Content Creation Research Articles

A Content Analysis Study of Distortion's Influence on Drum and Bass Music Production

This study uses content analysis and draws upon aesthetic theory and technological determinism as theoretical frameworks to explore contemporary approaches to the use of distortion within drum and bass production. To achieve this, it investigates online video tutorials created by professional drum and bass producers and online content creators in order to extract insights into their common working practice when using distortion in their work. The analysis highlights a prevalent use of aggressive distortion to transform bass timbres, which is a trend originating in the 1990s that continues to shape the genre's evolving aesthetic. This research provides unique insights into the evolution. and impact of distortion and shows how established techniques persist while subtly evolving within the ever-changing production ecosystem.

Beyond Sentiment Exploring the Dynamics of AIGC-Generated Sports Content and User Engagement on Xiaohongshu

This study explores the impact of AIGC-generated sports content on user sentiment and engagement on Xiaohongshu, a Chinese social media platform.Using MediaCrawler, we collected posts and comments related to sports topics generated by AI. Sentiment analysis was performed using SnowNLP to classify comments as positive or negative, with 57.1% showing positive sentiment and 42.9% negative. Despite the prevalence of positive sentiment, no significant difference in engagement (measured by likes) was observed between positive and negative comments.Temporal analysis revealed that user engagement is event-driven, with spikes in positive sentiment during major sports events. Additionally, word cloud analysis highlighted promotional and spam-like themes, suggesting challenges in content moderation. The interaction patterns showed a skewed distribution, with a small number of highly active users dominating discussions.The findings suggest that timing, relevance, and event alignment are more critical than sentiment polarity in driving engagement.The study provides insights for content creators and platforms on optimizing AIGC strategies through trend alignment and effective user collaboration.

Generative AI and Media Content Creation: Investigating the Factors Shaping User Acceptance in the Arab Gulf States

This article aims to investigate the factors that affect behavioural intention (BI) and user behaviour (UB) among Arabian users of generative artificial intelligence (GenAI) applications in the context of media content creation. The study’s theoretical framework is grounded in the unified theory of acceptance and use of technology (UTAUT2). A sample of 496 users was analysed using the partial least squares structural equation modelling technique (PLS-SEM). The results revealed that BI is significantly influenced by performance expectancy, effort expectancy, social influence, hedonic motivation, habit, and user trust, with hedonic motivation having the greatest impact. In terms of UB, facilitation conditions, habit, user trust, and BI were all found to have a positive and significant impact. This study contributes to the existing theory on the utilisation of GenAI applications by organising findings pertaining to the use of AI technology for media content creation.

A review of the role of artificial intelligence in Journalism

Artificial intelligence (AI) technologies have revolutionized journalism in the digital era. This study is constructed on a general literature review revealing the role of AI in journalism and emphasizes the following key facets: (i) automated reporting, (ii) automated content creation, (iii) automated transcription and translation, (iv) data mining and analysis, (v) fact-checking and verification, and (vi) content personalization. The role of AI is observed in creating news reports like financial digests, sports outcomes, and weather updates, gearing up the automated content creation, transcribing the interviews, providing multilingual support for content translation, data mining and analysis, detecting fake news, personalizing the content in line with audience's preferences. The wide application of AI in journalism automates routine journalistic tasks, thereby improving efficacy and productivity and saving time and effort. Though AI is transforming journalism, there are several challenges facing journalism using AI, including biased algorithms, data availability and quality, data privacy and security, the need for training and education, transparency, and cost concerns. Journalists must be trained to identify and address issues such as data privacy, algorithmic bias, and the ethical implications of adopting AI in news reporting. News agencies should also implement strong data protection measures and transparent AI algorithms to overcome these challenges. They must attain a balance between considering user privacy and offering personalized content. It is paramount to have robust regulatory frameworks to oversee the utility of AI in journalism. Also, warranting ethical standards in AI implementation is crucial to preserving journalistic integrity.

InclusiveWeb : A Smart Browser Approach to Enhancing Web Accessibility for Users with Diverse Disabilities

This article presents InclusiveWeb, an innovative accessibility-focused web browser designed to enhance digital inclusion for users with diverse disabilities. The browser addresses the persistent challenge of widespread non-compliance with web accessibility standards by implementing real-time content adaptation mechanisms, disability-specific tools, and a highly customizable user interface. InclusiveWeb's architecture incorporates advanced machine learning algorithms to dynamically modify web content, offering tailored solutions for users with visual impairments, dyslexia, language disorders, cognitive disabilities, and ADHD. The article details the browser's design principles, technical considerations, and user experience features, supported by a comprehensive evaluation methodology involving user studies with various disability groups. Results demonstrate significant improvements in task completion rates, user satisfaction, and overall accessibility compared to standard browsers. While acknowledging limitations and areas for future research, this article highlights InclusiveWeb's potential to revolutionize web accessibility, shifting the paradigm from reliance on content creators' compliance to browser-level adaptations. The implications of this approach for web accessibility standards, digital inclusion, and future technological developments are discussed, emphasizing the browser's role in creating a more equitable digital landscape.

Trending extinctions: online interest in recently extinct animals

AbstractHalf of all species are predicted to face extinction by the end of the century. Despite this, awareness of certain species' extinctions remains surprisingly muted, highlighting the need to improve and quantify public awareness. We explore the connection between biodiversity loss and public awareness by quantifying the changes in online interest on Twitter (now known as X) and Wikipedia both before and after the extinctions of eight species and following their reclassification in the IUCN Red List. Our findings reveal that extinction announcements generally spike online interest for most species, albeit briefly on Twitter (i.e. tweets and retweets about species), while Wikipedia (i.e. article pageviews of species) exhibits a more prolonged interest. IUCN reports were generally not associated with increased interest. Coordinated media coverage, especially when aligned with broader environmental narratives and key events, enhanced the impact of extinction announcements. On Twitter, spatially we observed a shift from local to global interest of users following extinction. We also found a small subset of influential users on Twitter, including content creators and media organisations, who disproportionately shaped conservation discussions. Environmentally oriented individuals and organisations also play a significant role, collectively comprising a third of the top retweeted users. Overall, these results highlight the need for conservation bodies, such as the IUCN, to engage more directly both with media organisations and content creators in order to drive public interest for conservation efforts, especially for less charismatic species. The tragedy of species extinction necessitates such efforts to ensure sustained and meaningful public awareness. Our findings also show that while social media outlets can generate global interest quickly, which may drive public discussions regarding ongoing extinctions and potential future de‐extinctions, this is likely to be short‐lived, underscoring the importance of alternative platforms such as Wikipedia, which can foster longer‐term engagement.

Uncovering Key Factors That Drive the Impressions of Online Emerging Technology Narratives

Social media platforms play a significant role in facilitating business decision making, especially in the context of emerging technologies. Such platforms offer a rich source of data from a global audience, which can provide organisations with insights into market trends, consumer behaviour, and attitudes towards specific technologies, as well as monitoring competitor activity. In the context of social media, such insights are conceptualised as immediate and real-time behavioural responses measured by likes, comments, and shares. To monitor such metrics, social media platforms have introduced tools that allow users to analyse and track the performance of their posts and understand their audience. However, the existing tools often overlook the impact of contextual features such as sentiment, URL inclusion, and specific word use. This paper presents a data-driven framework to identify and quantify the influence of such features on the visibility and impact of technology-related tweets. The quantitative analysis from statistical modelling reveals that certain content-based features, like the number of words and pronouns used, positively correlate with the impressions of tweets, with increases of up to 2.8%. Conversely, features such as the excessive use of hashtags, verbs, and complex sentences were found to decrease impressions significantly, with a notable reduction of 8.6% associated with tweets containing numerous trailing characters. Moreover, the study shows that tweets expressing negative sentiments tend to be more impressionable, likely due to a negativity bias that elicits stronger emotional responses and drives higher engagement and virality. Additionally, the sentiment associated with specific technologies also played a crucial role; positive sentiments linked to beneficial technologies like data science or machine learning significantly boosted impressions, while similar sentiments towards negatively viewed technologies like cyber threats reduced them. The inclusion of URLs in tweets also had a mixed impact on impressions—enhancing engagement for general technology topics, but reducing it for sensitive subjects due to potential concerns over link safety. These findings underscore the importance of a strategic approach to social media content creation, emphasising the need for businesses to align their communication strategies, such as responding to shifts in user behaviours, new demands, and emerging uncertainties, with dynamic user engagement patterns.

The rise of the producer: generative AI will transform content creation into content production

The rise of the producer: generative AI will transform content creation into content production

Privacy-Preserving Techniques in Generative AI and Large Language Models: A Narrative Review

Generative AI, including large language models (LLMs), has transformed the paradigm of data generation and creative content, but this progress raises critical privacy concerns, especially when models are trained on sensitive data. This review provides a comprehensive overview of privacy-preserving techniques aimed at safeguarding data privacy in generative AI, such as differential privacy (DP), federated learning (FL), homomorphic encryption (HE), and secure multi-party computation (SMPC). These techniques mitigate risks like model inversion, data leakage, and membership inference attacks, which are particularly relevant to LLMs. Additionally, the review explores emerging solutions, including privacy-enhancing technologies and post-quantum cryptography, as future directions for enhancing privacy in generative AI systems. Recognizing that achieving absolute privacy is mathematically impossible, the review emphasizes the necessity of aligning technical safeguards with legal and regulatory frameworks to ensure compliance with data protection laws. By discussing the ethical and legal implications of privacy risks in generative AI, the review underscores the need for a balanced approach that considers performance, scalability, and privacy preservation. The findings highlight the need for ongoing research and innovation to develop privacy-preserving techniques that keep pace with the scaling of generative AI, especially in large language models, while adhering to regulatory and ethical standards.

The thorn in feminism’s side: black feminist reconceptualization and defence of #tradwives and the #tradwife movement

ABSTRACT Tradwives have been the thorn in feminism’s side ever since they exploded onto the social media landscape in 2013, attracting considerable media attention post-COVID. With their growing popularity in the online influencer space, the movement has been a critical focus of feminist academic discourse, given their promotion of ‘traditional’ values. Adopting a black feminist lens, this article traces the construction of the tradwife as anti-feminist populism and given the complexity of defining tradwives, offers a typology to better understand sub-types of content creators. Three clear sub-types of tradwives are identified: 1) the nostalgic tradwife, 2) the former feminist and finally 3) the Southern Belle. It also examines the unassuming hyperfeminine aesthetic within the tradwife persona that allows tradculture to perpetuate alt-right ideology to an everyday audience. This article argues that some tradwives bury their heads in the sand by failing to consider how nostalgic constructions of ‘traditional’ femininity reproduce colonialist discourses, as well as modes of oppression through gendered, ethnic and class lines.

Bridging the AI Divide: Human and Responsible AI in News and Media Industries

Artificial intelligence (AI) is revolutionizing media and journalism, reshaping processes, content, and audience relationship. This editorial report discusses the opportunities and challenges AI brings to these industries raised by this collection of studies, emphasizing the importance of integrating ethical principles and human-centric approaches to its development. These articles examine how AI reshapes content creation, distribution, and audience interaction while addressing the ethical, political, and economic implications of its integration. Key contributions include discussions on the ethical challenges posed by AI—such as bias, transparency, and accountability—and the need for robust governance structures to foster trust and fairness in AI-driven media systems. A recurring theme in this issue is the AI divide, highlighting the disparity in access to AI technologies between the Global North and South. The special issue offers insights into how this divide exacerbates existing inequalities in media production and consumption. It also advocates for interdisciplinary approaches and collaborative efforts to ensure AI's benefits are equitably distributed across geographical and socio-economic contexts. By exploring both the opportunities and perils of AI adoption in media and news industries, this special issue serves as a comprehensive examination of the evolving relationship between AI, media, and society, offering pathways for responsible innovation and inclusive AI adoption worldwide.

The rise of Chinese animation: policy evolution and industry development since the 1990s

ABSTRACT This paper examines the evolution of China’s animation industry policies from 1990 to the present and their substantial impact on industry development. The study identifies four main stages: the exploratory phase in the 1990s, the boom period from 2000 to 2011, the transition period from 2012 to 2016, and the rational phase from 2017 onwards. Each stage had distinct policy focuses, collectively driving a shift in Chinese animation from simple quantity growth to a more sustainable, quality-oriented development. Various supportive measures, including market access management, fiscal and tax incentives, and industry fund support, provided critical market space and financial resources, fostering technological innovation, talent cultivation, and broadening international collaborations. Despite notable achievements, the industry still grapples with challenges like an incomplete industrial chain, dependence on government support, and gaps in original content creation. This paper provides essential references for optimizing future policies, offering valuable insights for the animation industry’s development in other countries as well.

Enhancing Knowledge Sharing on Social Media: The Role of Functionalities in User Engagement and Information Quality

This study investigates functionalities on social media platforms that promote effective knowledge sharing, focusing on information quality and user engagement. A systematic literature review (SLR) was conducted to analyze relevant research. The findings reveal that functionalities like content creation and curation tools, user interaction and feedback mechanisms, community building and gamification elements, and knowledge filtering and recommendation systems all contribute to a positive knowledge-sharing environment. These functionalities empower users to create high-quality content, engage in discussions that refine information, and discover trustworthy sources. The study highlights the potential of social media platforms for knowledge sharing but acknowledges that the effectiveness of functionalities can vary depending on the platform and audience. Future research is recommended to explore the most impactful functionalities in specific contexts and the interplay between functionalities, user behavior, and information quality.

Grab the Mic: Connecting theory and practice within an undergraduate sport communication course

Experiential learning within sport management classrooms provides valuable industry experience to complement theoretical knowledge. Content creation is a valuable skill for sport management students, particularly those who are looking to work within media and marketing spaces after graduation. Therefore, sport communication undergraduate students at a large research-intensive institution in the Midwest of the United States participated in a podcast creation project for their sport communication class. The experiential learning opportunity provided students with the opportunity to collaborate with a classmate to write, record, and edit a podcast episode under the umbrella of the department's podcast show. This gave the students valuable experience in creating content for professional consumption. The project received positive feedback from students on skill development and the benefits of collaboration, while also discussing the challenges associated with the time demands of the project.

A Real-Time and Interactive Fluid Modeling System for Mixed Reality.

Within the realm of mixed reality, the capability to dynamically render environmental effects with high realism plays a crucial role in amplifying user engagement and interaction. Fluid dynamics, in particular, stand out as essential elements for crafting immersive virtual settings. This includes the simulation of phenomena like smoke, fire, and clouds, which are instrumental in enriching the virtual experience. This work showcases a cutting-edge system developed to produce dynamic and interactive fluid effects that mirror real captured data in real-time for mixed reality applications. This innovative system seamlessly incorporates fluid reconstruction alongside velocity estimation processes within the Unity engine environment. Our approach leverages a novel physics-based differentiable rendering technique, grounded in the principles of light transport in participating media, to simulate the intricate behaviors of fluid while ensuring high fidelity in visual appearance. To further enhance realism, we have expanded our framework to include the estimation of velocity fields, addressing the critical need for fluid motion simulation. The practical application of these techniques demonstrates the system's capacity to offer a robust platform for fluid modeling in mixed reality environments. Through extensive evaluations, we illustrate the effectiveness of our approach in various scenes, underscoring its potential to transform mixed reality content creation by providing developers with the tools to incorporate highly realistic and interactive fluid seamlessly.

Beyond Text: Multimodal Credibility Assessment Approaches for Online User-Generated Content

User-generated content (UGC) is increasingly becoming prevalent on various digital platforms. The content generated on social media, review forums, and question–answer platforms impacts a larger audience and influences their political, social, and other cognitive abilities. Traditional credibility assessment mechanisms involve assessing the credibility of the source and the text. However, with the increase in how user content can be generated and shared (audio, video, and images), multimodal representation of UGC has become increasingly popular. This article reviews the credibility assessment of UGC in various domains, particularly identifying fake news, suspicious profiles, and fake reviews and testimonials, focusing on both textual content and the source of the content creator. Next, the concept of multimodal credibility assessment is presented, which also includes audio, video, and images in addition to text. After that, the article presents a systematic review and comprehensive analysis of work done in the credibility assessment of UGC considering multimodal features. Additionally, the article provides extensive details on the publicly available multimodal datasets for the credibility assessment of UGC. In the end, the research gaps, challenges, and future directions in assessing the credibility of multimodal UGC are presented.

Students' Readiness and Perceptions Towards Unity for Developing a Multimedia Interactive Package

This study investigates students' readiness and perceptions towards using Unity, a development platform, for creating a Multimedia Interactive Package (MIP). With the growing demand for interactive digital content in education, it is crucial to understand students’ readiness and perceptions in engaging with a platform like Unity in developing a language learning application in the form of MIP. The study examines language students' technology readiness as well as their perceptions towards integrating technology into educational content creation. A quantitative approach was employed using a survey to gather data using a set of questionnaires. The sample involved university language students who enrolled in multimedia development courses. Results indicate that while students generally show enthusiasm for using Unity, students faced challenges that may affect their learning experiences. However, the perceived benefits, including enhanced creativity, interactivity, and practical skill development, contribute to a positive overall attitude. The findings suggest that with adequate support and training, Unity can be a valuable tool for developing educational MIPs, promoting both student engagement and technical proficiency.

A SIMBA CoMICs Initiative to Cocreating and Disseminating Evidence-Based, Peer-Reviewed Short Videos on Social Media: Mixed Methods Prospective Study.

Social media is a powerful platform for disseminating health information, yet it is often riddled with misinformation. Further, few guidelines exist for producing reliable, peer-reviewed content. This study describes a framework for creating and disseminating evidence-based videos on polycystic ovary syndrome (PCOS) and thyroid conditions to improve health literacy and tackle misinformation. The study aims to evaluate the creation, dissemination, and impact of evidence-based, peer-reviewed short videos on PCOS and thyroid disorders across social media. It also explores the experiences of content creators and assesses audience engagement. This mixed methods prospective study was conducted between December 2022 and May 2023 and comprised five phases: (1) script generation, (2) video creation, (3) cross-platform publication, (4) process evaluation, and (5) impact evaluation. The SIMBA-CoMICs (Simulation via Instant Messaging for Bedside Application-Combined Medical Information Cines) initiative provides a structured process where medical concepts are simplified and converted to visually engaging videos. The initiative recruited medical students interested in making visually appealing and scientifically accurate videos for social media. The students were then guided to create video scripts based on frequently searched PCOS- and thyroid-related topics. Once experts confirmed the accuracy of the scripts, the medical students produced the videos. The videos were checked by clinical experts and experts with lived experience to ensure clarity and engagement. The SIMBA-CoMICs team then guided the students in editing these videos to fit platform requirements before posting them on TikTok, Instagram, YouTube, and Twitter. Engagement metrics were tracked over 2 months. Content creators were interviewed, and thematic analysis was performed to explore their experiences. The 20 videos received 718 likes, 120 shares, and 54,686 views across all platforms, with TikTok (19,458 views) and Twitter (19,678 views) being the most popular. Engagement increased significantly, with follower growth ranging from 5% on Twitter to 89% on TikTok. Thematic analysis of interviews with 8 out of 38 participants revealed 4 key themes: views on social media, advice for using social media, reasons for participating, and reflections on the project. Content creators highlighted the advantages of social media, such as large outreach (12 references), convenience (10 references), and accessibility to opportunities (7 references). Participants appreciated the nonrestrictive participation criteria, convenience (8 references), and the ability to record from home using prewritten scripts (6 references). Further recommendations to improve the content creation experience included awareness of audience demographics (9 references), sharing content on multiple platforms (5 references), and collaborating with organizations (3 references). This study demonstrates the effectiveness of the SIMBA CoMICs initiative in training medical students to create accurate medical information on PCOS and thyroid disorders for social media dissemination. The model offers a scalable solution to combat misinformation and improve health literacy.

DIGITAL TRANSFORMATION THROUGH COOPERATIVE LEARNING

In today’s complex world, a continuous upgrade of knowledge is crucial. Digital literacy, as one of the key competencies of the 21st century, is becoming more critical since it enables an efficient use of digital devices and tools. The European Union has set five key competencies for digital literacy, including informational and data literacy, digital content creation and communication and collaboration. In education, communication is widely accepted as a crucial skill for achieving common goals. Collaborative learning has proven to be a practical approach to teaching since it encourages the active participation of learners, provides many valuable and innovative solutions, and enables the development of key competencies. The collaborative workability can be further enhanced through cross-curricular integration, where learners are taught independent learning, information-seeking skills and critical thinking. In the school context, combining digital competencies, collaborative learning, and cross-curricular integration is key to preparing students for life in the modern world. This research presents an example of developing digital competencies in technology engineering lessons. The example above is offered in three stages and covers a period of ten school lessons. In addition to digital competencies, students are developing other competencies that will benefit their daily lives. Research is aimed at teachers who want to build digital competencies in their students through experiential learning, collaborative work, and cross-curricular integration, as well as prepare them for future challenges. Keywords: digital competences, digital literacy, cross-curricular approaches, cooperative learning, technology and engineering learning, technology and engineering literacy

Developing Marketing Strategy for User-Generated Content: Study Case for Company X

This study investigates strategies to enhance user-generated content (UGC) growth for Company X, a part of Company X, to address the declining trend in UGC contributions and increasing operational costs. The study employs a qualitative methodology, including in-depth interviews with Company X users and content creators, to identify user personas, motivations, and preferences. External analyses such as PESTEL, competitive analysis, and internal SWOT analysis are used to frame the problem. The results suggest that enhancing the reward system, aligning incentives with user expectations, and improving platform engagement can increase UGC contributions. The proposed strategies aim to leverage UGC to reduce costs and boost user engagement and retention, supporting Company X’s future growth.