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While social media platforms promote people's information exchange and dissemination, they also make rumors spread rapidly on online platforms. Therefore, how to detect rumors quickly, timely and accurately has become a hot topic for scholars in related fields. Traditional deep learning models ignore the relationship and topology between nodes in the rumor detection task and use fixed weights or mean aggregation strategies in the feature aggregation process, which fail to capture the complex interactions between nodes and the dynamics of information propagation, limiting the accuracy and robustness of the rumor detection model. To address these problems, we propose a location-aware weighted GraphSAGE rumor detection model GSMA. We first introduce an attention mechanism that dynamically assigns different attention weights to different neighboring nodes for different degrees of aggregation, improving GraphSAGE's strategy of using mean-value aggregation for all neighboring nodes during the aggregation process; second, we introduce a modulated position encoding into the model and encode the position information of nodes into the features to improve the model's ability to perceive the relative position and order of nodes; finally, the post text sentiment is incorporated into the features to provide additional semantic information for the model as a way to achieve rumor detection in microblogging platforms. Experiments show that the accuracy of the GSMA model on Ma-Weibo and Weibo23 reaches 97.43% and 97.55%, which is an improvement of 1.11% and 0.77% compared to the benchmark GraphSAGE, and all the evaluation metrics are also improved compared to other optimal rumor detection models. [ABSTRACT FROM AUTHOR]

To steer public opinion, autocracies prioritize state media reports of political news while marginalizing commercial and foreign media. Can this dominance guarantee people's trust in state media news? We contend that rumors, circulated via informal channels and resistant to state information control, present a formidable challenge to public trust in state media news. Our two survey experiments in China pitted news of varying information quality (e.g. informative/detailed reports vs cursory mentions of events) from state media sources against rumors, showing that state media news can retain high levels of trustworthiness only if its information quality is high; however, low-quality state media news resulting from information control diminishes its trustworthiness and prompts people to believe rumors. Low-quality rumors have more negative effects than high-quality rumors on news trustworthiness and citizens' satisfaction with government policies. Thus, information control can paradoxically erode trust in state media, which often represent the government in autocracies. [ABSTRACT FROM AUTHOR]

The article focuses on Kate Starbird and her team's efforts to track and correct election-related rumors in real time. Topics include the research team's approach to combating misinformation, the increasing connection between different rumor-spreading groups on social media, and Starbird's personal experiences with political attacks and harassment.

This study uses qualitative methods to examine the challenges faced by authoritarian regimes in managing rumors during public crises, focusing on the Urumqi government's (the capital of the Xinjiang Uyghur Autonomous Region in Northwestern China) response to COVID-19 lockdown rumors. The analysis identifies four factors contributing to the failure of government debunking communication: Rejection due to Negative Past Experiences, Discourse Reinterpretation by Mismatched Criteria, Disregard Toward Inflexible Statements, and Opposition Arising from Perceived Superficial Efforts. These factors culminate in a core mechanism termed 'Emotional Resistance Anchored in Distrust,' highlighting how negative past experiences shape public distrust and foster resistance to government communication. The findings challenge the assumption of automatic public trust in authoritarian contexts and underscore the importance of aligning government actions with public needs and expectations, particularly during crises. [ABSTRACT FROM AUTHOR]

The article delves into the CIA's failed attempt to disrupt the Guatemalan coffee industry in 1954 as part of a covert operation to overthrow President Jacobo Árbenz. While the operation, codenamed Operation FIBER, aimed to destabilize the government by disrupting coffee exports, it ultimately failed due to misconceptions about the industry and resistance from the U.S. coffee industry. The CIA's involvement in Guatemala's coffee industry was complex and intertwined with U.S. financial interests, highlighting the challenges of using economic warfare tactics in a globalized industry. Despite efforts to apply economic pressure through propaganda campaigns urging consumers to boycott Guatemalan coffee, the operation did not achieve its intended goals, showcasing the complexities of the transnational coffee trade. [Extracted from the article]

The article delves into the historical ties between Time Inc. and the CIA during the Cold War, showcasing a pattern of collaboration for intelligence gathering purposes. Time and Life magazines granted the CIA access to their resources, blurring the boundaries between journalism and intelligence work. Internal dissent within Time Inc. shed light on the complexities of U.S. journalism during this era, emphasizing the significance of journalistic independence and credibility. Despite initial collaboration, Time Inc. eventually ceased sharing foreign dispatches with the CIA in 1952, underscoring the evolving nature of newsroom ethics and the importance of maintaining a free and independent press. [Extracted from the article]

The far and wide distribution of innumerable rumors and fake news have been a serious threat to the truthfulness of microblogs. The earlier works have frequently aimed at remembering the earlier state with n consideration to the next context information. Also, a majority of the works before have made use of conventional feature representation approaches preceding a classifier. In this research, we evaluate the rumor detection problem by examining multiple Deep Learning approaches, with a focus on forward and backward direction analysis. The proposed technique incorporates Optimal Bidirectional Long Short-Term Memory and Convolutional Neural Network in order to correctly classify tweets as rumor or non-rumor. Then the Biogeography-based optimization (BBO) provides recommendations for fine-tuning the Bi-LSTM-CNN model's hyperparameters. According to the results of the experiments, the suggested technique is more precise than conventional methods, with an accuracy of 86.12%. The statistical analysis further demonstrates that the suggested model is much more successful than the appropriate alternatives. [ABSTRACT FROM AUTHOR]

How did it become possible to think of a racism without racists? This article tackles this question by looking at the contested interpretation of a racist incident in France. In 1969, Jewish shop owners in Orléans were baselessly accused of kidnapping women in fitting rooms and trafficking them into sexual slavery. This antisemitic agitation rapidly attracted the attention of local authorities, national media, and social scientists, led by sociologist Edgar Morin. Morin's study made these events into a famous case-study in disinformation, the "rumor of Orléans." But Morin was only one of several actors who attributed different causes to racism in Orléans. All of them agreed that racism was a serious problem, but they could not agree on its causes. Compared to other incidents at the time which grabbed media attention, the uncertainty of events in Orléans allowed people to debate this. Morin's contribution was to turn to communications and social psychology to deploy the concept of "rumor." He dissolved the problem of racism into a problem of communication. This suggests that in order to understand the emergence of "racism without racists," we have to pay close attention to the context in which theories emerged to make it thinkable, and to the relationship between analyses of racism and communication. [ABSTRACT FROM AUTHOR]

Virtual spaces, where adolescents coexist, become new channels to reproduce or question the inequality and violence of gender roles. Among the different forms that digital gender violence takes, this article analyzes the dissemination of teasing, rumours and intimate photos by students in secondary schools in Argentina. For this purpose, 18 discussion meetings were held in which 199 students between 12 and 19 years old participated confidentially, anonymously and voluntarily. The results indicate that students experience violence as part of their daily digital life and in relation to their face-to-face experiences. Technologies offer new ways of disseminating intimacy, such as the creation of anonymous accounts, stickers and memes. The creation of anonymous accounts is another widely used strategy among this population group. Girls are the ones who suffer more situations and with greater consequences. Age is a factor that influences experiences, themes and attitudes towards violence, which are generally passive. In conclusion, it is highlighted that, although its normalization is accepted, certain practices are questioned, such as the viralization of intimate images, which reveals the importance of generating spaces for listening and reflection to prevent gender violence in adolescence. [ABSTRACT FROM AUTHOR]

This article explores the political persecution unleashed during the post-war period by McCarthyism, which led to the systematic accusation and harassment of American citizens for their leftist beliefs or Communist Party affiliations. This campaign of rumors and denunciations was particularly aggressive against film industry professionals, notably the Hollywood Ten. The emotional climate of the era was charged with fear and anger, emotions that were vividly manifested in the experiences of those targeted. By analyzing the correspondence and screenwriting of Dalton Trumbo, including his work on films like Papillon, this article examines the impact of this persecution and the strategies Trumbo used to confront the U.S. government, survive the blacklist, and sustain his career. It traces his journey from self-exile in Mexico, writing under pseudonyms, and using front names, to his eventual return and recognition in Hollywood. This analysis highlights the importance of constructing a cultural history that captures the collective emotional experiences of communities affected by such events, and it shows how Trumbo’s personal ordeals influenced the dialogues and narratives of the films he contributed to. [ABSTRACT FROM AUTHOR]

This article examines the formation of modern Japanese national consciousness, with a focus on the case of Ryūkyū-Okinawa. It discusses the role of the central government in shaping national consciousness, as well as the opposition and antagonism between government intentions and citizen consciousness. The article also explores the unique relationship between the center and periphery, particularly the implementation of nationally uniform legislation in Okinawa. The annexation of Okinawa into modern Japan had a significant impact on both Japan's trajectory and the unification of Okinawa, although it did not always align with the government's intentions. The article also discusses the historical background and perspectives of Yamagata Aritomo, a key figure in the government and military, who visited Okinawa and influenced government policies. [Extracted from the article]

There are myriads of bank boxes and vaults in the world and judging by some of the stories under scrutiny in this article, many of them contain Dead Sea Scrolls. The article analyses tales linked to three so-called ghost scrolls whilst focussing on contemporary manuscript tales as a phenomenon: What characterises such stories? How are they developed, kept alive, and passed down? What are their functions? I will argue that these tales serve as adaptable templates for market players and bring colour and glamor to the grey market. The ghost scroll is not so much a container of text as a placeholder for hype, dreams and longing. It influences contemporary academic imaginations, expectations, desires and affects scholars' interpretational frames. [ABSTRACT FROM AUTHOR]

With the prevalence of online social networks, rumors spread rampantly online. The versatility and complexity of human attitudes make dissemination more challenging to portray, so it is meaningful to develop a more comprehensive diffusion model. To this end, an improved SEIHR model considering three attitudes towards rumors is proposed. Then we deduce the stability of the dynamics model and use two scenarios to validate its accuracy. Meanwhile, rumor diffusion generates extensive social threats. To mitigate such threats, we introduce three immunization strategies and forge bonds among their basic reproduction numbers. Besides, we develop three synergistic optimal controls that vary with the time and degree to impede rumor diffusion. The analysis of the optimal control problem is conducted by Pontryagin's maximum principle. Next, experiments are conducted to verify the efficacy of the SEIHR model and control strategies. Our simulations show that adding the exposed and the hibernated undermines the impact of rumors and puts off terminal time. Additionally, immunization strategies effectively curb rumor diffusion. Moreover, the combination of three synergistic optimal controls leads to the smallest rumor scale and the least cumulative total costs. • An improved SEIHR model is put forward, considering three attitudes toward rumors. • Three immunization strategies are implemented to mitigate social threats. • Three synergistic optimal controls to impede rumor diffusion are implemented. [ABSTRACT FROM AUTHOR]

Information sharing on social media has become a common practice for people around the world. Since it is difficult to check user-generated content on social media, huge amounts of rumors and misinformation are being spread with authentic information. On the one hand, most of the social platforms identify rumors through manual fact-checking, which is very inefficient. On the other hand, with an emerging form of misinformation that contains inconsistent image–text pairs, it would be beneficial if we could compare the meaning of multimodal content within the same post for detecting image–text inconsistency. In this paper, we propose a novel approach to misinformation detection by multimodal feature fusion with transformers and credibility assessment with self-attention-based Bi-RNN networks. Firstly, captions are derived from images using an image captioning module to obtain their semantic descriptions. These are compared with surrounding text by fine-tuning transformers for consistency check in semantics. Then, to further aggregate sentiment features into text representation, we fine-tune a separate transformer for text sentiment classification, where the output is concatenated to augment text embeddings. Finally, Multi-Cell Bi-GRUs with self-attention are used to train the credibility assessment model for misinformation detection. From the experimental results on tweets, the best performance with an accuracy of 0.904 and an F1-score of 0.921 can be obtained when applying feature fusion of augmented embeddings with sentiment classification results. This shows the potential of the innovative way of applying transformers in our proposed approach to misinformation detection. Further investigation is needed to validate the performance on various types of multimodal discrepancies. [ABSTRACT FROM AUTHOR]

At present, a large number of rumors are mixed in with various kinds of news, such as current affairs, politics, social economy, and military activities, which seriously reduces the credibility of Internet information and hinders the positive development of various fields. In previous research on rumors, most scholars have focused their attention on the textual features, contextual semantic features, or single-emotion features of rumors but have not paid attention to the chain reaction caused by the hidden emotions in comments in social groups. Therefore, this paper comprehensively uses the emotional signals in rumor texts and comments to extract emotional features and determines the relationship between them to establish dual-emotion features. The main research achievements include the following aspects: (1) this study verifies that, in the field of affective characteristics, the combination of rumor-text emotion and comment emotion is superior to other baseline affective characteristics, and the detection performance of each component is outstanding; (2) the results prove that the combination of dual-emotion features and a semantic-feature-based detector (BiGRU and CNN) can improve the effectiveness of the detector; (3) this paper proposes reconstructing the dataset according to time series to verify the generalization ability of dual affective features; (4) the attention mechanism is used to combine domain features and semantic features to extract more fine-grained features. A large number of data experiments show that the dual-emotion features can be effectively compatible with an existing rumor detector, enhance the detector's performance, and improve the detection accuracy. [ABSTRACT FROM AUTHOR]

This article explores the theme of public transport in African literatures and aims to bridge the gap between mobilities research and African literary studies. It acknowledges the criticism that mobilities scholarship often focuses on the Global North and neglects experiences in the Global South. The article argues for a nuanced approach that considers historical and contextual specificities when studying African literary mobilities. It also emphasizes the importance of shedding light on local, intra-African forms of mobility and challenges the binary distinction between formal and informal public transportation. The article concludes by discussing the limited attention given to public transport in African literary studies and highlights the need to study its literary dimensions. The special issue of the journal further explores the politics and representations of public transport mobilities in African literatures, addressing topics such as accessibility, class, race, and the role of public transport in post-colonial societies. The studies emphasize the interconnected nature of public transport mobilities and call for more research in this area with a broader regional scope. [Extracted from the article]

The influence blocking maximization (IBM) problem aims to identify the most influential set of positive nodes in a social network to prevent the propagation of negative information throughout the network. However, existing studies have not considered factors such as the time delay of influence propagation and the value factor of nodes. Therefore, we first propose an influence propagation model called Time-Delayed Campaign-Oblivious Independent Cascade Model (TD-COICM), which incorporates time delay to simulate the decay of influence over time in social networks. Additionally, we present the Time and Value aware Influence Blocking Maximization (TVIBM) problem by considering the value factor of nodes under TD-COICM. More precisely, the value of a node is determined by its social influence and geographical distance from Rumor Source (RS). We demonstrate TVIBM is NP-hard and the influence function is monotonic and submodular. To overcome the low efficiency of the greedy algorithm, we combine the technique of Reverse Influence Sampling (RIS) and present the Reverse Influence Sampling with Time Delay (RIS-TD) algorithm. We prove that the RIS-TD algorithm has a high probability to return a 1 - 1 / e - ϵ approximate guarantee. To improve the efficiency, we further present the ERIS-TD algorithm by reducing the number of samples. Experiments on three real geographical social networks further confirm that our algorithms outperform other baseline algorithms in effectiveness, and outperform RIS-based algorithms in efficiency. [ABSTRACT FROM AUTHOR]

AbstractThe pervasive reach of the Internet has revolutionized information access and transmission, which has contributed to the widespread dissemination of rumors on social media. This study explored the impact of real-world integrated counter-rumor features, specifically community notes (which provide context and additional information from the online community) and related articles (which link to verified news sources that address the rumor), on online users’ intentions to believe and spread rumor tweets on social media. Additionally, we investigated how these features mitigate online users’ intentions to believe and spread different types of rumor messages, including wish and dread rumors. After conducting an experimental study with 201 online users on social media, we found that the presence of integrated counter-rumor features in rumor tweets can reduce online users’ intentions to believe and spread rumors, regardless of the specific feature used. While we observed no significant differences between the effects of community notes and related articles on overall online users’ intentions, a nuanced pattern emerged when we considered wish and dread rumors. Specifically, community notes proved more effective at reducing online users’ intentions to believe and spread wish-related rumors due to the diverse perspectives and opinions within the online community. By contrast, related articles were found to have greater efficacy at mitigating online users’ intentions to believe and spread dread rumors, as they can provide more concrete information to alleviate any associated fear or anxiety. Our findings contribute theoretical and practical insights for effectively countering the spread of rumor tweets on social media platforms. [ABSTRACT FROM AUTHOR]

Rumors are unverified pieces of information whose veracity status is unknown at the time of circulation. Preventing them at an early stage helps to mitigate the consequential loss and reduces the cost of recovering the nodes affected by rumors in the social network. However, existing research focuses more on rumor detection and control than on rumor prevention. In this article, we propose a Multi-Criteria Decision Making (MCDM) integrated approach for rumor prevention that addresses three issues. Firstly, the need for a rumor prevention model to debunk them at an early stage. Secondly, introduction of counter-rumor in the system as soon as a rumor is detected to reduce the time lag between rumor diffusion and counter-rumor diffusion. Thirdly, selection of trusted authorities as key nodes to initiate the counter-rumor diffusion. The proposed method is two-fold. Firstly, we propose Analytic Hierarchy Process - Technique for Order of Preference by Similarity to Ideal Solution (AHP-TOPSIS) method, an MCDM-based approach, to select the important nodes and host agents on them. Secondly, using agent nodes, we propose a counter-rumor diffusion model Susceptible-Infected-Recovered-Prevented-Agent (SIRPA) which is an improved variant of the popular epidemic model Susceptible-Infected-Recovered (SIR). The proposed SIRPA model is simulated on six social network datasets and multiple experiments are performed on these networks to validate the proposed work. The results show that our proposed SIRPA model is effective in preventing rumors in social networks and outperforms the baseline model. [ABSTRACT FROM AUTHOR]

The article in "Dialogue: A Journal of Mormon Thought" reflects on the impact of Lester Bush's groundbreaking research on the exclusion of Black men from priesthood ordination in the LDS Church. The article details Lester Bush's journey in uncovering historical documents that challenged the official narrative and led to significant changes within the Church. Despite facing shunning and adverse actions from Church leaders, Lester's work ultimately influenced key figures and contributed to a shift in Church policy. The article highlights Lester Bush's lasting legacy in Mormon studies and his pivotal role in shaping historical scholarship on important topics within the Church. [Extracted from the article]

The article discusses the comparison between New York State and Germany's high-voltage transmission siting laws in relation to expanding renewable energy grids. Both states have ambitious renewable energy targets to achieve by 2030, with Germany aiming for 80% and New York aiming for 70%. While Germany has established legislation to facilitate efficient scenario planning and project development, New York has also implemented laws to streamline the process for environmentally responsible siting of renewable energy projects. Challenges in grid planning and project approval exist for both states, with Germany's model offering valuable insights for New York's transition to a clean grid. [Extracted from the article]

Internet rumors have no factual basis, lack credibility, and can easily trigger social panic and group attacks. Measures to effectively intervene in rumors play a crucial role in curbing the spread of rumors. However, government departments have limited resources, and optimizing the intervention of rumors under the premise of conserving resources is valuable research. Therefore, from the government's perspective, this paper takes the maximization of the effect of rumor intervention and the depreciation of the intervention cost as the decision-making goals. Then, based on the uncertainty of government influence, cost, environmental purification benefit, and other factors, the degree of intervention was used as the decision-making variable to establish an uncertain multi-objective rumor intervention model. In addition, the model is mathematically derived, and its equivalent form is given. Finally, the model's effectiveness is verified by experimental comparison of different rumor categories and comparison with the classical model. This study provides solid theoretical support for the government to save resources and effectively intervene in spreading of rumors. [ABSTRACT FROM AUTHOR]

With the increasing popularity of social media, Online Social Networks (OSNs) are being used for promoting or discrediting various products or persons. As such, rumors are spread in the networks to increase or decrease the popularity of the target. Limiting the spread of rumors is an important research problem. In a promotion or smear campaign, we see multiple rumors about the target. Many existing works have explored rumor propagation and mitigation in social networks for a single rumor. However, users become biased towards the topic due to multiple rumors about it. A user influenced by the previous rumors about a topic is more likely to believe a rumor with similar content. Therefore, in this work, we analyze the spread of multiple rumors about a topic and formulate an optimization problem to identify the top k rumor spreaders. A Bayesian Inference has been applied to model the user bias caused by multiple rumors based on rumor content and user opinion about the topic. An Adaptive Ant Colony Optimization algorithm has been proposed to determine the top k rumor spreaders, who may be isolated from the network to reduce the impact of the rumors in the OSN. The efficacy of the proposed approaches is shown through experimentation on two datasets by considering the budget k. [ABSTRACT FROM AUTHOR]

With the popularity of social media, the speed and scale of information dissemination has increased exponentially, among which rumors have become a prominent issue that arouses public concern. Due to the lack of comprehensive consideration of population flow, propagation mechanisms, and effective rumor refutation strategies, as well as related dynamical analysis in traditional models, we propose an extended ISR rumor spreading model based on the traditional SIR (Susceptible, Infected, Recovered) model. The average field equation is established by introducing the flow of population, trust and suspicion mechanism and two rumor-refuting strategies, and the basic reproduction number of homogeneous and heterogeneous networks and the stability of the rumor-free equilibrium point are analyzed. Finally, our experimental simulation shows that the trust mechanism increases the speed and scale of the spread of rumors in the network, while the suspicion mechanism inhibits the spread of rumors and gradually reduces the spread scale. In addition, the dual rumor refutation strategy has a good inhibition effect on the spread of rumors, especially the direct rumor refutation by the disseminator, and has been verified in different models. These findings enhance our understanding of rumor dynamics and suggest strategies for mitigating misinformation in social networks. [ABSTRACT FROM AUTHOR]

"City of Sediments: A History of Seoul in the Age of Colonialism" by Se-Mi Oh is a book that explores the vibrant and complex city of Seoul in the 1920s during the period of colonialism. The author focuses on the sensory experiences of the city, blending sound and text to create an urban synesthesia. The book challenges traditional linear approaches to history and instead uses a spatial model of sediment to uncover the diverse elements that coexist in close proximity. It also highlights the role of everyday experiences, language, and community-building in resisting colonial power. The book offers valuable insights into the spatial and visual dimensions of colonialism and is recommended for those interested in studying colonial cities. [Extracted from the article]

Purpose: Sharing and disseminating debunking information are critical to correcting rumours and controlling disease when dealing with public health crises. This study investigates the factors that influence social media users' debunking information sharing behaviour from the perspective of persuasion. The authors examined the effects of argument adequacy, emotional polarity, and debunker's identity on debunking information sharing behaviour and investigated the moderating effects of rumour content and target. Design/methodology/approach: The model was tested using 150 COVID-19-related rumours and 2,349 original debunking posts on Sina Weibo. Findings: First, debunking information that contains adequate arguments is more likely to be reposted only when the uncertainty of the rumour content is high. Second, using neutral sentiment as a reference, debunking information containing negative sentiment is shared more often regardless of whether the government is the rumour target, and information containing positive sentiment is more likely to be shared only when the rumour target is the government. Finally, debunking information published by government-type accounts is reposted more often and is enhanced when the rumour target is the government. Originality/value: The study provides a systematic framework for analysing the behaviour of sharing debunking information among social media users. Specifically, it expands the understanding of the factors that influence debunking information sharing behaviour by examining the effects of persuasive cues on debunking information sharing behaviour and the heterogeneity of these effects across various rumour contexts. [ABSTRACT FROM AUTHOR]

In our modern world, rumours have triggered chaos and conflicts. Study of the dynamics of rumor propagation helps yield effective countermeasures to resist rumour propagation. It is a major task to study an ordinary differential equation (ODE) model on high-order incidence and treatment function for its dynamical behaviours. First and foremost, we build an ODE model depending on the actual transmission mechanism. Secondly, we study the basic properties of solutions including non-negativity, boundedness and situation of inexistence of the limit cycle. Thirdly, we study the necessary conditions of the equilibrium points for the existence, stability and instability. Furthermore, this study analyses bifurcations induced by parameters around the equilibrium point of rumour-spreading. Finally, several numerical simulations are given to show diverse dynamics behaviours of the model on different parameters and the factors affecting rumour propagation are theoretically analysed, which proves the validity of the theoretical analysis. [ABSTRACT FROM AUTHOR]

This article argues that there was a crisis within the British state over policy towards Northern Ireland (1972–76). The Conservative then Labour government pursued a broadly bipartisan and conciliatory policy, culminating in the failed powersharing experiment (1974). By contrast, the New Right within the Conservative Party but also powerful elements in the Army and Intelligence Services, the Royal Ulster Constabulary and Unionism opposed conciliation as 'appeasement' and even treachery. They claimed conciliation and rumours of British political support for withdrawal encouraged the IRA and undermined the repressive approach that was necessary to win. From this perspective, the Conservative then Labour government were, in effect, '... striving to facilitate the achievement of the PIRA's aims' and so they resisted government policy. The crisis intensified as more troops were killed, and the Army suffered severe problems of morale, recruitment and retention. The Army's emergency created a need to withdraw troops and Ulsterise the conflict. Although this constrained the Labour government's ability to defend powersharing, the Army also appeared reluctant to support the government's conciliatory policy. The crisis of the British state over Northern Ireland (1972–76) provides part of the context in which allegations about the undermining of Prime Minister Harold Wilson and the Labour government in the 1970s should be considered. [ABSTRACT FROM AUTHOR]

This article examines the sportswriting of the 1920s, which has been criticized for its use of jargon, flowery language, and omission of negative aspects of sports heroes like Babe Ruth. It discusses how the press protected Ruth's image by downplaying or omitting negative information, and explores the unwritten code followed by sports reporters at the time. The article also discusses the shift in sportswriting towards revealing personal details about athletes' lives, contrasting it with the more heroic portrayal of athletes in the 1920s. It highlights the impact of books like "Ball Four" in changing the landscape of sports journalism and questions the role of sportswriters. [Extracted from the article]

Social media reconstitutes the idea of 'abroad' as a geographical place, shortens the symbolic distance between borders, and renders the local and global into one almost seamless space. This seamlessness is both metaphorical and symbolic, where happenings on the spatial or geographical 'abroad' are rendered through context onto both the spatial and virtual 'local'. Context via social media and other virtual spaces therefore serves to not only demarcate the local from the abroad, but also serves to at once create a seamless, borderless 'glocal' where texts are immediately 'translated' and 'transposed' into different forms. For this paper, I am interested in Twitter/X Spaces, where Kenyans congregate every day to discourse and reinforce certain public scripts. I use the euphemisms of 'serving hot tea' and 'character development', and how the use of these metaphors become spaces within which news, gossip, 'gender wars', and rumour get arbitrated. I am interested in the ways in which these vocabularies flatten, as well as expose, the distances between the 'here' and the 'there', and the multiple layers they espouse. I also end with a postscript on the 2024 political uprisings in Kenya that had their root and nexus on social media spaces. [ABSTRACT FROM AUTHOR]

This study focused on the news production volume of media, personal current affairs, and personal general channels that coexist on social media after the confirmation of political rumors. It also examined user reactions according to sentiments expressed in video titles. The decline in personal general channels was large after the confirmation, but personal current affairs channels were not affected by authenticity. Analysis of right-wing patterns of comments, users of personal current affairs channels responded more actively to titles that express positive/negative sentiments than neutral titles. However, the study found no significant changes in media videos. This study emphasizes the need for news producers to verify political rumors and the critical participation of users. [ABSTRACT FROM AUTHOR]

The film "Afwaah" directed by Sudhir Mishra explores the dangers of rumors and disinformation in the era of digital communication. It depicts how false information can spread rapidly on social media, negatively impacting people's lives and perpetuating biases. The film also delves into the interplay between patriarchy, religious sectarianism, and conservative extremism. It highlights the use of click farms and disinformation campaigns to manipulate public opinion and the consequences of such actions, including communal violence and political killings. The movie portrays the journey of the protagonists as they navigate a complex and dangerous situation while being pursued by a relentless community. [Extracted from the article]

This paper investigates rumor propagation in a multilingual environment, taking into account language usage variations. Firstly, a 2I2S2R model is proposed within a heterogeneous network framework that incorporates both immunologic and cross-transmitted mechanisms. Secondly, the paper calculates the basic reproduction number R0 by the next-generation matrix method. Thirdly, the local asymptotic stability and the global asymptotic stability are further explored, which indicate that whether the rumor continuously spreads or becomes extinct is determined by the threshold. Finally, the numerical simulation and sensitivity analysis are given to illustrate the effectiveness of theoretical results and the influence of model parameters on rumor spreading. [ABSTRACT FROM AUTHOR]

Misinformation such as fake news and rumors is a serious threat for information ecosystems and public trust. The emergence of large language models (LLMs) has great potential to reshape the landscape of combating misinformation. Generally, LLMs can be a double‐edged sword in the fight. On the one hand, LLMs bring promising opportunities for combating misinformation due to their profound world knowledge and strong reasoning abilities. Thus, one emerging question is: can we utilize LLMs to combat misinformation? On the other hand, the critical challenge is that LLMs can be easily leveraged to generate deceptive misinformation at scale. Then, another important question is: how to combat LLM‐generated misinformation? In this paper, we first systematically review the history of combating misinformation before the advent of LLMs. Then we illustrate the current efforts and present an outlook for these two fundamental questions, respectively. The goal of this survey paper is to facilitate the progress of utilizing LLMs for fighting misinformation and call for interdisciplinary efforts from different stakeholders for combating LLM‐generated misinformation. [ABSTRACT FROM AUTHOR]

We study in a general graph-theoretic formulation a long-range percolation model introduced by Lamperti [27]. For various underlying digraphs, we discuss connections between this model and random exchange processes. We clarify, for all $n \in \mathbb{N}$ , under which conditions the lattices $\mathbb{N}_0^n$ and $\mathbb{Z}^n$ are essentially covered in this model. Moreover, for all $n \geq 2$ , we establish that it is impossible to cover the directed n -ary tree in our model. [ABSTRACT FROM AUTHOR]

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This article explores the political persecution unleashed during the post-war period by McCarthyism, which led to the systematic accusation and harassment of American citizens for their leftist beliefs or Communist Party affiliations. This campaign of rumors and denunciations was particularly aggressive against film industry professionals, notably the Hollywood Ten. The emotional climate of the era was charged with fear and anger, emotions that were vividly manifested in the experiences of those targeted. By analyzing the correspondence and screenwriting of Dalton Trumbo, including his work on films like Papillon, this article examines the impact of this persecution and the strategies Trumbo used to confront the U.S. government, survive the blacklist, and sustain his career. It traces his journey from self-exile in Mexico, writing under pseudonyms, and using front names, to his eventual return and recognition in Hollywood. This analysis highlights the importance of constructing a cultural history that captures the collective emotional experiences of communities affected by such events, and it shows how Trumbo’s personal ordeals influenced the dialogues and narratives of the films he contributed to.