Dialogue from Experience: Exploring the Theoretical Basis and Application Challenges of Computational Social Science
With the advancement of information technology, the use of digital technology as a research tool, analytical method, and exploration approach has become a new wave of social science. This rapidly emerging trend of computational social science should itself be treated as a research subject. It is necessary to explore its methods and premises, and to think about the possibility of application, in order to enhance our understanding of its influence, value and prospects. Therefore, this article attempts to discuss the ontology, epistemology and methodology of computational social sciences.
The ontology of computational social sciences can be said to be a "metadatification" process, which converts various types of information into data, and performs computational processing with its mathematical logic. In the epistemology of computational social sciences, algorithms are used to sort out patterns and structures that were previously undetectable to the naked eye, and to find correlations or rules from the data pile. The methodology emphasizes that mechanical objectivity can be used to filter out artificial biases to produce rigorous knowledge. However, when we apply computational approaches, we must still reflect on its knowledge assumptions in order to find an appropriate method to integrate with social interpretative approaches. First, the form of research data is diverse, and not all are suitable for conversion to byte format. Second, the meaning of patterns and structures is not self-explanatory, but relies on human interpretation to bring context and meaning in order to make it into thick data. Third, it is necessary to be honest in the process of data intermediation, including the determination of the scope of data col-lection, the process of data translation and cleaning, and the final presentation of data, all of which are full of traces of social construction.
Through my research experience of data collection and analysis by using a computational approach, I will discuss how the data analysis of the computational approach can be used in conjunction with the narrative interpretation method to promote the understanding of social facts. I use a mobile app to collect the temporary data of people using social media to understand the temporal structure and mechanism of social media's integration into daily life. This technology-assisted method can help me collect more accurate and detailed information, and I also use in-depth interviews to understand the context and meaning behind the data. The data obtained from the mobile app, like cultural probes, gives an overview of the usage scenarios, finds out the structure of the usage patterns, and then illuminates an entrance for us, allowing us to see the deeper meanings in the context. In other words, data and interviews are complementary, both by using data to stimulate narratives and deepening data by using narratives.
In addition, I also discuss how digital technology-assisted forms of data collection pose complex challenges to method ethics, including changes in the nature of the field, and research ethics and privacy protection issues. With such a positive understanding and dialogue with digital technology methods, we hope that we can continue to develop new, appropriate and mutually inclusive ways to cope with the social world that has gradually been involved in technology.