Manipulation Of Information Research Articles

Information manipulation on TikTok and its relation to American users' beliefs about China

Three studies explored how TikTok, a China-owned social media platform, may be manipulated to conceal content critical of China while amplifying narratives that align with Chinese Communist Party objectives. Study I employed a user journey methodology, wherein newly created accounts on TikTok, Instagram, and YouTube were used to assess the nature and prevalence of content related to sensitive Chinese Communist Party (CCP) issues, specifically Tibet, Tiananmen Square, Uyghur rights, and Xinjiang. The results revealed that content critical of China was made far less available than it was on Instagram and YouTube. Study II, an extension of Study I, investigated whether the prevalence of content that is pro- and anti-CCP on TikTok, Instagram, and YouTube aligned with user engagement metrics (likes and comments), which social media platforms typically use to amplify content. The results revealed a disproportionately high ratio of pro-CCP to anti-CCP content on TikTok, despite users engaging significantly more with anti-CCP content, suggesting propagandistic manipulation. Study III involved a survey administered to 1,214 Americans that assessed their time spent on social media platforms and their perceptions of China. Results indicated that TikTok users, particularly heavy users, exhibited significantly more positive attitudes toward China's human rights record and expressed greater favorability toward China as a travel destination. These results are discussed in context of a growing body of literature identifying a massive CCP propaganda bureaucracy devoted to controlling the flow of information in ways that threaten free speech and free inquiry.

The Cyber Proxy War: Non-State Actors Role in Global Geopolitical Competition

Cyberwarfare has become one of the most prominent aspects of global geopolitical competition, introducing a new dimension of conflict involving states and non-state actors. Although research on the role of states in cyber warfare has been amplacious, research on the role of non-state actors is still limited. This study aims to analyze the role and impact of non-state actors in global cyber warfare. In cyber warfare, non-state actors can exploit the vulnerabilities of security systems to achieve their political or ideological goals, changing geopolitical dynamics in unexpected ways. Case studies raised in this study include cyber attacks by Anonymous groups against governments and companies, cyber acts of terrorism by ISIS, manipulation of information by extremist groups to achieve their political goals, and the use of digital propaganda in regional conflicts. By paying attention to the concept of force and security in the perspective of realism, this research is expected to provide a better understanding of how non-state actors influence global geopolitical dynamics through cyber warfare. The implication of this research is the importance of strengthening national cyber defense and international cooperation in the face of threats presented by non-state actors in the cyber domain.

Enhancing Deepfake Detection Through Quantum Transfer Learning and Class-Attention Vision Transformer Architecture

The widespread use of the internet, coupled with the increasing production of digital content, has caused significant challenges in information security and manipulation. Deepfake detection has become a critical research topic in both academic and practical domains, as it involves identifying forged elements in artificially generated videos using various deep learning and artificial intelligence techniques. In this dissertation, an innovative model was developed for detecting deepfake videos by combining the Quantum Transfer Learning (QTL) and Class-Attention Vision Transformer (CaiT) architectures. The Deepfake Detection Challenge (DFDC) dataset was used for training, and a system capable of detecting spatiotemporal inconsistencies was constructed by integrating QTL and CaiT technologies. In addition to existing preprocessing methods in the literature, a novel preprocessing function tailored to the requirements of deep learning models was developed for the dataset. The advantages of quantum computing offered by QTL were merged with the global feature extraction capabilities of the CaiT. The results demonstrated that the proposed method achieved a remarkable performance in detecting deepfake videos, with an accuracy of 90% and ROC AUC score of 0.94 achieved. The model’s performance was compared with other methods evaluated on the DFDC dataset, highlighting its efficiency in resource utilization and overall effectiveness. The findings reveal that the proposed QTL-CaiT-based system provides a strong foundation for deepfake detection and contributes significantly to the academic literature. Future research should focus on testing the model on real quantum devices and applying it to larger datasets to further enhance its applicability.

Evaluating the role of generative AI and color patterns in the dissemination of war imagery and disinformation on social media.

This study explores the evolving role of social media in the spread of misinformation during the Ukraine-Russia conflict, with a focus on how artificial intelligence (AI) contributes to the creation of deceptive war imagery. Specifically, the research examines the relationship between color patterns (LUTs) in war-related visuals and their perceived authenticity, highlighting the economic, political, and social ramifications of such manipulative practices. AI technologies have significantly advanced the production of highly convincing, yet artificial, war imagery, blurring the line between fact and fiction. An experimental project is proposed to train a generative AI model capable of creating war imagery that mimics real-life footage. By analyzing the success of this experiment, the study aims to establish a link between specific color patterns and the likelihood of images being perceived as authentic. This could shed light on the mechanics of visual misinformation and manipulation. Additionally, the research investigates the potential of a serverless AI framework to advance both the generation and detection of fake news, marking a pivotal step in the fight against digital misinformation. Ultimately, the study seeks to contribute to ongoing debates on the ethical implications of AI in information manipulation and to propose strategies to combat these challenges in the digital era.

Integrative and syntactic complexity's role in decision-making under uncertainty.

This study explores the impact of integrative complexity (IC) and syntactic complexity (SC) on decision-making under uncertainty. The research addresses how cognitive structures contribute to decision quality in ambiguous situations. A modified Ellsberg experiment was conducted using an online platform. Participants were exposed to varying levels of ambiguity, and decision support tools were introduced to assess the influence of IC and SC on decision-making. The manipulation of available information allowed for a controlled analysis of cognitive processing. The findings reveal that IC and SC significantly enhance decision quality. IC facilitates the integration of diverse information, while SC supports the comprehension and management of ambiguity. Both cognitive structures play essential roles in navigating uncertainty. These results underscore the importance of IC and SC in effective decision-making. The findings suggest that fostering these cognitive abilities may improve decision-making skills in uncertain contexts, offering practical implications for training and development in high-stakes environments.

Neural correlates of olfactory working memory in the human brain.

Previous research has revealed that the insula, pallidum, thalamus, hippocampus, middle frontal gyrus, and supplementary motor area are activated during odor memory and that the performance of olfactory working memory is affected by the verbalization of odors. However, the neural mechanisms underlying olfactory working memory and the role of verbalization in olfactory working memory are not fully understood. Twenty-nine participants were enrolled in a study to complete olfactory and visual n-back tasks using high- and low-verbalizability stimuli while undergoing fMRI imaging. The behavioral results showed that the participants achieved greater accuracy in the visual rather than olfactory n-back task. We observed increased activation in the precentral gyrus, superior frontal gyrus, middle frontal gyrus, supplementary motor area, and inferior parietal gyrus during olfactory working memory. Interestingly, decreased activation was observed in the olfactory 2-back task versus the 0-back task. Moreover, the left angular gyrus and inferior parietal gyrus were more strongly activated during processing of olfactory working memory using high-verbalizability odors. In conclusion, olfactory working memory engages cross-modal regions to facilitate responses, is involved in the monitoring and manipulation of information during working memory, and boasts a unique activation pattern that is different from that of visual working memory. Semantic information supports the representation of odor information in the working memory system.

Local Protectionism, Information Manipulation, and Government Disclosure of Food Safety Information

Local Protectionism, Information Manipulation, and Government Disclosure of Food Safety Information

From epidemics to infodemics: historical investigations on information manipulation and technoscientific risk

From epidemics to infodemics: historical investigations on information manipulation and technoscientific risk

TRANSFORMATION OF POLITICAL DISCOURSE IN THE CONTEXT OF MEDIATIZATION: CHALLENGES FOR SOCIAL ORDER IN UKRAINE

Research objective: To analyze the transformation of political discourse under mediatization conditions and its impact on social order in Ukrainian society. The study employs a comprehensive application of systemic approach, institutional, comparative and historical methods, as well as content analysis of official social media pages of state institutions. The dualistic nature of modern mediatization is established, which manifests through simultaneous processes of media integration into traditional social institutions and the formation of media as an independent social institution. Key challenges to social order arising from the mediatization of political discourse are identified. A conceptual model of interaction between media and political institutions in the context of social order transformation is proposed. The research reveals the emergence of new forms of political engagement and participation facilitated by digital platforms. It demonstrates how social media has become a crucial arena for political discourse, reshaping power dynamics between political actors and citizens. The study also highlights the potential risks of information manipulation and the spread of misinformation in the mediatized political environment. The understanding of mechanisms of political actors’ adaptation to media requirements and transformation of traditional forms of political communication is expanded. The research results can be used to develop communication strategies for state institutions under mediatization conditions. For the first time, a comprehensive analysis of the impact of political discourse mediatization on social order in the Ukrainian context is conducted, taking into account the specifics of hybrid threats. An in-depth study of the influence of digital technologies and social networks on the transformation of political communication in the context of hybrid threats is suggested. The article is empirical in nature.

Impact of Information Disorders in Librarians’ Community

Objective. Librarians' role is crucial in combating information disorders. Their ability to identify false information is a core professional competency. As librarians refine their professional identities, they also cultivate a robust knowledge practice. This paper delves into the impact of information disorders on the librarian community. Methods. A group of Filipino public librarians were interviewed to understand the librarians' perceptions of the severity and impact of information disorders on their communities. Results. After careful analysis of qualitative data, five themes emerged including credibility threat, detrimental information, unfounded claims, manipulation of information, and promotion of truthful information. Conclusions. Information disorders pose a serious threat to librarians and the public. Malicious actors exploit these to manipulate public opinion, leading to fraud and false expertise. Librarians can counter these threats by sharing credible resources. They can also address the crisis of credibility by sharing expert advice and advocating for the value of accurate information

And No One Gets the Short End of the Stick: A Blockchain-Based Approach to Solving the Two-Sided Opportunism Problem in Interorganizational Information Sharing

In interorganizational information sharing, opportunism has two sides: information poaching by the information recipient and information manipulation by the information provider. The threat of such opportunism can entirely preclude business relationships. Prior countermeasures either failed to reliably prevent opportunistic behavior or addressed only one of the two sides. To overcome these shortcomings, we develop three design principles of an information system that facilitates reliable interorganizational information sharing without revealing the underlying data. We instantiate the design in a blockchain system for wear-based leasing contracts for machine tools. We demonstrate and evaluate the efficacy and utility of our design through in-depth interviews with business and technology experts and a survey of 85 machine tool users and 77 lessors in the manufacturing industry. Our study conceptualizes information poaching and information manipulation as two sides of the same problem and shows empirically that opportunities for beneficial business relationships arise when both are addressed together. Our design principles provide a blueprint for a shared information system that prevents both information poaching and information manipulation, thereby enabling new interorganizational information sharing relationships based on data that would otherwise be considered too sensitive to share or too untrustworthy to rely on.

Devising a method for detecting information threats in the Ukrainian cyber space based on machine learning

The object of this study is a disinformation detection process based on search algorithms for identifying fake news. The main task was to define a set of criteria and parameters for detecting the Ukrainian-language disinformation based on machine learning. A methodology has been considered for developing and filling a dataset of fakes for further training of the model and testing it for the purpose of identifying disinformation and propaganda, as well as determining the attributes of primary sources and routes of their distribution. This makes it possible to reasonably approach the definition of a model for forecasting the development of information threats in the cyberspace of Ukraine. In particular, the accuracy of automatic detection of the probability of disinformation in texts can be increased. For the English-language texts using balanced datasets for training when applying classical machine learning classifiers, the accuracy of identification and recognition of fakes is ³90 %, and for the Ukrainian-language texts – ³52 % and £90 %. That has made it possible to devise requirements for the structure and content of a typical dataset of fakes in the period after the full-scale invasion of Ukraine. The practical result of this work is the designed decision-making support system for monitoring, detecting, recognizing, and forecasting information threats in the cyberspace of Ukraine based on NLP and machine learning. The implementation of preliminary processing of the Ukrainian-language news, taking into account the linguistic features of the language in the text, increases the accuracy of fake identification by »1.72 times. Approaches to the construction of models for forecasting the development of information threats in cyberspace have been developed, which is an urgent task when fake news and information manipulation can affect public sentiment, politics, and the economy

Mediating role of earnings management upon nexus among bank financial leverage and economic financial stability

PurposeThis research aims to investigate the relationship between banks’ financial leverage and economic financial stability, and as a result, the research will discuss the role of earnings management (EM) in this relationship, since managers normally manipulate their financial reports when they show higher financial leverage. It is important to control the financial leverage in Jordanian banks based on the research results. The main objective is to mitigate the bank’s financial leverage risk as much as its relationship with financial stability. Results may be important for investors, managers, regulatory bodies and auditors in Jordan since they help strengthen financial stability in Jordan. Finally, the main objective of this study is to find a solution to maintain stable and real financial economy by finding the effect of higher financial leverage in Jordanian banks of managers’ cosmetic practices. This will be discussed through testing the role of EM of the relationship between firm’s financial leverage and financial stability.Design/methodology/approachIn order for the researchers to analyze data, quantitative methods are processed statistically. Also, the researcher tests research conceptual framework according to the mediation model that was developed by Preacher and Hayes (2004). In Figure (1) of which panel A: determines a direct effect, while panel B: illustrates a mediating design. To construct the sample, the researcher used information extracted from Jordanian annual financial reports that is extracted from Amman Stock Exchange. The population of the study includes all Jordanian banks which are 26 banks, additionally, the period from 2008 to 2018 was used to illustrate data. The reason behind using this period is that to examine the variables relationships for and after 2008 financial crisis and its consequences. The researcher chose 2018 as the end period, that is because it is the year before COVID-19 period which covers 2019–2022, and this period is considered not normal. In comparison with past studies, the researcher used modified Jones Model to measure EM (Valášková et al., 2021; Nopiana and Salvi, 2022; Riahi, 2020; Quddoos et al., 2020; Cho et al., 2012), while financial stability and financial leverage was calculated using total debt/total equity (Nopiana and Salvi, 2022). Finally, financial stability is measured using the financial stability model for banking sector, but not for all economy that is because the banking sector represents 96% of the economy, also this study applied for banking sector. Missing values were replaced using the mean on SPSS. Finally, regression model and F-score, correlation have been examined in the research analysis.FindingsIncreased risk on enterprises has an impact on economic financial stability. And the interest rate result shows that Jordan’s central bank boosts interest rates during inflationary periods, increasing the risk to the economy’s financial stability. Furthermore, size has a minimal impact when compared to other variables, and greater business sizes signal more sophisticated transactions and higher leverage, reducing the economy’s financial soundness. Finally, ROA indicates increased bank performance, which contributes to the economy’s financial stability. While EM has a direct negative impact on financial stability, this conclusion is consistent with the researcher’s expectations. Because EM refers to the manipulation of financial report information, including information about financial leverage, manipulation also lowers investor confidence in bank share prices, affecting the stability of the economy’s financial system. It has little influence on the relationship between leverage and economic financial stability.Practical implicationsThe implications of this research have been discussed through the research, for example, to maintain economic financial stability, auditors must take care through their role specially when there is higher financial leverage of Jordanian banks. Further, managers must pay attention before manipulating financial information if there is high financial leverage, because this will affect the economic financial stability. Lastly, the most important implication is that the maintenance of economic financial stability, and EM if not discovered for a period of time may show false signaling of economic financial stablity, and suddenly face financial crises.Originality/valueUnderstanding the role of EM in the relationship between banks’ financial leverage the economic financial stability, may control many issues like the role of external auditor of reporting about the reliability of financial information (when there is high bank financial leverage, the auditor must exercise professional care and increase his sample to ensure that there are no cosmetic accounting), and when EM is in control, the economy will work smoothly and react normally to the effect of financial leverage of Jordanian banks. And the situation of 2008 crisis will not be repeated (because of the cosmetic practices by American firms for many years since 2008 with hidden cosmetic practices, suddenly, the 2008 crises happened). In conclusion, this discussion is original, since no literature theoretically discussed this issue before which (EM when financial leverage is high) may be applied in practice.

Firm‐Specific Economic Policy Uncertainty and Stock Price Crash Risk

ABSTRACTEconomic policy uncertainty (EPU) significantly impacts capital markets and financial activities. Prior studies present inconsistent results regarding the effect of EPU on stock price crash risk, possibly due to the usage of a macro‐level EPU index that assumes homogeneity in its effects across diverse firms. Using data from Chinese A‐share listed firms from 2008 to 2019, we adopt a text‐based method to measure firm‐specific economic policy uncertainty (FEPU) and examine its impact on future stock price crashes. We find that FEPU mitigates crash risk through two channels: monitoring enhancement and conservatism promotion, which deter the accumulation of negative information. The mitigating effect of FEPU is more pronounced for firms with greater managerial stock option incentives, overconfident CEOs, and higher reliance on government subsidies. Overall, our study highlights the crucial role of FEPU in reducing the expected costs of managerial information manipulation and managing stock return tail risks.

Russian Utilization of Reflexive Control

Russian utilization of reflexive control plays a pivotal role in advancing its foreign policy objectives. This strategic concept involves shaping an adversary's perception and decision-making processes to achieve desired outcomes without direct confrontation. The Russian government employs reflexive control across various domains, including intelligence, strategic communication, and diplomacy. The EU has recognized these manipulative methods and labelled them as Foreign Information Manipulation and Interference (FIMI). This paper endeavors to conduct an in-depth analysis of Kremlin's application of reflexive control to influence decision making processes in Serbia. The study closely examines how Russia successfully manipulated the information landscape to its benefit by understanding and shaping the internal dynamics of its partner and leveraging existing fault lines. By capitalizing on the internal tensions, Russia made Serbia permissive to the reflexive control manipulation and influenced the outcomes in a way that aligns with Kremlin’s own foreign policy objectives. This paper analysis contributes to a better understanding of the intricate dynamics between reflexive control strategies and their impact on the national and international political landscape.

The Role of Ilha Study Program Students in Spreading the Values ​​of Religious Moderation on Social Media

The main aim of this research is to understand and analyze in depth how students from the Al-Qur'an and Tafsir Science Study Program (Ilha) play an active role in spreading the values ​​of religious moderation through social media. This research problem focuses on the important role of the younger generation, especially Ilha Study Program students, in facing the challenges of radicalism and intolerance which are often spread through social media. This research tries to answer the question of how Ilha Study Program students can become agents of change in spreading the values ​​of religious moderation in the digital space. Qualitative research method with field research type, conducting in-depth interviews with Ilha Study Program students to dig deeper into the i, challenges, strategies, as well as supporting and inhibiting factors they face in spreading the values ​​of religious moderation. The results of this research can provide a comprehensive picture of the role of Ilha Study Program students in spreading the values ​​of religious moderation on social media. identify strategies used by Ilha Study Program students, such as creating creative content, online discussions, social media campaigns, and collaboration with other parties. The challenges faced are lack of good understanding or just following trends, and manipulation of information or hoax news. The supporting and inhibiting factors for Ilha Study Program students in spreading the values ​​of religious moderation are the influence of peers, being quick and interactive, while the inhibiting factors are a lack of increasing understanding or reducing negative content on social media

Whether words and deeds are consistent or superficial: Will Management Discussions Attract Green Fund Managers?

Based on the text analysis of MD&A intonation of Chinese listed companies in Shanghai and Shenzhen A-share companies from 2008 to 2021, we study the attracting effect of green words in MD&A on the entry of green fund investors. The research finds that the disclosure of green words by management is significantly positively correlated with the entry of green fund investors. It shows that green words can attract green fund investors, and when we divide green words into energy saving and emission reduction, the two kinds of words still have a significant role in attracting green fund investors. Further research shows that when the MD&A of the enterprise is consistent with the action (green invention patent), green fund investors have the strongest investment intention. Otherwise, investors may regard it as a kind of information manipulation and thus be cautious about investment. This study provides new empirical evidence for the study of economic consequences from the perspective of text analysis.

Grouping Student Achievement Data In A Decision Making System Using The Weight Product Method

Information, modeling, and data manipulation systems are called decision support systems (DSS). When there is uncertainty about the best course of action in semi-structured or unstructured situations, the system is utilized to support decision-making. There are various approaches available for producing decision support systems, one of which is the Weighted Product (WP) Method. With the Weighted Product (WP) approach, attribute ratings are connected by multiplication; however, each attribute's rating must first be increased to the power of the attribute's weight. The normalizing process is same to this one. SPK procedure to choose the winners of the scholarships. Scholarship information from MTS Swasta Alwasliyah Simpang Merbau can be saved in the Decision Support System using this method. This way, in the event that an error arises when entering grades or scholarship information, the wrong information can be fixed without requiring the scholarship information to be re-input. Scholarships are presents to individuals in the form of financial aid intended to be utilized toward their ongoing educational pursuits.

The Role of Generative AI in Shaping Human Rights and Gender Equity: A Critical Analysis

This research aims to explore the dual role of generative AI technology in supporting human rights activism and gender equality. The primary issue addressed is how AI can empower individuals and organizations in advocating for human rights, while also posing risks such as the spread of misinformation and the perpetuation of bias. The methods used include case study analysis and literature review to understand the impact of AI in social and political contexts. The urgency of this research lies in the pressing need to develop ethical frameworks that safeguard human rights amid rapid technological advancements. The novelty of this study stems from its interdisciplinary approach, combining technology, human rights, and gender equality, while highlighting the philosophical and ethical challenges that arise alongside AI development. The findings of the research indicate that AI holds significant potential to enhance the visibility of human rights issues through more effective social media campaigns and compelling data presentation. However, the study also identifies substantial risks, including information manipulation and biases that could harm certain groups. The conclusion emphasizes the importance of creating strategies that maximize the benefits of AI while minimizing its risks. Thus, this research contributes to efforts to create an AI-driven future that not only supports human rights but also promotes gender equality, and it encourages further discussions about the boundaries between humans and machines in the context of these rights.

Driving superconducting qubits into chaos

Abstract Kerr parametric oscillators are potential building blocks for fault-tolerant quantum computers. They can stabilize Kerr-cat qubits, which offer advantages toward the encoding and manipulation of error-protected quantum information. The recent realization of Kerr-cat qubits made use of the nonlinearity of the SNAIL transmon superconducting circuit and a squeezing drive. Increasing nonlinearities can enable faster gate times, but, as shown here, can also induce chaos and melt the qubit away. We determine the region of validity of the Kerr-cat qubit and discuss how its disintegration could be experimentally detected. The danger zone for parametric quantum computation is also a potential playground for investigating quantum chaos with driven superconducting circuits.