Dynamic feedback mechanism for maximizing interaction in online social network services

Online social network services have embedded social rating systems that users can evaluate and share the quality of content such as the “Like” button for Facebook. This rating system is an important mechanism in social interaction since the system can affect the degree of user connection and the spread of information sharing. Most of such social rating systems, however, are based on the fixed feedback mechanism, where users cannot communicate their emotion and evaluation toward certain content in a real-time manner. In this research, we propose a novel feedback method that dynamically updates rating scores in social network services to give users immediate feedback. To confirm the usefulness of dynamic feedback mechanism compared to the current static feedback mechanism, we conducted an exploratory experiment with 46 participants in a simulated Facebook situation. Since types of content matter for the nature and degree of social interaction, we assumed that the dynamic feedback mechanism might yield different effects to different types of content. Hence, in the experiment, we included three different types of content, namely a) user-generated content, b) news article, and c) commercial advertisement, to examine the interaction effect between feedback mechanism and content types. The dependent variable was the number of “Like” clicks. The results indicate that the dynamic feedback type received significantly higher “Like” clicks than the fixed feedback type. Further, there was a significant interaction effect between feedback types and content types. The dynamic feedback mechanism was the most effective for the user-generated content type.