Big Data-driven Based Socioeconomic Status Analysis:A Survey

Socioeconomic Status (SES), an overall measure of a person's economic and social status relative to others combining factors such as economics and sociology, has received a lot of attention from researchers, as its assessment can help relevant orga-nizations to make various policies and decisions (governmental formulation of social policies, advertising personalized services, etc).In addition, with the development of big data technology and machine learning in recent years, assessing people's socioeconomic attributes (SEAs) and further obtaining the corresponding socioeconomic status with a data-driven approach can address the issue of extremely high cost of traditional methods.Therefore, this paper summarizes the research progresses of applying big data techniques to socioeconomic status analysis in recent years.It first introduces the basic concept of socioeconomic status and discusses the challenges posed by big data methods compared to traditional methods.After that, it systematically summarizes and classifies the state-of-the-art related methods based on the information in the learning process, and present them in detail, discusses the pros and cons of each type of method.Finally, it discusses the challenges and problems of inferring people's socioeconomic status and provides an outlook on future research directions.

Abstract licence: CC BY-NC-ND

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