ABSTRACT
The rise of digitalization has led to a significant increase in the attention given to online sports news. In a similar vein, the Metaverse has gone through various stages of evaluation. At present, it is in a developmental phase where real-world socio-economic and cultural activities are seamlessly integrated into a 3D virtual environment. Understanding the impact and implications of the Metaverse 3.0 era is highly sought after. This study seeks to investigate social issues related to the Metaverse in South Korea. It will analyse a large dataset of online sports news articles from June 2021 to May 2022 using LDA-based topic modelling. As a result, four main topics were identified: a new platform, a new business model, pervasive online cultural and educational media, and a new frontier for business and investment. New Platform (Topic 1) showcased keywords indicating the potential of Metaverse as a cutting-edge platform, while New Business (Topic 2) highlighted keywords indicating digital media companies' pursuit of a new profit model within the virtual realm of Metaverse. The increasing prevalence of online culture and educational media (Topic 3) highlights the growing demand for a wide range of content that caters to the virtual world's cultural and educational experiences. "New Frontier for Business and Investment (Topic 4) highlights the significant involvement of digital media companies in acquiring investments, technologies, and intellectual property (IP) to gain a competitive edge in the global Metaverse market. This study solely examined online sports data, but future research could encompass a wider range of raw data sources, such as interviews with practitioners, user reviews, and research reports. By doing so, a more comprehensive understanding of the potential challenges that the Metaverse may encounter can be obtained.(AU)
Subject(s)
Humans , Male , Female , Psychology, Sports , Sports/trends , Big Data , Data MiningABSTRACT
In an era marked by the rapid proliferation of Internet-based social platforms, efficient data dissemination across networks has reached unprecedented levels. However, this widespread accessibility to information has also ushered in a concerning trendthe propagation of false and deceptive narratives. The consequences of fake news, especially in the context of the sports sector, are far-reaching. Beyond eroding trust in media sources, fake sports news can instigate social unrest and disruption with implications extending into politics and the economy.Recognizing the urgent need to address this challenge, this study embarks on the vital task of automatically detecting fake sports news within the complex landscape of online content. Fake sports news typically comprises statements or reports containing elements of falsehood, often diverging significantly from the actual events they purport to describe. Such misinformation is frequently disseminated for political or economic reasons, making its accurate identification formidable.To tackle this pressing issue, we propose a comprehensive fake sports news detection framework termed MFNDF (Multimodal Fake News Detection in Sports). This innovative framework leverages a multifaceted approach, extracting features from three distinct modalities.Firstly, we employ the BERT model for text feature extraction, fine-tuning the extracted text features through a fully connected (FC) layer to enhance the representation of news semantics.Secondly, in image feature extraction, we harness the power of the DenseNet pre-training model to extract convolution features from image content. Additionally, we utilize the Discrete Cosine Transform (DCT) algorithm to extract image frequency domain features, which aid in detecting image tampering and repeated compressiona common tactic employed in creating fake sports news images.Thirdly, we delve into the realm of user context, mining valuable insights from users' behavioral features and news statistical features through advanced feature engineering techniques.Furthermore, we introduce an attention mechanism, a critical component of our approach, to assign weights to word vectors within the text feature space. This attention mechanism takes into account both image features and word vectors, thereby facilitating the fusion of image and text information. The resulting feature vector, enriched with multimodal data, enhances the overall performance of our detection model.Systematic experiments conducted on MFNDF confirm its superior effectiveness in the realm of fake sports news detection. By addressing the critical challenge of identifying deceptive narratives within the sports sector, our research strives to mitigate the adverse impact of fake sports news and safeguard the integrity of information in the dynamic world of sports reporting."(AU)
Subject(s)
Humans , Sports/trends , Psychology, SportsABSTRACT
In the rapidly evolving landscape of sports news and sports psychology, driven by the proliferation of mobile Internet and Internet media in China, it is essential to recognize two pivotal factors shaping the discourse. Firstly, there is the imperative 'construction of new liberal arts' within professional knowledge education. Secondly, the practice of news communication is undergoing transformative changes due to media integration, particularly in the context of sports news concerning Chinese athletes. These two dynamics together create a favorable environment, underpinned by robust policy support, for interdisciplinary research at the intersection of sports psychology and sports news communication. Within the academic realm, our efforts must be attuned to the evolving curriculum and the unique challenges posed by this dynamic landscape. Such an approach is instrumental in advancing in-depth interdisciplinary research at the confluence of sports psychology and the communication of sports news. Recent years have witnessed an upsurge in research interest in media communication, with a pronounced emphasis on sports. In light of this, we have a unique opportunity to conduct a comprehensive analysis of interdisciplinary interactions within the domain of sports news and sports psychology. To facilitate this, we propose employing advanced knowledge graph techniques and correlation analysis. In this specialized context, the interdisciplinary study of sports psychology and sports news communication can be envisaged as a dynamic process that involves the assimilation and dissemination of specialized knowledge. We advocate for the application of a network environment correlation analysis method rooted in knowledge mapping principles. This approach entails the development of a tailored knowledge map specific to the realm of sports news concerning Chinese athletes, within the framework of sports psychology. Furthermore, we will explore the creation of efficient storage and retrieval mechanisms to optimize the effectiveness of our research pursuits in this exciting and evolving field.(AU)
