Public attitudes on open source communities in China: A text mining analysis

Abstract

The Development of open source community has been a major concern in many countries. Sustainable public engagement is one of the essential conditions for establishing an open source community. Social media offers a new channel for understanding public opinions on OSCs. This paper conducts a content analysis focusing on social media data regarding the OSCs in China. Topic clustering, sentiment classification, and social network analysis are used to analyze the text data. Results show that most people on social media support the development of OSCs in China, but there are still some objections that believe open source will reduce the innovation ability of China. Based on the findings, we suggest that the government should fully understand public attitudes on OSCs and respond in time to the public by using social media. More high-quality China's independent OSCs should be built to enable Chinese local open source contributors to survive and communicate with each other. In addition, we suggest that a comprehensive and reasonable evaluation and incentive system and more effective copyright protection measures should be created. Overall, this paper contributes to the field of development of OSCs from the perspective of users.