Sports Big Data Analysis Based on Cloud Platform and Its Impact on Sports Economy

Abstract

The service information system is constantly transforming to a networked information model, and domestic hardware equipment is constantly updated. Independent controllability has also become the basic requirement of the new information age. With the development of the information age and the new era of independent control, more and more services and applications will also be deployed on autonomous and controllable cloud platforms. With the rapid development of Internet technology in the information age and the resulting changes in productivity, people can record, store, and transmit more and more information. When information becomes recordable, storage, and easy to transmit, information becomes modern meaning nowadays, an era of information explosion characterized by massive, volatile, timely transmission, and diverse forms has truly come, forming what is now called the “big data era”. This article mainly introduces the analysis of sports big data based on the cloud platform and the research on the impact on the sports economy and intends to provide ideas and directions for the analysis of sports big data and the research on the impact on the sports economy. This paper proposes a cloud platform-based sports big data analysis and research methods for its impact on the sports economy, including the use of Hadoop cloud platform big data processing systems and support vector regression algorithms for cloud platform-based sports big data analysis and sports economy. The experimental results of this paper show that the average correlation between sports big data analysis and sports economic development is 0.5155, and appropriate cloud platform-based sports big data analysis plays a positive role in promoting sports economic development.

Big Data in Sports: A Bibliometric and Topic Study

“…The most commonly found word was: data (frequency 137), analysis (frequency 54), health and study (both with frequency 51), based (frequency 51) and sports (frequency 40). Five words with the highest TF-IDF were sports (32,2), cycling (30,3), weather (24,6), exercise (22,0) and obesity (21,6). Table 3 presents the following most frequently used phrases, where the frequency of occurrence was higher or equal to 4.…”

“…In sports, Big Data has generated new opportunities and challenges with the aim of spreading sports data (Patel et al, 2020) Big Data is common in professional sports but is not the only one. The connection between Big Data and different sports fields can be found in many areas that are not directly related to sports (Cheng et al, 2021). The mentioned areas of research on the use of sport and Big Data are, for example, engineering (Kim et al, 2020), medicine (Hayano et al, 2019, Al-Mallah et al, 2014 and public health (Park et al, 2020), social and computer science (Hou et al, 2017), business and management (Khazaeli et al, 2016), environmental science (Phan et al, 2020) and some others.…”

Research on urban landscape big data information processing system based on ordinary differential equations

“…According to different data acquisition methods, landscape big data can be divided into traditional data and emerging data. Common survey statistics and remote sensing mapping are traditional data acquisition methods, which are used to obtain data related to urban economy, society, population and space; the Internet and smart facilities are emerging data acquisition methods, which can obtain more Various types of open data and data of urban operation facilities provided by the subject [9]. Dang Anrong et al divided the data from two different perspectives: conventional spatial data and attribute data, new static data and dynamic data, and divided it into two major categories, 12 medium categories and more than 30 small categories [10].…”

Integration and Dissemination of Sports Big Data Based on Blockchain

“…Sports products include both tangible sports goods and intangible sports services. News reports on sports information often occupy the front page headlines of major media [8,9]. In the field of sports news, the combination of data and network sports news has fully affected the dissemination of its own information, making the news industry experience significant changes from news sources to news writing methods.…”