced and comprehensive analysis. The brevity enforced by character limits on platforms like Twitter has shaped concise and direct communication, with emojis, memes, and hashtags becoming integral to online discourse. The rapid spread of information on social media has, however, led to the dissemination of misinformation, influencing public opinion and potentially affecting political outcomes. Collaboration among individuals, policymakers, and technology developers is crucial to shape the future of social media responsibly. This necessitates cultivating a culture of responsible use, promoting digital literacy, and advocating for policies that safeguard user rights and well-being. Striking a balance between innovation and ethical considerations is paramount to ensure the continued positive contribution of social media to society.

Can Invalid Information Be Ignored When It Is Detected?

With the rapid spread of information via social media, individuals are prone to misinformation exposure that they may utilize when forming beliefs. Over five experiments (total N = 815 adults, recruited through Amazon Mechanical Turk in the United States), we investigated whether people could ignore quantitative information when they judged for themselves that it was misreported. Participants recruited online viewed sets of values sampled from Gaussian distributions to estimate the underlying means. They attempted to ignore invalid information, which were outlier values inserted into the value sequences. Results indicated participants were able to detect outliers. Nevertheless, participants’ estimates were still biased in the direction of the outlier, even when they were most certain that they detected invalid information. The addition of visual warning cues and different task scenarios did not fully eliminate systematic over- and underestimation. These findings suggest that individuals may incorporate invalid information they meant to ignore when forming beliefs.

Age differences in the context of climate change: Does exposure to a fake consensus statement make a difference?

The present study examined whether people of different age groups respond differently to a true versus fake consensus statement concerning climate change. In total, 309 participants were randomly exposed to a true consensus statement about climate change and 311 were exposed to a false statement. Subsequently, respondents were asked to respond to items about attitudes, feelings, and behavioral intentions concerning climate change. Compared with younger people, older persons are significantly more concerned about climate change, more likely to report that climate change is real and more willing to take climate change action. Nevertheless, older persons also are more likely to be willing to post both fake and truthful information about climate change, thus, possibly serving as spreaders of both fake and truthful information. The findings suggest that it is younger people who will benefit from further education about climate change and older people who may benefit from education about the spread of information in social media. Our findings also suggest that simply providing individuals with consensus information has only limited impact on their climate change attitudes, feelings and behavioral intentions.

Quasiprobability fluctuation theorem behind the spread of quantum information

Information spreads in time. For example, correlations dissipate when the correlated system locally couples to a third party, such as the environment. This simple but important fact forms the known quantum data-processing inequality. Here we theoretically uncover the quantum fluctuation theorem behind the quantum informational inequality. The fluctuation theorem quantitatively predicts the statistics of the underlying stochastic quantum process. To fully capture the quantum nature, the fluctuation theorem established here is extended to the quasiprobability regime. We also experimentally apply an interference-based method to measure the amplitudes composing the quasiprobability and verify our established fluctuation theorem by the IBM quantum computer.

Environmental harshness does not affect the propensity for social learning in great tits, Parus major

According to the harsh environment hypothesis, natural selection should favour cognitive mechanisms to overcome environmental challenges. Tests of this hypothesis to date have largely focused on asocial learning and memory, thus failing to account for the spread of information via social means. Tests in specialized food-hoarding birds have shown strong support for the effects of environmental harshness on both asocial and social learning. Whether the hypothesis applies to non-specialist foraging species remains largely unexplored. We evaluated the relative importance of social learning across a known harshness gradient by testing generalist great tits, Parus major, from high (harsh)- and low (mild)-elevation populations in two social learning tasks. We showed that individuals use social learning to find food in both colour-associative and spatial foraging tasks and that individuals differed consistently in their use of social learning. However, we did not detect a difference in the use or speed of implementing socially observed information across the elevational gradient. Our results do not support predictions of the harsh environment hypothesis suggesting that context-dependent costs and benefits as well as plasticity in the use of social information may play an important role in the use of social learning across environments. Finally, this study adds to the accumulating evidence that the harsh environment hypothesis appears to have more pronounced effects on specialists compared to generalist species.

The Dark Side of Language Models: Exploring the Potential of LLMs in Multimedia Disinformation Generation and Dissemination

Disinformation - the deliberate spread of false or misleading information poses a significant threat to our society by undermining trust, exacerbating polarization, and manipulating public opinion. With the rapid advancement of artificial intelligence and the growing prominence of large language models (LLMs) such as ChatGPT, new avenues for the dissemination of disinformation are emerging. This review paper explores the potential of LLMs to initiate the generation of multi-media disinformation, encompassing text, images, audio, and video. We begin by examining the capabilities of LLMs, highlighting their potential to create compelling, context-aware content that can be weaponized for malicious purposes. Subsequently, we examine the nature of disinformation and the various mechanisms through which it spreads in the digital landscape. Utilizing these advanced models, malicious actors can automate and scale up disinformation effectively. We describe a theoretical pipeline for creating and disseminating disinformation on social media. Existing interventions to combat disinformation are also reviewed. While these efforts have shown success, we argue that they need to be strengthened to effectively counter the escalating threat posed by LLMs. Digital platforms have, unfortunately, enabled malicious actors to extend the reach of disinformation. The advent of LLMs poses an additional concern as they can be harnessed to significantly amplify the velocity, variety, and volume of disinformation. Thus, this review proposes augmenting current interventions with AI tools like LLMs, capable of assessing information more swiftly and comprehensively than human fact-checkers. This paper illuminates the dark side of LLMs and highlights their potential to be exploited as disinformation dissemination tools.

Solvable Model of Quantum-Darwinism-Encoding Transitions.

We propose a solvable model of quantum Darwinism to encoding transitions-abrupt changes in how quantum information spreads in a many-body system under unitary dynamics. We consider a random Clifford circuit on an expanding tree, whose input qubit is entangled with a reference. The model has a quantum Darwinism phase, where one classical bit of information about the reference can be retrieved from an arbitrarily small fraction of the output qubits, and an encoding phase where such retrieval is impossible. The two phases are separated by a mixed phase and two continuous transitions. We compare the exact result to a two-replica calculation. The latter yields a similar "annealed" phase diagram, which applies also to a model with Haar random unitaries. We relate our approach to measurement-induced phase transitions (MIPTs), by solving a modified model where an environment eavesdrops on an encoding system. It has a sharp MIPT only with full access to the environment.

The mnemonic effect of central and peripheral misinformation on social media

ABSTRACT The increasing use of social media has amplified the spread of false information. Yet little is known about the mnemonic consequences associated with exposure to different types of false information online. In two studies, we examined in a simulated online context how exposure to false information either central or peripheral in events affected memory. European American and Asian/Asian American college students (Study 1 N = 200; Study 2 N = 225) were presented with GIFs of daily life events and read tweets about the events that included four types of information: central true information, central false information, peripheral true information, and peripheral false information. They then took a True/False recognition test that included tweeted and untweeted true and false information and indicated how confident they were in their responses. Regardless of cultural background, participants in both studies demonstrated the misinformation effect, whereby they falsely recognised more and resisted less tweeted than untweeted false information. Furthermore, they showed higher susceptibility to peripheral than central false information exposed via tweets. Asian participants were less influenced by misinformation than European Americans in Study 2. These findings have important implications to combat misinformation in online environments.

A branch-and-cut approach to solve the Fault Diagnosis Problem with Lazy Spread and imperfect system information

This paper presents a new approach to solving the Fault Diagnosis Problem with Lazy Spread (FDPL) that arises in many fault-tolerant real-world systems with few opportunities for maintenance during their operations and significant failure interactions between the subsystems/components. As opposed to cascading faults that spread to most of the system almost instantaneously, FDPL considers fault-resistant systems where the spread of failures is relatively slow (lazy), i.e., only a small fraction of the components are faulty at the time of inspection, and accurate diagnosis of the faulty components is of critical importance to restore system performance and stop further damage. Introducing an extra level of difficulty, FDPL needs to be solved under imperfect (missing and wrong) system information in most real-world settings. To address this challenging prediction problem, we use graph theory concepts to develop an integer programming formulation and devise an efficient branch-and-cut algorithm for its solution. Extensive numerical experiments on realistic problem instances attest to the superior performance of our approach in terms of both computational efficiency and prediction accuracy compared to the state-of-the-art in the literature.

Assessing Patients Perception: Analyzing the Quality, Reliability, Comprehensibility, and the Mentioned Medical Concepts of Traumatic Brain Injury Videos on YouTube

AimThe aim of this study is to analyze the quality, reliability, comprehensibility, and the mentioned medical concepts of traumatic brain injury (TBI) related videos on YouTube. Material – Methods"Traumatic brain injury" and related Google Trends queries were used and 328 videos included. Categorization, quality assessment via a 5-point Global Quality Scale, reliability evaluation using a modified DISCERN scale, comprehensibility assessment using Flesch-Kincaid Reading Ease and Flesch-Kincaid Grade Level, and consensus-based classification for usefulness were performed. Target audience categorization was content-based. Text mining techniques were used to identify biomedical terms in video transcripts. ResultsMost of the videos were intended for non-healthcare professionals and deemed useful. The videos had intermediate quality and moderate level of reliability. The comprehensibility of the videos exceeded the recommended levels. Videos predominantly covered TBI symptoms, the severity of the condition, its impact on individuals, and possibly strategies related to diagnosis and treatment. ConclusionsResults suggest the requirement for higher quality and reliability in YouTube content about TBI. Emphasis should be placed on clear and accurate language to promote comprehensibility. Continued research, guidelines, education, and platform oversight can enhance the spread of reliable health information on social media, benefiting creators and consumers in this field.

A spherical evolution algorithm with two-stage search for global optimization and real-world problems

This paper proposes a spherical evolution algorithm with two-stage search. Spherical search and hypercube search are combined to achieve individuals' evolution. A self-adaptive Gaussian scale factor and a variable scale factor are designed to adaptively control individuals' spherical and hypercube search area according to their search situations. Two search stages frequently switch with four search cases to enhance the balance between exploration and exploitation processes. A directed adjacency matrix is devised to analyze the relationship among individuals from the perspective of graph theory. Experiments compare the proposed algorithm with five algorithms with distinctive search patterns on twenty nine CEC2017 benchmark functions. The diversity analysis and graph theory analysis show the good population diversity and effective information spreading of the proposed algorithm. Twenty two real-world problems evaluate the practicality and optimization ability of the proposed algorithm. Finally, the computational time complexity demonstrates that the proposed algorithm is more efficient than the original spherical evolution algorithm.

The Dangers of Hoaxes and Efforts to Overcome them in the 2024 Indonesian Presidential Election

Hoaxes are often the dominant element in every electoral process, whether in regional or presidential elections. The spread of fake news or false information through hoaxes can be done for a variety of purposes, ranging from jokes to serious political purposes. Incomprehension of political education and misuse of social media have become fertile fields for spreading hoaxes, especially in every election. In maintaining vigilance and facing the wave of hoaxes in the 2024 presidential election, research methods that can be used are content analysis and social network analysis. The purpose of this study is to detail the causes and consequences of the spread of hoaxes in the General Election, as well as present recommendations related to effective political education strategies to prevent and overcome the spread of hoaxes in the context of elections. This research is expected to contribute conceptually and practically to minimize the negative impact of spreading hoaxes on elections and increase public understanding of elections through the application of political education. To achieve this goal, this research will involve literature analysis and case studies of the spread of hoaxes in elections.

Ensuring children’s online safety in Kazakhstan: balancing protection from harm with rights to information access

The relevance of scientific research is due to a number of problems that arise in the field of protecting children from the spread of harmful information on the Internet. An increase in the level of crimes against children of a sexual nature, a sharp jump in the level of suicides, the manifestation of various types of addiction, ranging from gambling and ending with drugs, is a consequence of such an influence. The purpose of this work is to study the current legislation of Kazakhstan in this area and to find gaps in its functioning, as well as to propose an effective mechanism for the legal regulation of protecting children from harmful information on the Internet, taking into account international legal experience. The basis of the methodological approach is the dialectical method, which was used to study the legal regulation in the sphere of the use of Internet resources by minors, the analysis method was used to study the legal acts in this area. The results of this study are a comparative analysis of the legal regulation of the protection of children from harmful content on the example of the legal experience of Australia, Britain, Germany in comparison with Kazakhstan. Also, the legislation on the protection of children from harmful information in Kazakhstan was analysed in detail and the main gaps in the existing acts were identified. The study outlines possible ways to develop national legislation through the adoption of new regulations, the purpose of which should be to increase control over the privacy of minors’ data, restrict and block content that explicitly contains scenes of a sexual nature or violence, restrict advertising content, restrict access to information depending on from age. Also, it is going about the creation of special departments to regulate and control the issue of harassment and bullying, namely the Special Commissioner for Cyberbullying. The results obtained in this study can be used to protect children and prevent illegal actions against minors online at the legislative and local levels

SMS-Based Inter Campus Communication System of Isabela State University – Ilagan Campus

Rapid advancements and technological breakthroughs have revolutionized the spread of information and communications. The development of technology has significantly altered the transmission and storage of information. The widespread use of computers has revolutionized numerous businesses and sectors worldwide. Computers affect how employees can improve their work for every client. For example, offering their services in a way that is more accurate, efficient, and competitive when providing information. To carry out their work tasks, they may use a variety of programs or software. As a result, the manual is still the standard procedure for document recording, including the distribution of memos and communication letters to specific recipients or across offices using record books. Therefore, they might encounter challenges in the assigned personnel carrying out their duties during this process. So, the study's goal was to create a paperless communication system that would make it simple for the recording officer to find, distribute, and alert recipients—whether or not they had a cell phone. Every stage of the waterfall model was applied to the development process for the system. The respondent assessed and tested the system, and found that it met the requirements for sending outgoing and incoming memos and communication letters to the intended recipients.

Limitation of Religion Information Spread under Media Law

Limitation of Religion Information Spread under Media Law

UNVERIFIED INFORMATION IN SOCIAL NETWORKS: ANALYSIS FROM AN ISLAMIC PERSPECTIVE

In contemporary society, social media has evolved into an indispensable and pervasive tool, impacting individuals worldwide across various dimensions, including the personal, social, economic, and political spheres. The basic expectation from social networks is to serve the people and society by providing important, authentic information and verified news. Unfortunately, false news, rumours and fabricated information on social networks have become a threat to individuals, and a destructive tool for peace and societal harmony. The unregulated proliferation of hoaxes on social networks can lead to a myriad of societal disruptions and issues, thereby intensifying the need for harmonious and peaceful coexistence as advocated by both individuals and society at large. This is a qualitative descriptive article that explores the Islamic understanding and rulings on the spread of unverified information in social networks intentionally for gaining personal interest or political advantages. The article also recommends some ethical and moral precepts of revealed knowledge to ensure the proper use of social networks for the benefit of individuals and community, and to avoid unethical violation and immoral actions.

Herbal medicines for treatment of socially significant diseases in current Bulgarian society

Abstract Socially significant diseases are defined as widespread diseases causing great economic, social and demographic damage. Nowadays traditional health practices have gained increasing interest. The aim of this online survey was to establish the knowledge of a random sample of Bulgarian people about traditional medicines in order to find out: 1) the knowledge about the use of medicinal plants for some socially significant diseases; 2) the attitudes of respondents towards the medicinal plants safety; 3) the statement whether the herbs can replace conventional drugs. In present survey the most used medicinal plants reported was Crataegus monogyna Jacq., Zingiber officinale Roscoe, Allium sativum L., Valeriana officinalis L., Sambucus nigra L., Cinnamomum verum J. Presl and Curcuma longa L. Current scientific studies proved appropriate use reports of these plants. One of the reasons for the renewed interest in phytotherapy is the assumption that anything natural is safe, but there are data that herbal chemical constituents could exert toxic effects. The demographic features of our respondents revealed the importance of the level of education for the self-health care. So, more efforts should be focused on the spread of disease prevention information in low educated populations.