Search Results (567)

This study investigated how the front-page designs of digital newspapers differ based on institutional origin—comparing platforms that were born-digital with those that have transitioned from print—focusing specifically on their appeal to Generation Z audiences. Grounded in Media Richness Theory, this research employed a mixed-methods approach that combined a quantitative visual content analysis with qualitative semi-structured interviews. In the quantitative phase, the front pages of ten Saudi digital newspapers (five digital-native and five digital-migrant) were systematically analyzed to identify differences in their layouts, typography, multimedia usage, and interactivity. The qualitative phase then explored Generation Z users’ perceptions of the design clarity, visual engagement, and interactive affordances, as well as their suggestions for improving interface usability. The results indicate that digital-native newspapers more closely adhere to contemporary digital design standards and demonstrate significantly higher levels of media richness. This study contributes to digital journalism scholarship by offering both theoretical insights into interface-centered richness and practical design recommendations for enhancing user experience and engagement among younger audiences. Full article

Hate speech is a complex topic that transcends language, culture, and even social spheres. Recently, the spread of hate speech on social media sites like Facebook has added a new layer of complexity to the issue of online safety and content moderation. This study seeks to minimize this problem by developing an Arabic script-based tool for automatically detecting hate speech in Roman Urdu, an informal script used most commonly for South Asian digital communications. Roman Urdu is relatively complex as there are no standardized spellings, leading to syntactic variations, which increases the difficulty of hate speech detection. To tackle this problem, we adopt a holistic strategy using a combination of six machine learning (ML) and four Deep Learning (DL) models, a dataset from Facebook comments, which was preprocessed (tokenization, stopwords removal, etc.), and text vectorization (TF-IDF, word embeddings). The ML algorithms used in this study are LR, SVM, RF, NB, KNN, and GBM. We also use deep learning architectures like CNN, RNN, LSTM, and GRU to increase the accuracy of the classification further. It is proven by the experimental results that deep learning models outperform the traditional ML approaches by a significant margin, with CNN and LSTM achieving accuracies of 95.1% and 96.2%, respectively. As far as we are aware, this is the first work that investigates QLoRA for fine-tuning large models for the task of offensive language detection in Roman Urdu. Full article

This study examines the evolving relationship between online media coverage and protest movements by analyzing year-long demonstrations in Israel against Prime Minister Benjamin Netanyahu. Through comprehensive qualitative thematic analysis and content analyses of 219 online newspaper articles from five major Israeli newspapers; 324 social media posts across Facebook, Instagram, and Twitter; and 9 semi-structured interviews with protest leaders, this research identifies a gradual paradigm shift in protest representation in online media. The findings reveal a transition from the traditional “protest paradigm”—which frames protests as violent and remote through warlike discourse and visual distancing—toward an emerging “our protest paradigm”, characterized by rhetorical and visual proximity to protesters. This new paradigm manifests through personal testimonies in mainstream media and portrait photography on social media platforms, both creating a sense of closeness and accountability. The study further reveals a significant disconnect between protest leaders’ perceptions and legacy media, as leaders increasingly view traditional media as irrelevant despite their advisers’ recommendations to engage with it. Using polysystem theory as a theoretical framework, this research demonstrates how two media systems—legacy media and social media—operate with epistemological rigidity, challenging the previously established notion of “competitive symbiosis” between protesters and journalists. This investigation offers a novel analytical perspective through the lens of distance, illuminating how changing dynamics in online information transfer are reshaping protest coverage and production. The resulting paradigm model explains the coexistence of two simultaneous protest paradigms and provides valuable insights into the contemporary relationship between social movements, legacy media, and digital platforms in an evolving media ecosystem. Full article

This study explores the thematic structure and editorial focus of the digital media landscape in Bulgaria by analyzing one year of online news publications from eight major media outlets. The data were collected through a custom-built web scraping application developed in Java, which enabled the automated extraction and processing of full-text articles from publicly accessible news websites. The structured dataset, generated during the scraping process, records word-level occurrences in both article titles and bodies, along with publication dates and URLs. By applying lexical frequency analysis and temporal tracking, this study identifies the most frequently used words and platform-specific usage patterns. The findings reveal clear distinctions in editorial focus between public broadcasters, private national media, and international outlets. Additionally, the analysis highlights how title construction and word prominence vary depending on platform type and media strategy. This study demonstrates the potential of web scraping and computational text analysis as scalable tools for investigating media systems in small and transitional democracies. Full article

Psychology is a core discipline in understanding why and how individuals choose to engage in sustainable action. This paper uses social representations theory to explore the rising use of eco/green prefixes for psychology concepts through a critical analysis of the concept of eco/green fatigue. It argues that this term, which originated in the world of popular online news media, has typically been treated in academic psychology discussions using existing psychology concepts in the same way as eco-anxiety and eco-grief, which hides important features of the phenomenon that need to be better understood. The paper presents an analysis of eco-fatigue based on a critical review of the existing psychology literature, qualitative online archival analyses, and an exploratory quantitative survey study. The survey study was conducted with a sample of 182 students and non-students and analysed using principal components and cluster analysis. The paper provides evidence that simply adding an eco/green prefix to an existing psychology concept without a systematic empirical investigation into the phenomenon can result in overly simplistic conceptual frameworks that do not lead to sound practical conclusions. A preliminary empirical examination of the social representation of eco-fatigue in the public arena suggested that inappropriate sustainability messaging and bad business behaviour may be more of a barrier to sustainability action than the beliefs or attitudes held by individuals. Full article

Video-sharing platforms have significantly influenced social justice movements by creating unprecedented opportunities for mobilization and support. However, YouTube’s unique role and platform culture in facilitating social justice movements remain relatively understudied. This research addresses this gap by analyzing video content related to two prominent online social justice movements: #BLM and #StopAAPIHate. We conducted a comprehensive thematic analysis of a dataset comprising 489 videos obtained using the YouTube Data API. Thematic categories were developed to explore the identities of video creators, the type of information conveyed, storytelling techniques, and promotional features utilized. Our findings indicate that public figures, vloggers, and news reporters are the most frequent creators of videos supporting these movements. The primary purpose of these videos is to share movement-related knowledge and personal stories of discrimination. Most creators primarily promote their social media accounts and do not extensively utilize platform features such as live streaming, merchandise sales, donation requests, or sponsorships to actively support these social justice initiatives. Full article

The purpose of this study is to thoroughly examine the technical competencies of university websites in Northern Cyprus, as well as the contributions of Learning Management System (LMS) platforms integrated with these websites to user experience, with a focus on efficiency and sustainability in online education. This study adopts a “mixed-method” research model, which combines both quantitative and qualitative research methods for data collection and analysis, with the results being evaluated together. The participants of the research consist of the websites of universities in the Turkish Republic of Northern Cyprus (TRNC) and the IT department managers who will be consulted for their opinions on these websites. A total of 15 university websites were analyzed within the scope of the study, and interviews were conducted with the IT managers of these universities. During this process, analysis tools such as SimilarWeb, Alexa, Ahrefs, Moz, and SEMrush were utilized. For qualitative analysis, a semi-structured interview method was chosen to gather the views of IT managers on the websites. The findings emphasize the need for universities to optimize their digital strategies. Differences in website performance directly affect the strength of universities’ digital presence, while technological infrastructure, user experience, and the integration of educational tools emerge as key factors in improving this performance. Based on the results of this study, some universal solutions are proposed to optimize the digital strategies of universities in Cyprus. Full article

The present study explores the emerging role of “public affairs live streamers” on the short video platform Kuaishou, examining how these individuals have evolved into new forms of rural elites, expanding opportunities for civic participation and rural governance in China. Through content analysis and case studies, the research identifies six key themes central to the streamers’ discourse: land and property issues, financial aid and subsidies, policy and governance, advocacy for the public, educational outreach, and customs. These themes underscore their role as rural knowledge elites who bridge the gap between the government and rural residents through digital platforms. The study further examines the mechanisms behind the emergence of “public affairs live streamers”. Empowered by the platform, these streamers effectively convert their cultural capital into online social capital, which may then be partially transformed into offline social influence and economic returns. However, their empowerment is constrained by the platform’s algorithm distribution mechanisms and opaque content regulation, making the conversion of capital unstable, traffic-dependent, and challenging to sustain. Linking to the broader socio-political landscape, the study delves into the empowering role of “public affairs live streamers” in society. These online rural elites blend knowledge with digital skills to facilitate public engagement and inspire civic awareness in rural areas through their activities. Nonetheless, their contribution to rural governance and civilization is often limited to informal mediation and emotional expression, with limited capacity to foster rational discourse or deeper improvements in rural governance. Overall, this study contextualizes the rise of rural elites within China’s rapid technological and rural development, offering a fresh perspective on how digital media can supplement governance strategies and enhance grassroots’ civic participation. Based on this analysis, the study proposes recommendations for improving platform governance and integrating public affairs streamers into broader participatory frameworks, thereby stabilizing their empowering effects and promoting sustainable rural governance. Full article

This paper explores death practices and how societies have “placed the dead”. It examines the implications of analyzing death in the digital age, using Portugal as a case study. In a country where death has long been tied to Catholic traditions, how do people respond to rising cremation rates, online memorials, and social media groups dedicated to the deceased? Are they open to “digital death ways”, such as AI-driven chatbots, holograms, and platforms that preserve messages beyond one’s lifetime? Following Recuber’s call for empirical studies on how, when, and by whom technology is used to communicate with the dead, this research serves as a preliminary step toward a broader project on Portuguese digital death practices. It focuses on two key themes: changes in the treatment of physical remains due to evolving perceptions of the deceased and the relationships between the living and the dead (also in the new form of digitally resurrected personas). Full article

This study explores the information–communication discourse in modern recruitment by applying the Design Thinking (DT) methodology to enhance employee selection and integration strategies. By incorporating digital tools and empathetic approaches, this study examines innovative practices that improve candidate experience and ensure alignment with organizational culture. This study follows the DT framework, encompassing empathy, problem definition, and ideation, with a research sample including candidates, employees, and HR professionals. Methods such as desk research, interviews, diary methods, and P/C matrix diagonalization, supported by original metrics, assess the effectiveness of these approaches. The findings highlight that digital tools, particularly gamification and online assessments, significantly enhance recruitment quality, increase efficiency, reduce hiring time, and improve cultural alignment. Additionally, this study develops informational constructs of knowledge, skills, and attitudes, offering deeper insights into key factors for successful hiring. By integrating new media and technological solutions, this research contributes to transforming traditional recruitment practices into more candidate-centred processes. Further evaluation through complementary studies is recommended to determine the long-term impact of digital tools on recruitment outcomes and employee selection success. Full article

Youth media consumption and disordered eating practices have historically been subjects of moral panics, often resulting in protective, deficit-based interventions like content removal. We argue for interventions which instead equip youth to evaluate and manage risks in their online environments, building upon their existing “information sensibility” practices. Drawing upon ethnographic research and intervention testing with 77 participants in the US and India, we analyze how youth (aged 13–26), including those with diverse political perspectives and those recovering from disordered eating (DE), engage with online news and health information. Participants generally algorithmically encountered (rather than searched for) information online, and their engagement was shaped more by social motivations—like belonging—than truth seeking. Participants interpreted online information collaboratively, relying on social cues and peer validation within their online communities. They demonstrated preference for personal testimonies and relatable sources, particularly those with similar social identities. We propose resilience-building interventions that build upon these youth online information practices by: (1) leveraging peer networks, promoting critical information engagement through collaborative learning and peer-to-peer support within online communities; (2) developing social media sensibility, equipping youth to critically evaluate information sources in situ; (3) providing pathways offline, connecting youth to desired in-person communities; and (4) encouraging probabilistic thinking. Full article

This study analyses social media networks in tourism using graphs focusing on user influence, hashtag patterns, and engagement. This study aims to reveal the structural function of core users, development of hashtags, and interaction patterns that construct tourism discourses. Using NodeXL 2024 for social network visualization and clustering analysis, this study measures centrality, modularity, and geodesic distances for influential user detection, topical dissemination, and engagement pattern identification. The results uncover bridging nodes between different communities, the proliferation of thematic hashtags related to sustainability and cultural heritage, and the role of emotional and visual storytelling in the use of engagement patterns. The theoretical implications also progress SNA application in tourism studies by illuminating aspects of how online discourses coalesce and the effect of SNA on access. In practical terms, this study indicates that destination marketers must consider leveraging key influencers, using strategic types of hashtags, and by monitoring engagement at key times to maximize effective destination marketing and to enhance crisis communication. These contributions notwithstanding, limitations involve the omission of sentiment analysis and the necessity for longitudinal data. By exploring new emerging platforms like TikTok and Instagram, researchers can begin to understand the more relevant trends of digital engagement. The present research offers a data-driven approach for facilitating the significance of integrating social media strategies with network externalities for tourism operators. Full article

Open-source disaster intelligence (OSDI) is crucial for improving situational awareness, disaster preparedness, and real-time decision-making. Traditional OSDI frameworks often rely on social media data, which are susceptible to misinformation and credibility issues. This study proposes a novel AI-driven framework utilizing automated data collection from 444 large-scale online news portals, including CNN, BBC, CBS News, and The Guardian, to enhance data reliability. Over a 514-day period (27 September 2023 to 26 February 2025), 1.25 million news articles were collected, of which 17,884 were autonomously classified as disaster-related using Generative Pre-Trained Transformer (GPT) models. The analysis identified 185 distinct countries and 6068 unique locations, offering unprecedented geospatial and temporal intelligence. Advanced clustering and predictive analytics techniques, including K-means, DBSCAN, seasonal decomposition (STL), Fourier transform, and ARIMA, were employed to detect geographical hotspots, cyclical patterns, and temporal dependencies. The ARIMA (2, 1, 2) model achieved a mean squared error (MSE) of 823,761, demonstrating high predictive accuracy. Key findings highlight that the USA (6548 disasters), India (1393 disasters), and Australia (1260 disasters) are the most disaster-prone countries, while hurricanes/typhoons/cyclones (5227 occurrences), floods (3360 occurrences), and wildfires (2724 occurrences) are the most frequent disaster types. The framework establishes a comprehensive methodology for integrating geospatial clustering, temporal analysis, and multimodal data processing in OSDI. By leveraging AI automation and diverse news sources, this study provides a scalable, adaptable, and ethically robust solution for proactive disaster management, improving global resilience and preparedness. Full article

The goal of the study is to reveal the reasons (strategies) behind the use of “virtual masks” (fake profiles and altered identities) by real (human) users of social media networks (SMNs) within a cultural context, specifically in Armenia. Applying Erving Goffman’s Dramaturgical Theory and concepts of virtual identity, the research explores how users construct their online personas, either reflecting their real identities or modifying them to achieve specific communicative goals. A statistical analysis of the most popular SMNs in Armenia, combined with semi-structured interviews with 400 users, reveals diverse approaches to virtual communication. While SMNs facilitate news consumption, socializing, and professional networking, many users deliberately conceal personal information or engage in deceptive practices. Approximately 35% prefer anonymity when following others, and 24% of men and 11% of women admit to posting false information. Additionally, 26% of men and 12% of women alter their online appearance to enhance attractiveness. The study also highlights the role of anonymity in expressing controversial opinions, particularly in political discussions. Men are more inclined than women to create fake accounts and manipulate information to avoid social repercussions. Ultimately, the study highlights how “virtual masks” in Armenia reflect both cultural attitudes and broader global digital communication trends. Full article

The travel and transportation sectors continuously fight to stay up to date with new advancements in technology. Disruptive technologies, such as Artificial Intelligence (AI), are being used to develop businesses, enhance economic growth, revolutionize existing industries, create new opportunities, and increase productivity and efficiency. Notwithstanding the several advantages that this technology may bring, there is still little research on AI use in the travel and transportation sectors. This research contributes to this still understudied field to fill a gap in the literature by putting out a novel, thorough, and as far as we know not yet tested until now theoretical model, designed with the combination of the outcome of a literature meta-analysis study with Travel Experience and the Intention to Recommend technology constructs. A quantitative investigation using an online questionnaire was administered through social media and reached a total of 100 European participants. Structural equation modelling (SEM) was employed to test the suggested model empirically. The findings highlight that the user’s attitude towards AI is strongly influenced by Performance Expectancy and that the Intention to Use this technology is significantly influenced by Initial Trust and Attitude. Theoretical and practical contributions, limitations, and future areas of research are discussed. Full article