This paper investigates the moderating role of industry regulation on the effectiveness of audit committees in restricting earnings management. Using comprehensive panel data of S&P 1500 firms between 2003 and 2007, we find that the proportion of CEO directors on an audit committee is positively associated with earnings management in unregulated industries, while this association is significantly weaker in regulated industries. Further, the proportion of financial experts on an audit committee is negatively associated with earnings management. Our results also indicate (...) that the average board tenure of audit committee members is negatively related to earnings management in regulated industries, but positively affects earnings management in unregulated industries. Finally, audit committee members’ average directorship increases earnings management in regulated industries, but reduces earnings management in unregulated industries. Overall, our results suggest that the effectiveness of audit committees in reducing earnings management and improving financial reporting quality is influenced by industry regulation. (shrink)

Computational social science, as an emerging interdisciplinary discipline, is a field ushered in by long-term development of traditional social science. It is committed to supplying data thinking, resources, and analytics to study human social behavior and social operation laws to accurately grasp and judge the developing path of the discipline, which is of great significance to promote the innovation and development of social sciences. This study is to conduct a systematic quantitative analysis from a bibliometric perspective, aiming to provide a (...) reference for scholars to explore the paths and changing rules in the field. We use the relevant literature in Web of Science as the dataset. After eliminating journal calls and irrelevant literature, R language and SciMAT tools are used to visualize and analyze the number of articles, keyword clustering, keyword cooccurrence network, and theme evolution, so as to summarize and sort out the paths of computational social science research. The study found that the annual volume of publications has been gradually increasing and will probably remain active in the next few years with high productivity. Subject themes in different periods are diversified, and the evolutionary relationship is found complex as well. Besides, as a cross discipline, scientific knowledge from different fields cross collides and couples with each other in the big data environment, changing the traditional concept of computational social science and forming a new development path. Recently, the emergence of “big data+” has promoted the rise of new subject areas, making the development of new disciplines a reality. (shrink)