Research On Innovation Of Social Science Evaluation Under Big Data Environment

With the rapid development and an in-depth fusion with real life of information technology, social life increasingly presents a characteristic of informatization and datamation. Against this background, a big data era was born at the right moment, which profoundly changes the social life and scientific researches in every regard, effectively promotes the development of social science evaluation and has a great influence on the environment as well as theory, method and procedure of social science evaluation. Being more institutionalized, specified and legalized, social science evaluation which is in the big data era, plays a more and more important role in the management decision. National governments give special supports to social science evaluation institutions and theirs related activities, indicating that they fully recognize the influence of the big data environment and thus devote themselves to the optimization of the social science evaluation environment in reverse.As to the theory, the epistemology base, subject, and object of social science evaluation all in the big data environment have been changed; As to evaluation method, many methods that were applied to natural science evaluation only in early period have been expanded to the evaluation of humanistic and social science, which makes the latter becomes more quantified, systematized and integrated, produces a assimilation tendency between the methods of natural science evaluation and social science evaluation and causes a suddenly rise of data science methods; as to evaluation procedure, it presents a circular structure in the big data era, with more reasonable design, scientific allocation of each evaluation step, and dynamically updated evaluation results.This paper aims to explore the innovation of social science evaluation in the big data environment. Social changes and influences of big data on social science and its evaluation in big data environment are discussed at first, which reveals the necessity social science evaluation in big data. Subsequently, taking result, theory, method, practice, and system of social science evaluation as breakthrough points, explores a benign interaction development path between the big data and social science evaluation in order to promote the synthesis, scientificity, objectivity, impartiality, and efficiency of social science evaluation. The concrete content of each chapter in this paper is as the following:Chapter one, theoretical explanation on big data environment and social science evaluation. This chapter explains core concepts of science, social science and social science evaluation at first, and then discusses the contents as well as the characteristics of social science research and the important roles of social science evaluation in promoting social science development. At last but not least, reasons and characteristics of big data are introduced in this chapter. In short, this chapter specifically describes core concepts and clears logic chains among them, which makes a sound theoretical foundation for this study.Chapter two is mainly about the effects of big data environment on the innovation of social science evaluation. Firstly, this chapter analyzes the changes of society and social science in big data environment and concludes the fact that changes appear in the objects, thoughts, methods and research paradigm of social science research in big data environment; secondly, this chapter explores the impact of big data environment on social science evaluation and predicts that subjects, methods, indicator system as well as feedback on evaluation results will be changed in accordance with the characteristics of social science research in big data environment; thirdly, this chapter highlights the necessity and connotation of social science evaluation in big data environment and analyzes the frame of social science evaluation innovation in big data environment.Chapter three, study on theory innovation of social science evaluation in the big data environment. The chapter constructs a basic theory of social science evaluation from various theoretical dimensions such as philosophy, information management science, metrology, economics, management science, system science, comparison and classification theory. Based on it, a significant theoretical innovation of social science evaluation's epistemology and methodology brought by the big data environment is discussed; Furthermore, this chapter elaborates the classification and main types of social science evaluation and reveals changes from evaluation type, social science research subjects as well as objects in the big data environment by using a comparative analysis. The result highlights the data's weight increment phenomenon in the speaking right of scientific evaluation and an irresistible trend of evaluation subjects'role differentiation. The increasingly important function of an independent and professional "third-party evaluation" is further demonstrated; At last, this chapter analyzes the influences of big data technologies on basic standards of social science evaluation and classification standards based on evaluated objects in the environment due to the fact that classification evaluation will be the only effective evaluation type in the big data environment.Chapter four, the research on method innovation of social science evaluation in the big data environment. At first, this chapter discusses the traditional methods of social science evaluation. Then, it puts forward that those methods such as data collection and cleaning, analyzing and digging will extend the source of evaluation data, diversify the type of evaluation data, and increase quantifiable evaluation indicator. It can also make evaluation indicators more reasonable, the design of weights and evaluation data more precise, judgment of experts more scientific, and evaluation results more dependable.Chapter five, the research on the practice innovation of social science evaluation in the big data environment. Firstly, this chapter highlights the flexibility, scientificity and reasonability of social science evaluation practice by using a comparative analysis on innovation advantage from the structure of social science evaluation procedure, step design and its scientific selection in the big data environment after elaborating the procedure of traditional social science evaluation; secondly, this chapter defines the related concepts of social science evaluation indicator system and states the defining principles and requirements in such environment. In order to reflect scientificity, systematicness and operability of the indicator system, the big data environment, differentiating from the establishment of traditional social science evaluation indicator system, requires a continuous innovation of the indicator selection to fit to the development of social science evaluation in it; In addition, the development of big data environment will promote acquaintance of experts on evaluated objects with the development of big data in terms of the social science expert selection process. It provides possibilities to realize evaluation on interdisciplinary and break through the discipline restriction as well as the academic monopoly. The combination of qualitative evaluation with quantitative evaluation is also promoted, leading to fairer procedures and more accurate results of evaluation.The application of big data is also beneficial to the update of evaluation expert database, realizes the effective experts matching, solves disadvantages evasions such as high cost but low efficiency of the traditional peer evaluation, and expands new ways for peer evaluation and expert selection. At last, an empirical study, i.e. innovation competitiveness evaluation on social sciences in Chinese universities, is performed.Chapter six, the research on institution innovation of social science evaluation in the big data environment. Firstly, this chapter explains the problems such as imperfect system, unscientific executive subject as well as unreasonable evaluation standard of traditional social science evaluation and anticipates a development trend that the social science evaluation system in China is perfect gradually and the academic rigor of evaluation subject is constantly reinforced. Then, a realistic contradiction between the increasingly improved demand of open and legal utilization social evaluation data and lack of the effective protection of the data is pointed out, which requires establishment of a more advanced social science evaluation safeguard mechanism to fit the reform of social science evaluation environment caused by the big data environment and drive an institutionalized, normalized and legalized development of the social science; at last, this chapter presents an implement approach of establishing a new environment of social science evaluation in a the data background, mainly including the establishment of perfect social science evaluation institution system, promotion of establishing a thorough social science classification evaluation system, some authoritative third-party social science evaluation organization in each field and a unified big data platform of social science evaluation.