The innovation and challenge of quantitative social research methods in the era of big data

The arrival of the era of big data not only deeply affected people's understanding of the social world, but also provided great possibilities for the innovation of quantitative social research methods. Through the innovation of social science research, the paradigm of traditional sociological quantitative research will be reshape through the innovation of big data, and new research areas and directions will be developed.

Big data brings quantitative social research methods innovation

With the development of modern information technology, we have entered the "digital era". The emergence and extensive use of big data are deeply changing traditional social research, and the development and innovation of quantitative research methods have brought a significant impact.

First, big data has given us a new understanding of social research data. Sociology research has long been affected by empiricalist methodology and attaches great importance to quantitative data. Traditional quantitative data is mainly based on survey data of individual samples. Although this type of structured data is inferred and interpreted under representative large sample conditions, the sample scale is always limited due to factors such as investigation and research conditions. The emergence of big data completely changed the nature of the data, allowing us to have a new understanding of the data of social research.

The so -called "big data" is usually related to the cloud computing. Wide application value and so on. Matthew Salganik pointed out in "Computing Sociology" that big data is conducive to the outstanding characteristics of social research is massiveness, sustainability and incompetence. These characteristics are not available in traditional quantitative data. In the past, even if there were enough large samples, the quantity was very limited. Using big data, you can easily obtain hundreds of thousands or more data information of the analysis objects. As Salgnik said: "The increase in massive big data means that we have entered a world with extremely rich behavior data from a world that lacks behavioral data."

Second, big data has expanded social research data acquisition. Traditional quantitative social research data mainly depends on the special laws such as questionnaire surveys or experimental research. The method is limited and restricted by various research conditions. In the era of big data, the way we obtain data have been greatly expanded. At present, social big data exists in various fields of social activities, and more and more institutions that specialize in big data are developed. Data storage, mining and development technology are constantly improving. This provides us with great convenience for us to obtain and use big data.

The problems encountered in social research in the era of big data have been different from that traditional social research is often trapped by data acquisition. More and more researchers feel that there are too many data or information and face difficulty in choosing.

Third, big data has greatly developed quantitative research methods. Although quantitative social research methods have continued to develop and progress in recent decades, there have always been certain limitations. With the rapid development of modern computer technology and "cloud computing", analysis methods and technologies have been continuously updated, which has greatly enriched and developed quantitative social research methods. For example, data mining and analysis technologies based on the Internet and the Internet of Things have been widely used. Therefore, on the basis of new computing technologies and methods, social science research has undergone major changes in data processing and analysis methods, and new computing sociology is very different from traditional quantitative sociology. It can also be said that the development of big data and related new technologies and the combination of social science research has formed a disciplinary computing social science, which provides directions and possibilities for the innovation of quantitative social research methods.

Reasonable use of big data to promote the integration and innovation of social research methods

The emergence of big data not only brings unprecedented opportunities for quantitative society research, but also brings great changes and challenges. Some scholars even call the rise of social sciences related to big data as a "paradigm revolution" for social research. At the same time, this development has also aroused fierce debate on big data in the academic community, and there have been some relative views. In fact, since the development of empiricalism, the debate between quantitative research and qualitative research has not stopped. At present, the dispute over big data is its new expression. Of course, we have entered a new era of digitalization, so we need to form a new understanding of related issues.

First, social research should treat big data with an open and positive attitude. At present, we have entered the stage of digital information. Digitalization of information in various fields has become a common development trend. This requires social research to treat big data with a more open and positive attitude. In this sense, it is "right to speak" after mastering the data. Quantitative social research cannot be separated from data, and it is inseparable from big data. Of course, big data is not only conducive to social research, but also aspects that are not conducive to research. For example, Salgnik pointed out that its adverseity includes the incompleteness of the data, difficulty in obtaining, not representative, algorithm issues, "dirty data" and sensitivity.

Although there are certain problems with big data and its applications, this is not enough to affect the current social science research on the attention and use of big data. Victor Mel-Schaneberg and Kennes Cookye pointed out in "Big Data Age: Life, Work and Thinking": "The huge value to be released in the era of big data makes us choose the big data of big data. Concepts and methods are no longer a balance, but an inevitable change to the future. "This requires us to pay attention to big data and accept and use big data in an open and specialized manner.

Secondly, social research also needs to use big data in a reasonable way. Using big data, we must not only deepen the understanding of it, but also need to innovate in actual research ideas and design. Pay attention to the following two relationships. The first is to deal with the relationship between the purpose of social research and tools. The basic procedure of traditional sociological quantitative research is to put forward research assumptions in advance, and analyze the quantitative data according to the research framework designed by myself. This deductive research logic is mainly "theoretical orientation". And the new social research logic based on big data seems to be "data -driven", that is, the big data that the research institute relies on is not obtained by researchers in advance, but directly obtained from other channels. Essence As a result, some scholars pointed out that big data may not be able to meet the research purposes of researchers, and even limited to the analysis of the data itself, there will be great limitations; Sexual lack and other issues. Although there may be similar problems, we should also start from research needs and pay attention to the selection and utilization of data. We need to pay attention to the use of big data, but we cannot be completely trapped in big data.

The second is to deal with the relationship between traditional quantitative social research and big data methods. In recent years, there have been some new changes in the research paradigm, and the integration and innovation of research methods has become an important development direction. Based on the development and innovation of Chinese sociology, as Chen Yunsong pointed out in the article "The Macro Steering of Contemporary Sociology Quantitative Research", the "macro quantitative sociology" based on big data " It is of great significance to expand the territory of the discipline and build a socio -speaking language system with Chinese characteristics.

This certain amount of sociological research brought by big data is turning to a powerful trend, which not only impacts the research method of traditional sociology, but is also a paradigm for the integration of research methods. Learn research and development of new research areas and directions. Therefore, we need to attach importance to the development and utilization of big data, and promote the continuous development of Chinese sociology through the integration and innovation of research methods.

(Author unit: Department of Sociology, Shandong University)

Source: China Social Science Network-Journal of Social Sciences of China

Author: Lin Juan

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