Hasil untuk "Journalism. The periodical press, etc."

Sang Lee, Samar Ben Romdhane

This research demonstrates how confirmation and disconfirmation biases manifest based on individuals’ political affiliations when processing a self-disclosure message in the context of a political crisis. An experiment presented a crisis message in which a politician voluntarily revealed his campaign finance violations. The results revealed that confirmation bias and disconfirmation bias significantly influenced the information processing of participants based on their political affiliations. Democrat participants were significantly more open to and forgiving of the crisis message when it featured a Democrat politician. In contrast, Republican participants showed a strong tendency to be more critical and less forgiving under the same conditions. However, this pattern reversed when a Republican politician was shown in the crisis message. The research also tested moderated mediation hypotheses: the interaction effects between study participants’ political affiliations and politicians’ parties were mediated by perceived attitude toward the politician and crisis responsibility, leading to ethical perceptions about the politician. The study contributes to our understanding of the mechanisms underlying political polarization and the ways in which the biases of confirmation and disconfirmation influence individuals’ processing of political messages.

Jiajian Xie, Hubery Yin, Chen Li et al.

Diffusion models have achieved remarkable generative quality but remain bottlenecked by costly iterative sampling. Recent training-free methods accelerate diffusion process by reusing model outputs. However, these methods ignore denoising trends and lack error control for model-specific tolerance, leading to trajectory deviations under multi-step reuse and exacerbating inconsistencies in the generated results. To address these issues, we introduce Error-aware Trend Consistency (ETC), a framework that (1) introduces a consistent trend predictor that leverages the smooth continuity of diffusion trajectories, projecting historical denoising patterns into stable future directions and progressively distributing them across multiple approximation steps to achieve acceleration without deviating; (2) proposes a model-specific error tolerance search mechanism that derives corrective thresholds by identifying transition points from volatile semantic planning to stable quality refinement. Experiments show that ETC achieves a 2.65x acceleration over FLUX with negligible (-0.074 SSIM score) degradation of consistency.

Zhuoqi Lyu, Qing Ke

Subject classification schemes are foundational to the organization, evaluation, and navigation of scientific knowledge. While expert-curated systems like Scopus provide widely used taxonomies, they often suffer from coarse granularity, subjectivity, and limited adaptability to emerging interdisciplinary fields. Data-driven alternatives based on citation networks show promise but lack rigorous, external validation against the semantic content of scientific literature. Here, we propose a novel quantitative framework that leverages classification tasks to evaluate the effectiveness of journal classification schemes. Using over 23 million paper abstracts, we demonstrate that labels derived from k-means clustering on Periodical2Vec (P2V)--a periodical embedding learned from paper-level citations--yield significantly higher classification performance than both Scopus and other data-driven baselines (e.g., citation, co-citation, and Node2Vec variants). By comparing journal partitions across classification schemes, two structural patterns emerge on the map of science: (1) the reorganization of disciplinary boundaries--splitting overly broad categories (e.g., "Medicine" into "Oncology", "Cardiology", and other specialties) while merging artificially fragmented ones (e.g., "Chemistry" and "Chemical Engineering"); and (2) the identification of coherent interdisciplinary clusters--such as "Biomedical Engineering", "Medical Ethics", and "Information Management"--that are dispersed across multiple categories but unified in citation space. These findings underscore that citation-derived periodical embeddings not only outperform traditional taxonomies in predictive validity but also offer a dynamic, fine-grained map of science that better reflects both the specialization and interdisciplinarity inherent in contemporary research.

Dahyun Lee, Jonghyeon Choi, Jiyoung Han et al.

As online news consumption grows, personalized recommendation systems have become integral to digital journalism. However, these systems risk reinforcing filter bubbles and political polarization by failing to incorporate diverse perspectives. Stance detection -- identifying a text's position on a target -- can help mitigate this by enabling viewpoint-aware recommendations and data-driven analyses of media bias. Yet, existing stance detection research remains largely limited to short texts and high-resource languages. To address these gaps, we introduce \textsc{K-News-Stance}, the first Korean dataset for article-level stance detection, comprising 2,000 news articles with article-level and 21,650 segment-level stance annotations across 47 societal issues. We also propose \textsc{JoA-ICL}, a \textbf{Jo}urnalism-guided \textbf{A}gentic \textbf{I}n-\textbf{C}ontext \textbf{L}earning framework that employs a language model agent to predict the stances of key structural segments (e.g., leads, quotations), which are then aggregated to infer the overall article stance. Experiments showed that \textsc{JoA-ICL} outperforms existing stance detection methods, highlighting the benefits of segment-level agency in capturing the overall position of long-form news articles. Two case studies further demonstrate its broader utility in promoting viewpoint diversity in news recommendations and uncovering patterns of media bias.

Marta De la Mano González, Chelo Sánchez Serrano

El objetivo de esta investigación es identificar y analizar la producción científica sobre pódcast en el ámbito de la comunicación y su impacto, desde sus comienzos en 2004 hasta 2023, a través de las revistas indexadas en Scopus. Para el análisis bibliométrico de los datos, se ha utilizado la herramienta de evaluación de la producción científica Scival. Entre los resultados obtenidos, se constata el importante crecimiento experimentado por la producción científica sobre pódcast en los últimos tres años, particularmente en 2023, cuando casi se duplica la producción del año anterior. Además, este trabajo ha constatado el posicionamiento internacional de España como uno de los principales productores de investigación científica sobre el tema, hasta el punto de situarse en segundo lugar en número de citas y a la cabeza en número de visualizaciones de la producción sobre pódcast. Sin embargo, el impacto de las publicaciones españolas resulta limitado en relación con su producción. El estudio revela que los artículos publicados en español, aunque reciban muchas visualizaciones por el interés que despiertan sus títulos y resúmenes en inglés, finalmente no son consultados o citados en la misma medida por autores que no dominan este idioma. Por último, cabe destacar la prevalencia de la coautoría, aunque sigue siendo un reto la colaboración internacional.

Dimity Stephen

This study investigates the viability of distinguishing articles in questionable journals (QJs) from those in non-QJs on the basis of quantitative indicators typically associated with quality. Subsequently, I examine what can be deduced about the quality of articles in QJs based on the differences observed. I contrast the length of abstracts and full-texts, prevalence of spelling errors, text readability, number of references and citations, the size and internationality of the author team, the documentation of ethics and informed consent statements, and the presence erroneous decisions based on statistical errors in 1,714 articles from 31 QJs, 1,691 articles from 16 journals indexed in Web of Science (WoS), and 1,900 articles from 45 mid-tier journals, all in the field of psychology. The results suggest that QJ articles do diverge from the disciplinary standards set by peer-reviewed journals in psychology on quantitative indicators of quality that tend to reflect the effect of peer review and editorial processes. However, mid-tier and WoS journals are also affected by potential quality concerns, such as under-reporting of ethics and informed consent processes and the presence of errors in interpreting statistics. Further research is required to develop a comprehensive understanding of the quality of articles in QJs.

Subigya Nepal, Arvind Pillai, William Campbell et al.

Mental health concerns are prevalent among college students, highlighting the need for effective interventions that promote self-awareness and holistic well-being. MindScape pioneers a novel approach to AI-powered journaling by integrating passively collected behavioral patterns such as conversational engagement, sleep, and location with Large Language Models (LLMs). This integration creates a highly personalized and context-aware journaling experience, enhancing self-awareness and well-being by embedding behavioral intelligence into AI. We present an 8-week exploratory study with 20 college students, demonstrating the MindScape app's efficacy in enhancing positive affect (7%), reducing negative affect (11%), loneliness (6%), and anxiety and depression, with a significant week-over-week decrease in PHQ-4 scores (-0.25 coefficient), alongside improvements in mindfulness (7%) and self-reflection (6%). The study highlights the advantages of contextual AI journaling, with participants particularly appreciating the tailored prompts and insights provided by the MindScape app. Our analysis also includes a comparison of responses to AI-driven contextual versus generic prompts, participant feedback insights, and proposed strategies for leveraging contextual AI journaling to improve well-being on college campuses. By showcasing the potential of contextual AI journaling to support mental health, we provide a foundation for further investigation into the effects of contextual AI journaling on mental health and well-being.

Giohanny Olave

En noviembre de 2018, el entonces alcalde de Bucaramanga (Colombia) agredió físicamente a un concejal del municipio, cuando mantenían una discusión política acalorada. El video de la agresión circuló profusamente en redes sociales y fue utilizado por la Procuraduría General de la Nación como prueba fehaciente para suspender del cargo al alcalde. En este artículo se analiza un conjunto de comentarios virtuales de internautas en reacción al video de las agresiones. El corpus de comentarios se extrajo de la publicación realizada por la casa de noticias El Tiempo en la red social YouTube, a través de la herramienta YouTube Comment Scraper, entre el 28 de noviembre y el 28 de diciembre de 2018, para concentrarse en las reacciones que el hecho político suscitó durante el primer mes en que fue publicado. Desde una perspectiva interpretativa interdisciplinar del Análisis del Discurso se determinan las regularidades de esas reacciones, los modos de justificar explícita e implícitamente los actos violentos y los efectos políticos que terminaron por favorecer la imagen pública del alcalde en ese momento. Se concluye insertando el caso estudiado dentro de las discusiones actuales sobre la representación democrática y el ascenso de matrices ideológicas antipolíticas en el discurso público de quienes gobiernan.

Alfonso Nieto Tamargo

Los soportes móviles adquieren mayor penetración en el mercado de la comunicación digital. Son claves en su definición los conceptos de movilidad, soporte y servicio. El más desarrollado es el teléfono móvil, según la Unión Internacional de Telecomunicaciones, en el presente año habrá 4,000 millones de unidades de teléfono móvil. El siguiente artículo explica cómo la intemporalidad y la ubicuidad han conformado una cultura del móvil. En el actual mercado el teléfono es un producto soporte de Relaciones y es un servidor de contenidos que tiene especial importancia económica. Interesa observar sus características actuales para proyectar sus tendencias.

Miya Williams Fayne

The Black press is often conceptualized as an advocacy press, but in the current digital environment, in which there are numerous entertainment-focused outlets, what exactly constitutes advocacy is fraught. Perceptions of advocacy, which have previously been associated with hard news content, are broadening to accommodate the entertainment content on Black news websites. Informed by interviews with journalists and focus groups with readers, this research finds that there are two different categorizations of advocacy journalism – hard advocacy and soft advocacy. Some editors and consumers believe the Black press should contain hard advocacy content, such as political activism coverage, while others perceive entertainment in the Black press, which provides positive coverage of African Americans and additional representation of Black life, as soft advocacy. Expanding advocacy conceptions provides further nuance and insight into how the Black press functions in the new media age.

Amit Kumar Das, Bidyarthi Dutta

There exist huge chunk of academic items receiving no citation years after years and remaining beyond the veil of ignorance of the academic audience. These are known as uncited items. Now, the question is, why a paper fails to get citation? The attribute of incapability of receiving citation may be termed as Uncitedness. This paper traces brief history of the concept of uncitedness sprouted first in 1964 in an article entitled Cybernetics, homeostasis and a model of disease by Gerson Jacobs. The concept of uncitedness was scientometrically first explained by Garfield in 1970. The uncitedness of twelve esteemed Indian physics and astronomy journals over a twelve years' (2009-2020) time span is analysed here. Besides Uncitedness Factor (UF), three other indicators are introduced here, viz. Citation per paper per Year (CY), h-core Density (HD) and Time-normalised h-index (TH). The journal-wise variational patterns of these four indicators, i.e. UF, CY, HD and TH and the relationships of UF with other three indicators are analysed. The calculated numerical values of these indicators are observed to formulate seven hypotheses, which are tested by F-Test method. The average annual rate of change of uncited paper is found 67% of total number of papers. The indicator CY is found temporally constant. The indicator HD is found nearly constant journal-wise over the entire time span, while the indicator TH is found nearly constant for all journals. The UF inversely varies with CY and TH for the journals and directly varies with TH over the years. Except few highly reputed Indian journals in physics and astronomy, majority other journals face the situation of uncitedness. The uncitedness of Indian journals in this field outshines the same for global journals by 12%, which indicates lack of circulation and timely reach of research communication to the relevant audience.

Rima Hazra, Aryan, Hardik Aggarwal et al.

New researchers are usually very curious about the recipe that could accelerate the chances of their paper getting accepted in a reputed forum (journal/conference). In search of such a recipe, we investigate the profile and peer review text of authors whose papers almost always get accepted at a venue (Journal of High Energy Physics in our current work). We find authors with high acceptance rate are likely to have a high number of citations, high $h$-index, higher number of collaborators etc. We notice that they receive relatively lengthy and positive reviews for their papers. In addition, we also construct three networks -- co-reviewer, co-citation and collaboration network and study the network-centric features and intra- and inter-category edge interactions. We find that the authors with high acceptance rate are more `central' in these networks; the volume of intra- and inter-category interactions are also drastically different for the authors with high acceptance rate compared to the other authors. Finally, using the above set of features, we train standard machine learning models (random forest, XGBoost) and obtain very high class wise precision and recall. In a followup discussion we also narrate how apart from the author characteristics, the peer-review system might itself have a role in propelling the distinction among the different categories which could lead to potential discrimination and unfairness and calls for further investigation by the system admins.

Mattía Panza Guardatti, Eugenia Mitchelstein, Pablo J. Boczkowski

Esta investigación examina la agenda online de dos de los diarios más relevantes en Argentina -Clarín y La Nación- a través de un análisis cuantitativo de las noticias publicadas en las respectivas páginas de inicio y en las respectivas publicaciones en las cuentas oficiales de estos dos medios en Facebook y Twitter. El análisis de 3.780 noticias demuestra que existen diferencias entre las agendas propuestas por los sitios y las noticias publicadas en las redes sociales de los mismos. Los resultados exponen que los diarios mantienen una agenda relacionada a los asuntos públicos en sus páginas de inicio, mientras que en las redes sociales priorizan noticias vinculadas a los asuntos no públicos. La divergencia es menor temprano por la mañana y aumenta a lo largo del día. A partir de estos hallazgos este trabajo indaga los motivos de esta selección y las diferentes temáticas que seleccionan los medios.

Alberto Baccini, Lucio Barabesi, Mahdi Khelfaoui et al.

This paper explores, by using suitable quantitative techniques, to what extent the intellectual proximity among scholarly journals is also a proximity in terms of social communities gathered around the journals. Three fields are considered: statistics, economics and information and library sciences. Co-citation networks (CC) represent the intellectual proximity among journals. The academic communities around the journals are represented by considering the networks of journals generated by authors writing in more than one journal (interlocking authorship: IA), and the networks generated by scholars sitting in the editorial board of more than one journal (interlocking editorship: IE). For comparing the whole structure of the networks, the dissimilarity matrices are considered. The CC, IE and IA networks appear to be correlated for the three fields. The strongest correlations is between CC and IA for the three fields. Lower and similar correlations are obtained for CC and IE, and for IE and IA. The CC, IE and IA networks are then partitioned in communities. Information and library sciences is the field where communities are more easily detectable, while the most difficult field is economics. The degrees of association among the detected communities show that they are not independent. For all the fields, the strongest association is between CC and IA networks; the minimum level of association is between IE and CC. Overall, these results indicate that the intellectual proximity is also a proximity among authors and among editors of the journals. Thus, the three maps of editorial power, intellectual proximity and authors communities tell similar stories.

Hülya Öztekin

İkinci Dünya Savaşı döneminde Türkiye’nin yürüttüğü dış politika ve dönemin uluslararası politik koşulları, pek çok noktada iç politikaya ilişkin kararların ve uygulamaların da temel belirleyicisi olmuştur. Bu çerçevede siyasal iktidarın, özellikle savaş döneminde aktif hale gelen ve basın da dahil pek çok alanda etkinlik gösteren Turancı harekete karşı tutumu da ülkenin dış politikadaki manevralarına ve uluslararası konjonktüre bağlı olarak gelişmiştir. Almanya’yla kurulan dostane ilişkiler ve Almanya’nın savaşta aldığı galibiyetler bağlamında Turancı hareketin 1943 yılının sonlarına kadar resmî ideoloji tarafından hoşgörüyle karşılanması, hatta bizzat hükümet çevrelerinde destek bulması; buna karşın Almanya’yla ilişkilerin kesildiği 1944 yılında Turancı hareketin de beklenmedik bir şekilde tasfiye edilmesi bu etkiyi açıkça ortaya koymaktadır. Turancı çevrelere yönelik bu tasfiye süreci Alman yanlısı ve Turancı yayınların teker teker kapatılmasıyla başlamış, Sabahattin Ali-Nihal Atsız davası sonrasında gelişen gözaltı ve tutuklamalar ve son olarak ‘ırkçılık-Turancılık davası’yla devam etmiştir. Bu çalışmada, Mayıs 1944’te başlayıp Mart 1947’de sona eren ve Türk siyasi literatürüne ‘ırkçılık-Turancılık davası’ olarak geçen davanın dönemin yazılı basınında ele alınış biçimi incelenmiştir. Çalışmanın amacı, Türk siyasi tarihinin önemli gelişmelerinden biri olan ırkçılık-Turancılık davası ve bu dava etrafında gelişen olayların dönemin iç ve dış siyasetiyle olan bağını ortaya koymak; ulusal gazetelerin bu davaya yaklaşımı çerçevesinde dönemin basın-iktidar ilişkilerine ışık tutmaktır. Tarihsel betimleyici analiz yöntemi ile hazırlanan çalışmada ilgili dönemde yayımlanan ulusal gazetelerden Akşam, Cumhuriyet, Tan, Tanin, Ulus, Vakit gazeteleri taranmış, konu ile ilgili haber ve köşe yazıları analiz edilmiştir.

Mike Thelwall

Microsoft Academic is a free academic search engine and citation index that is similar to Google Scholar but can be automatically queried. Its data is potentially useful for bibliometric analysis if it is possible to search effectively for individual journal articles. This article compares different methods to find journal articles in its index by searching for a combination of title, authors, publication year and journal name and uses the results for the widest published correlation analysis of Microsoft Academic citation counts for journal articles so far. Based on 126,312 articles from 323 Scopus subfields in 2012, the optimal strategy to find articles with DOIs is to search for them by title and filter out those with incorrect DOIs. This finds 90% of journal articles. For articles without DOIs, the optimal strategy is to search for them by title and then filter out matches with dissimilar metadata. This finds 89% of journal articles, with an additional 1% incorrect matches. The remaining articles seem to be mainly not indexed by Microsoft Academic or indexed with a different language version of their title. From the matches, Scopus citation counts and Microsoft Academic counts have an average Spearman correlation of 0.95, with the lowest for any single field being 0.63. Thus, Microsoft Academic citation counts are almost universally equivalent to Scopus citation counts for articles that are not recent but there are national biases in the results.

Kim Fletcher