CNN Effect Research Articles

The CNN effect in Indonesia: re-arguing the relevance of communication theories in international relations

The CNN effect in Indonesia: re-arguing the relevance of communication theories in international relations

The CNN Effect and South Korea’s Humanitarian Response to North Korea: A Media-Driven Policy?

The CNN Effect and South Korea’s Humanitarian Response to North Korea: A Media-Driven Policy?

Analysis of Media Influence on Military Decision-Making

Information warfare challenges, including the "CNN Effect," are increasing in quantity and complexity as the internet saturates modern life. Media communications, reliable or not, are constantly injected into American life, affecting opinions, decision-making, and actions—which may result in terrifying and permanent consequences when the media influences military members and government leaders. This research focuses on the immersive learning environment—an engaging, simulation-based educational experience with realistic conflict scenarios where students apply lesson objectives through hands-on activities. Instructors conduct immersive learning in the US Air Force Academy's (USAFA) Multi-Domain Laboratory. Traditionally, students were taught military strategy in a classroom where they engaged in wargaming by rolling dice using a board game. Now, the Military & Strategic Studies (MSS) Department uses hands-on, real-time wargaming with unique hardware and software to teach future leaders how to apply classroom concepts using experiential learning. Wargames are critical for meeting the priorities of the Joint Chiefs of Staff—specifically, preparing leaders to conduct joint operations in all domains by integrating experiential learning. The guidance explains that "curricula should leverage live, virtual, constructive, and gaming methodologies with wargames… to develop deeper insight and ingenuity." The wargame with media provides external influences like news and information from various sources, which may influence students' decision-making process, resulting in "The CNN Effect." "The CNN Effect" is a short-hand way to explain how news reports drive government leaders' responses, including military decision-making. This project builds upon existing research uniquely because this study examines decision-making from multiple leaders based on the same simulated media in USAFA's immersive learning environment. This research uses mixed methods analysis to explore how students act based on the wargame media inputs and compare course outcome differences after receiving enhanced Information Operations education or when exposed to different quantities of broadcasts. The Information Warfare (news literacy) module enhances education on the media's influence on decision-making and trust for students. Students learned to identify and research information sources, analyze biases, opinion versus fact-based reporting, and compare news reports from various outlets.

The Indian Media’s Interface with Diplomacy

Diplomacy and its institutions have been constantly changing. The manner in which diplomacy was practised in the earlier centuries is vastly different from how it is being practised in the twenty-first century. These changes range from the emergence of the training of messengers, the start of record keeping of diplomatic exchanges, the establishment of resident embassies, codification of formal diplomatic processes, widening domain of actors and issues, the use of multilateral conferences, use of summitry and many others. This evolution has been both a result of and further resulted in changing the larger socio-political-economic dimensions that the world has undergone. Among the myriad contextual changes, the revolution in communications, information and media technology has been phenomenal. This has brought into focus terms like the CNN effect and Vietnam War Syndrome where it is argued that media has had an influence in directing foreign policy choices of countries. Hence, this article seeks to analyse the media’s interface with the most important institution of diplomacy, the Ministry of Foreign Affairs. It specifically focuses on the Ministry of External Affairs (MEA), India. Has the news media acted either as an impediment or an accelerator to diplomatic practice? Has the information overload caused the diplomatic fraternity to face a loss of autonomy in any manner? With the objective of seeking an answer to these questions from diplomacy’s perspective, the article explores the evolution of the External Publicity Division of the MEA, India. The External Publicity Division as it is generally known has been the nodal division leading the institutions’ interface with the media. The actuality of media’s interface with diplomacy in India’s case will be set in the backdrop of the existing literature in the fields of media, diplomacy and foreign policy.

Media w stosunkach międzynarodowych w epoce nadmiaru informacji

The objective of the article is to check the functionality of the leading concepts explaining the role of media in international relations and foreign policy in the fourth era of political communication. The author focuses on the “CNN effect” and “manufacturing consent” concepts to illustrate how the Almond–Lippman consensus was rejected. The study is framed by the idea of globalization of media and uses the cases from the EU (Poland and the Netherlands), the relations with Russia and the recent migration crisis on the Polish–Belarussian border to assess the role and position of media in international relations in the age of information overload. The author concludes that despite the deep mediatization of societies in the 21st century, the governments are able to take charge of the discourses in international communication using their strategic narratives.

The “CNN Effect” and Its Influence on US Foreign Policy Decision-Making

The “CNN effect” is a term that has been used to describe the influence of 24-hour news coverage on foreign policy decision-making, particularly in the context of the United States. The term was coined in the early 1990s following the Gulf War, during which CNN's live coverage of the conflict was widely credited with shaping public opinion and influencing US foreign policy decisions. Since then, the concept of the “CNN effect” has been the subject of much debate and analysis in the field of media and foreign policy. The aim of this paper is to examine the impact of the 'CNN effect' on US foreign policy, with a specific focus on its role in shaping public opinion and influencing policy outcomes. Through a case study of US foreign policy initiatives in Somalia, this study analyzes the relationship between media coverage and policy decisions. The methodology used in this study involves conducting an in-depth analysis of media coverage and policy decisions in the selected cases. A combination of primary and secondary sources, including news reports, government documents, and academic literature, was used to develop a comprehensive understanding of the “CNN effect” on US foreign policy decision-making. The findings of this study suggest that the “CNN effect” is a real phenomenon that has had a significant influence on US foreign policy decision-making. Media coverage can create pressure on policymakers to take action by generating a sense of urgency and demand for response among the public and other stakeholders. In addition, media coverage can shape the international community's response to a crisis or conflict, which can further influence policymakers. However, the impact of media coverage on foreign policy decisions is complex and multifaceted, as decision-makers must balance the information presented in the media with other factors, such as strategic interests and long-term goals. This paper contributes to the understanding of the relationship between media coverage and foreign policy decision-making, highlighting the importance of considering the influence of media in policy outcomes. Understanding the “CNN effect” can inform the strategies of policymakers, journalists, and the general public in shaping the discourse and decisions of US foreign policy.
 
 Received: 05 May 2022 / Accepted: 18 May 2023 / Published: 20 May 2023

Rethinking 3D-CNN in Hyperspectral Image Super-Resolution

Recently, CNN-based methods for hyperspectral image super-resolution (HSISR) have achieved outstanding performance. Due to the multi-band property of hyperspectral images, 3D convolutions are natural candidates for extracting spatial–spectral correlations. However, pure 3D CNN models are rare to see, since they are generally considered to be too complex, require large amounts of data to train, and run the risk of overfitting on relatively small-scale hyperspectral datasets. In this paper, we question this common notion and propose Full 3D U-Net (F3DUN), a full 3D CNN model combined with the U-Net architecture. By introducing skip connections, the model becomes deeper and utilizes multi-scale features. Extensive experiments show that F3DUN can achieve state-of-the-art performance on HSISR tasks, indicating the effectiveness of the full 3D CNN on HSISR tasks, thanks to the carefully designed architecture. To further explore the properties of the full 3D CNN model, we develop a 3D/2D mixed model, a popular kind of model prior, called Mixed U-Net (MUN) which shares a similar architecture with F3DUN. Through analysis on F3DUN and MUN, we find that 3D convolutions give the model a larger capacity; that is, the full 3D CNN model can obtain better results than the 3D/2D mixed model with the same number of parameters when it is sufficiently trained. Moreover, experimental results show that the full 3D CNN model could achieve competitive results with the 3D/2D mixed model on a small-scale dataset, suggesting that 3D CNN is less sensitive to data scaling than what people used to believe. Extensive experiments on two benchmark datasets, CAVE and Harvard, demonstrate that our proposed F3DUN exceeds state-of-the-art HSISR methods both quantitatively and qualitatively.

Hybrid Pipeline for Building Arabic Tunisian Dialect-standard Arabic Neural Machine Translation Model from Scratch

Deep Learning is one of the most promising technologies compared to other methods in the context of machine translation. It has been proven to achieve impressive results on large amounts of parallel data for well-endowed languages. Nevertheless, for low-resource languages such as the Arabic Dialects, Deep Learning models failed due to the lack of available parallel corpora. In this article, we present a method to create a parallel corpus to build an effective NMT model able to translate into MSA, Tunisian Dialect texts present in social networks. For this, we propose a set of data augmentation methods aiming to increase the size of the state-of-the-art parallel corpus. By evaluating the impact of this step, we noticed that it has effectively boosted both the size and the quality of the corpus. Then, using the resulted corpus, we compare the effectiveness of CNN, RNN and transformers models to translate Tunisian Dialect into MSA. Experiments show that a better translation is achieved by the transformer model with a BLEU score of 60 vs., respectively, 33.36 and 53.98 with RNN and CNN models.

The Influence of News Coverage on Humanitarian Aid: The Bureaucrats’ Perspective

ABSTRACT We examine if and how news coverage influences governments’ humanitarian aid allocations, from the perspective of the senior bureaucrats involved in such decision-making. Using rare in-depth interviews with 30 directors and senior policymakers in 16 of the world’s largest donor countries, we found that the majority of these bureaucrats believed that sudden-onset, national news coverage can increase levels of emergency humanitarian aid allocated to a crisis. They said that this influence operated by triggering other accountability institutions (the public, civil society, elected officials) who put pressure on aid bureaucracies to announce additional funding. However, these practitioners claim that annual humanitarian aid allocations—which are much larger—are unaffected by news pressure. Intriguingly, we also find that many respondents interpret a lack of news coverage as grounds for increasing their annual aid allocations to what they call “forgotten crises”. We argue that “bureaucratic mediatisation”, rather than the “CNN Effect” or the “Cockroach Effect”, provides the most appropriate theoretical perspective to understand these multiple, concurrent and indirect forms of media influence. These findings have important implications for government donors, news organisations and aid agencies, and for our wider understanding of how news coverage may influence foreign policy.

Deep reasoning neural network analysis to predict language deficits from psychometry-driven DWI connectome of young children with persistent language concerns.

This study investigated whether current state‐of‐the‐art deep reasoning network analysis on psychometry‐driven diffusion tractography connectome can accurately predict expressive and receptive language scores in a cohort of young children with persistent language concerns (n = 31, age: 4.25 ± 2.38 years). A dilated convolutional neural network combined with a relational network (dilated CNN + RN) was trained to reason the nonlinear relationship between “dilated CNN features of language network” and “clinically acquired language score”. Three‐fold cross‐validation was then used to compare the Pearson correlation and mean absolute error (MAE) between dilated CNN + RN‐predicted and actual language scores. The dilated CNN + RN outperformed other methods providing the most significant correlation between predicted and actual scores (i.e., Pearson's R/p‐value: 1.00/<.001 and .99/<.001 for expressive and receptive language scores, respectively) and yielding MAE: 0.28 and 0.28 for the same scores. The strength of the relationship suggests elevated probability in the prediction of both expressive and receptive language scores (i.e., 1.00 and 1.00, respectively). Specifically, sparse connectivity not only within the right precentral gyrus but also involving the right caudate had the strongest relationship between deficit in both the expressive and receptive language domains. Subsequent subgroup analyses inferred that the effectiveness of the dilated CNN + RN‐based prediction of language score(s) was independent of time interval (between MRI and language assessment) and age of MRI, suggesting that the dilated CNN + RN using psychometry‐driven diffusion tractography connectome may be useful for prediction of the presence of language disorder, and possibly provide a better understanding of the neurological mechanisms of language deficits in young children.

SITUATING THE CNN EFFECT IN NIGERIAN CONTEXT: ANALYSING IMPACT ON DIPLOMACY AND LOCAL TELEVISION

Scholars believe that the global media of television influence foreign policy-making through a presentation of compelling images of events happening. It is termed the CNN effect or factor. However, the extent of this effect is not yet determined especially on Nigeria foreign policy and local television. The CNN Effect stands on the agenda-setting theory. The factor implies that the global television goes further to tell policymakers what it should think, what to think about, how to think about what they think, and what to do with what they think and think about. This study is carried out through analysis of secondary data and observation of global and local televisions. Beside already observed effects of global television on foreign policymaking such as making decisions in haste without proper considerations and sideling of diplomatic protocols, the study found some side effects of the influence of global media; one of which is that global television force policymakers to be unduly attached to them (global television). The greater revelation from the CNN effect is not on Nigeria’s foreign policy but on local television industry where the local television loses audience, credibility and revenue to global television. The study recommends better funding and training for local television.

Aplikasi Media Sosial sebagai Alat Politik Donald Trump (Netnografi Cuitan Trump di Twitter)

Every political actors, either at local, national, or global levels, tends to demonstrate their characteristics, including Donald John Trump. Different from his predecessors, Trump decides his communication style by using simple, easily understood, and solid words. Meanwhile, for the media, Trump tends to prioritize social media, such as Twitter, as his tool. Using the concept of CNN Effect and Agenda-Setting, this paper aims to analyze the interests of Trump in using Twitter as the communication tools and verify the concept of CNN Effect by using the case study of the Trump’s utilization of social media. Then, by applying agenda setting, the authors analyze the content of Trump’s tweet and the interests following. Literature study is fully applied in this paper. Whereas, the time scope of this research is limited from Trump’s campaign period until September 2020. This research argues that the effects of Trump’s tweets in his Twitter account have similar implications with the concept of CNN Effect. This also confirms that CNN Effect can occur not only in mass media, but also in social media. Secondly, the paper argues that Trump consistently voice particular issues through his Twitter account in order to achieve his plans manifested in his campaign.

Globalización y poder: la consolidación de la comunicación internacional como disciplina. Artículo de revisión

A tour of the theoretical development and the main research lines of international communication is presented. To do this, the appearance of communication in the configuration of power in four aspects (hard, soft, sharp and strategic narrative) is analyzed. The critical perspective and the Anglo-Saxon mastery on the subject are examined, with evidence from France, Germany, or Latin America. Five axes of future research are anticipated, such as the strengthening of the theoretical and methodological bases with interdisciplinary methods; the nature and characteristics of the international journalists (correspondents versus false news); the management of populist communication in the face of a political globalization with leaders that hinder the conventional journalistic ethos; the analysis of the structures; and global information systems in a multipolar scenario and less “CNN effect” than expected, and the constant innovation dynamics of propaganda.

Mediji kao instrument strateške komunikacije u oružanim sukobima - Si-En-En efekat

Media, politics and public opinion are mutually conditioned social categories. Their interdependence is particularly pronounced in armed conflicts, especially in the context of armed interventions. The forum of the interaction of these phenomena is framed by the paradigm of strategic communication, which is transmitted to the public through the actions of entities identified as strategic communicators to achieve a motivating effect for reactions that are in line with communicators' interests. One of the emerging forms of strategic communication in all its forms and contents is the CNN effect. The paper contributes to the definition of the CNN effect as a broader concept than the television station, after which it was named. Furthermore, the paper analyzes the relationship between politics, the media and the public to gain public support for military intervention. The paper also provides an analysis of the CNN effect in the function of strategic communication on the example of the media use of bloodshed in the Markale market during the war in Bosnia and Herzegovina in 1995, with an analysis of the US actions and effects to support the idea of military intervention.

PERAN MEDIA MASSA DALAM POLITIK LUAR NEGERI: KASUS DI INDONESIA

As a country embraces democratic values in its political system, mass media has an increasing role in influencing government policy making including foreign policy making. Study on mass media relations with foreign policy making has developed to level conceptual even theoretical framework in mass communication study. This article shows that theoretical and analytical approaches toward media and foreign policy decision making have at least seven analytical frameworks. Those tools of analysis are CNN Effect, the Indexing Hypothesis, Media – Policy Interaction Model, Positioning Theory Agenda – Setting Theory, Propaganda Model dan Manufacturing Consent. In Indonesia, study on relations between media and foreign policy has not been developed. But there is prominent case in foreign policy change of Indonesia regarding Iranian nuclear issue in United Nations Security Council.

CNN Effect in Yemen War

This article is a study of the involvement of the United States (US) in the Yemeni War thas has already taken place since 2015 by using the 'CNN Effect' theory. The authors analyzed documents and mass media coverage and conducted discourse analysis on US mainstream media news, namely CNN and the New York Times. The result of this research shows that CNN and the New York Times did not report the Yemeni War proportionally so that public opinion ignored this war and did not encourage further action from the US government and United Nations to stop the war. This way of reporting is in line with US’ economic-political interests in Yemen and US support for the Saudi Arabia.

PCANet-Based Convolutional Neural Network Architecture for a Vehicle Model Recognition System

Vehicle model recognition plays a crucial role in intelligent transportation systems. Most of the existing vehicle model recognition methods focus on locating a large global feature or extracting more than one local subordinate-level feature from a vehicle image. In this paper, we propose the principal component analysis network-based convolutional neural network (PCNN) and pinpoint only one discriminative local feature of a vehicle, which is the vehicle headlamp, for vehicle model recognition. The proposed model eliminates the need for locating and segmenting the headlamp precisely. In particular, PCNN ascertains the effectiveness of both principal component analysis and CNN in extracting hierarchical features from a vehicle headlamp image and also reducing the computational complexity of the traditional CNN system. To further enhance the training procedure while still keeping the discriminative property of the network, the fully connected layer is updated by backpropagation optimized with stochastic gradient descent. The proposed method is validated using a data set that comprises 13 300 training images and 2660 testing images, respectively. The model is robust against various distortions. Experiments show that PCNN outperforms state-of-the-art techniques with an average accuracy of 99.51% over 38 vehicle makes and models using the PLUS data set. In addition, the effectiveness of the proposed method is also validated using the public CompCars data set, achieving 89.83% accuracy over 357 vehicle models.

Media dan Terorisme di Uni Eropa:

Tulisan ini bertujuan mendeskripsikan hubungan media dan terorisme yang sama-sama saling mempengaruhi dan saling memanfaatkan. Studi kasus yang diambil adalah rangkaian teror di Paris (2015) dan pengeboman di Manchester (2017) karena kedua kasus ini menjadi isu global yang melibatkan jaringan pemberitaan global. Dengan menggunakan teori Efek CNN dan analisis media, penulis melihat bahwa terorisme dimanfaatkan untuk tujuan kepentingan korporasi media global dan sebaliknya, media merupakan salah satu sarana penting bagi kelompok teror untuk memperluas pengaruh dan ancamannya terhadap masyarakat global. Kemajuan teknologi informasi membuat media, sadar atau tidak, justru menjadi ‘teman terbaik’ bagi kelompok teroris karena medialah yang menjadi penyampai pesan utama mereka.

Moving Beyond the CNN Effect or Stuck in the Middle? How Relational Sociology Remaps Media and Security Studies

Recent studies of media and security continue to be limited by various theoretical and ontological commitments, despite their claims of “moving beyond” or “reconsidering” the CNN effect. In this article, I review the two dominant research paradigms for media and security. The first research paradigm, which includes the CNN-effect literature, imagines media as an independent actor in the policy-making process. The second research paradigm portrays media as a neutral channel, passing along the message of foreign policy elites. Each of these paradigms remains wedded to an actor-centered and choice-theoretic approach to media and security, as witnessed by recent attempts to study the CNN effect. I argue that a new research paradigm based on relational sociology actually moves media and security studies beyond the CNN effect and resolves the fundamental theoretical limitations associated with it.

Syria &amp; the CNN Effect: What Role Does the Media Play in Policy-Making?

Syria's devastating war unfolds during unprecedented flows of imagery on social media, testing in new ways the media's influence on decision-makers. Three decades ago, the concept of a “CNN Effect” was coined to explain what was seen as the power of real-time television reporting to drive responses to humanitarian crises. This essay explores the role traditional and new media played in U.S. policy-making during Syria's crisis, including two major poison gas attacks. President Obama stepped back from the targeted air strikes later launched by President Trump after grisly images emerged on social media. But Trump's limited action did not shift policy. Interviews with Obama's senior advisors underline that the media do not drive strategy, but they play a significant role. During the Syrian crisis, the media formed part of what officials describe as constant pressure from many actors to respond, which they say led to policy failures. Syria's conflict is a cautionary tale.