Abstract: A new round of information technology revolution has brought new data resources and data analysis and processing tools to social research. And social research has thus become the core content of computational social science based on network big data. However, the quality and value of relevant research results are not satisfactory, and the development is facing great difficulties in recent years. In this article, the causes of this phenomenon were analyzed. As founded, the hype of emerging technologies creates a complex information environment, which led to the cognitive biases on the data acquisition capability, data representation, data quality, data processing capability of social science scholars in the era of big data. In order to correct these deviations and break through the current development bottleneck, the feasible path that targeting research on various network big data and understanding its characteristics accurately and thoroughly were necessary. In this research, the integration of network big data and traditional data resources was focused to make them complement each other. New information processing technology was applied to explore and innovate suitable analysis methods for big data, which is committed to developing a complete set of specifications in terms of research methods and specific technologies.

Key words: Big data, Hype cycle, Social research, Computational social science, Data quality, Data representativeness