Social media analytics in the construction industry comparison study between China and the United States

The purpose of this paper is to discover similarities and differences in the construction industry in China and the United States by using data analytic tools on data crawled from social media platforms.

The method comprised comprehensive data analytics using network link analysis and natural language processing tools to discover similarities and differences of social networks, topics of interests and sentiments and emotions on different social media platforms.

From the research, it showed that all clusters (construction company, construction worker, construction media and construction union) shared similar trends on follower-following ratios and sentiment analysis in both social media platforms. The biggest difference between the two countries is that public accounts (e.g. company, media and union) on Twitter posted more on public interests, including safety and energy.

The research contributes to knowledge about an alternative method of data collection for both academia and industry practitioners. Statistical bias can be introduced by only using social media platform data. The analyzed four clusters can be further divided to reflect more fine-grained groups of construction industries. The results can be integrated into other analyses based on traditional methodologies of data collection such as questionnaire surveys or interviews.

The research provides a comparative study of the construction industries in China and the USA among four clusters using social media platform data.