Decision-Making Model of Social Work Specialization Process Using Big Data Analysis and Chaos Cloud

Abstract

Big data and mobile edge computing information technology have revolutionized traditional industries' development. The organic integration of community social work and big data technology will undoubtedly promote the growth of community social work services, thanks to the new information technology platform for big data. In terms of the future of big data-driven social work, it is primarily reflected in the following: in the application of social work, big data can acquire and update real human behavior data in real time, and eliminating the need for subjects' subjective reports in the data collection process; It can also provide a basis for public decision-making, which is worthy of our active exploration and innovation, provide efficient and accurate technical means for risk population assessment and crisis intervention and have a more accurate and intuitive grasp of the temporal and spatial distribution of service personnel and basic social service facilities. The core of professionalization of social work is improving the post-setting system for social workers in our country, improving their treatment, and strengthening the construction of professional ethics for social workers in our country. A big data social workflow adaptive scheduling optimization algorithm based on the chaotic cloud diversion mechanism is proposed to address the problems of high costs, poor time convergence performance, and poor cost accounting quality in the current social workflow adaptive scheduling optimization algorithm. As an important part of social governance, social work accelerates the process of social work specialization to improve decision-making efficiency.