The Communication Data and Network Analytics lab (CDNA) was established in August 2020. It is a cross-disciplinary team composed of social scientists and information engineering researchers. The main goal of CDNA is to provide a comprehensive understanding of communication behaviors related to important social issues, using triangulation of different research methods. The topics being examined include: fake news detection and verification, consumer risk assessment, public health risk information dissemination, political polarization, etc. Combining traditional social scientific methods (e.g., survey, experiment) with computational approaches (e.g., texting mining), the core line of CDNA research is on online public opinion mining, as well as the assessment of the process, dynamics, and effects of human communication behaviors through the integration of user log and self-reported data from survey or experiment.

In addition to research, the CDNA team is also committed to providing academic and public services, including several data platforms for use by domestic scholars and the general public. The “online data platform” is created for scholars to search and retrieve online data relevant to the topic of their interest. Users can search the online data by keywords to understand how a topic is being reported by the news media and how online public opinions on that topic change over time.

In addition to research projects and service platforms, CDNA regularly holds academic lectures, covering diverse topics related to texting mining, data analysis, AI and other latest research development. CDNA has actively recruited domestic scholars who have devoted themselves to machine learning and AI, and has expanded its perspective to the world.