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AbstractIn this article, we examine whether and how small investors' social media activity is associated with subsequent bond credit spreads. We use extensive data from posts/comments on social media 30 days before the bond issuance announcement date to identify their implied power and find that the more posts/comments, the smaller the bond issuance spreads. We further find that information quality improvement of posts increases this negative relation between social media activity and bond cost, and that posts directly related to issuers' fundamentals and/or debt financing drive our main results. Additional tests show that the effect is more salient when there is a greater demand for information quality or when macroeconomic conditions worsen.

ABSTRACT
Prior research has argued that companies in transition economies engage in corporate social responsibility (CSR) activities to achieve political goals, such as building connections with the government. However, it is unclear why chief executive officers (CEOs) agree to make these politically driven CSR decisions that mainly benefit the controlling shareholders. We show that controlling shareholders may "bribe" the CEOs with greater compensation or perks—a form of economic rents extracted by the CEOs—to make CSR decisions, and such a pattern is more salient in local government-owned companies. We reason that these CSR activities reflect implicit contracting between the controlling shareholders and the CEOs. Through cross-section analyses, we find that the CEO's economic rents vary with local government fiscal needs, the firm's governance structure, and CEO power. Furthermore, we demonstrate that increases in CSR-linked compensation lead to a decline in shareholder value.
Data Availability: All data are available from public databases identified in the paper.
JEL Classifications: D72; M12; P26.

Today, more and more geospatial services are provided by the governments and enterprises to share various geographic information data and functions, and services-based application integration has become a trend. However, many problems existed in the geo-platform for Geographic information sharing while providing services in the form of API, such as the coexistence of different versions of the same service, similar service routes of different APIs, cluttered service protocols, and complex authority management, that makes the integration among different geographic information services difficult and reduces the development efficiency. There are already some API gateway technologies to solve the problem, but the characteristics of geospatial services are not considered in the existing product. To address these problems, this paper proposed a high-currency geospatial service gateway system for National Geo-Information Service Platform based on the opensource framework of Kong for realizing the unified management and authorized open. The system provides the whole lifecycle management and fine-grained control for the service, and the functions such as unified geospatial service access, protocol conversion, service management, authorization verification, rate limiting, and security protection are also equipped. The system has been released and integrated in the National Geo-Information Service Platform, supporting hundreds of millions of service invocation every day. The result proves it simplifies geospatial services management, deployment, and application, and benefits the exchanging and sharing of geographic information.

Today, more and more geospatial services are provided by the governments and enterprises to share various geographic information data and functions, and services-based application integration has become a trend. However, many problems existed in the geo-platform for Geographic information sharing while providing services in the form of API, such as the coexistence of different versions of the same service, similar service routes of different APIs, cluttered service protocols, and complex authority management, that makes the integration among different geographic information services difficult and reduces the development efficiency. There are already some API gateway technologies to solve the problem, but the characteristics of geospatial services are not considered in the existing product. To address these problems, this paper proposed a high-currency geospatial service gateway system for National Geo-Information Service Platform based on the opensource framework of Kong for realizing the unified management and authorized open. The system provides the whole lifecycle management and fine-grained control for the service, and the functions such as unified geospatial service access, protocol conversion, service management, authorization verification, rate limiting, and security protection are also equipped. The system has been released and integrated in the National Geo-Information Service Platform, supporting hundreds of millions of service invocation every day. The result proves it simplifies geospatial services management, deployment, and application, and benefits the exchanging and sharing of geographic information.

With the rapid development of remote sensing technology, it is possible to obtain continuous video data from outer space successfully. It is of great significance in military and civilian fields to detect moving objects from the remote sensing image sequence and predict their movements. In recent years, this issue has attracted more and more attention. However, researches on moving object detection and movement prediction in high-resolution remote sensing videos are still in its infancy, which is worthy of further study. In this paper, we propose a ship detection and movement prediction method based on You-Only-Look-Once (YOLO) v3 and Simple Online and Realtime Tracking (SORT). Original YOLO v3 is improved by multi-frame training to fully utilize the information of continuous frames in a fusion way. The simple and practical multiple object tracking algorithm SORT is used to recognize multiple targets detected by multi-frame YOLO v3 model and obtain their coordinates. These coordinates are fitted by the least square method to get the trajectories of multiple targets. We take the derivative of each trajectory to obtain the real-time movement direction and velocity of the detected ships. Experiments are performed on multi-spectral remote sensing images selected on Google Earth, as well as real multi-spectral remote sensing videos captured by Jilin-1 satellite. Experimental results validate the effectiveness of our method for moving ship detection and movement prediction. It shows a feasible way for efficient interpretation and information extraction of new remote sensing video data.