About Us


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, CDNA provides a “human annotation and matching platform" for academics who have the need for annotating a large amount of data. They will be able to use the platform to find annotators and complete the task. Finally, as a result of CDNA’s research projects on different social risks and political issues, a “verification platform for false and/or biased information" is developed. Users only need to enter the news material, and the platform will automatically provide an assessment of its veracity (e.g., whether a news story is misinformation) and nature (e.g., whether an article is advertorial or whether it contains specific political stance).

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 also expanded its perspective to the world, actively establishing a transnational scholarly community.

Project


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.

Platform


Member


Chingching Chang
Distinguished Research Fellow and Director
Research Topic: Media Effects, Media Psychology, Consumer Psychology
Mu-Jung Cho
Assistant Research Fellow
Research Topic: Digital Interaction, Media Psychology, Artificial Intelligence, Data Science
Hen-Hsen Huang
Assistant Research Fellow
Research Topic: Natural Language Processing, Computational Linguistics, Information Retrieval
Yuan Hsiao
Assistant Professor
Research Topic: Political Communication, Social Media, Social Networks
Ying-Ju Chiu
Project Research Scientist
Research Topic: Technology-Assisted Learning, Digital Game-based Learning, Social Network Analysis, Machine Learning, and Epistemic Beliefs
Hao-Hsuan Wang
Data Analyst
Yu-Wei Huang
Data Engineer
Yi-Ru Hsieh
Data Engineer
Liang-Hao Chin
Data Engineer
Hsin-Yu Kuo
Fellowship

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