Abstract
Social networks contain a large amount of unstructured data. To ensure the stability of unstructured big data, this study proposes a method for visual dynamic simulation model of unstructured data in social networks. This study uses the Hadoop platform and data visualization technology to establish a univariate linear regression model according to the time correlation between data, estimates and approximates perceptual data, and collects unstructured data of social networks. Then, the unstructured data collected from the original social network are processed, and an adaptive threshold is designed to filter out the influence of noise. The unstructured data of social network after feature analysis are processed to extract its visual features. Finally, this study carries out the Hadoop cluster design, implements data persistence by HDFS, uses MapReduce to extract data clusters for distributed computing, builds a visual dynamic simulation model of unstructured data in social network, and realizes the display of unstructured data in social network. The experimental results show that this method has a good visualization effect on unstructured data in social networks and can effectively improve the stability and efficiency of unstructured data visualization in social networks.
Highlights
With the development of computer and mobile terminal technology, Internet-based social network platform is increasingly going deep into people’s daily lives, work, and study, and has become the main place and important source of social information diffusion [1,2,3]
Data visualization technology can quickly express a wide range of data and visualize information, to reduce the cognitive difficulty of data and help people understand data [5,6,7]
Mrsic et al [9] proposed the application of social network analysis and data visualization technology in information dissemination analysis
Summary
With the development of computer and mobile terminal technology, Internet-based social network platform is increasingly going deep into people’s daily lives, work, and study, and has become the main place and important source of social information diffusion [1,2,3]. How to use visualization technology to quickly and effectively find useful data from huge and complex social network data and transform it into easy-to-understand image information, to serve users and platform managers, has attracted great attention in the industry. Kline andVolegov [8] proposed a method to realize 3D data visualization using virtual reality tools. Is method can effectively use virtual reality tools to realize 3D data visualization. Mrsic et al [9] proposed the application of social network analysis and data visualization technology in information dissemination analysis. Security and Communication Networks the development of basic models, data retrieval, data processing, and result analysis and visualization, social network information dissemination is realized. E social network unstructured data visualization effect of this method is good, stable, and efficient A univariate linear regression model is established using the Hadoop cluster design and data visualization technology, and HDFS is used for data persistence, MapReduce is used for distributed computing of visual data feature classes, and a visual dynamic model of unstructured data in social networks is constructed to realize the display of unstructured data information in social networks. e social network unstructured data visualization effect of this method is good, stable, and efficient
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