Two Distinguished Lectures on Digital Big Data and (Health) Communication: How Research and Practice Are Changing
Everyday life is increasingly taking place online, including health-related actions. Examples of that include posting on health-related discussion fora, the use of smart devices to track our physical activity, and even sensor-enabled clothing to register bodily movements. All of those actions leave behind a wealth of digital traces, causing an exponential growth of data. These data lead to interesting academic questions such as “What can we do with these data?” “Should we adjust our research practices to the data and the new methods of analysis?” “What role does theory have in this new situation?”
These and other questions will be addressed in two keynote lectures that are part of the fifth, half-yearly, symposium of the Amsterdam Center for Health Communication (ACHC) and RPA Communication:
- 12:40- 13:10: Keynote 1: Prof. Dhavan V. Shah: “Digital Traces and Social Ties: How Computational Social Science is Transforming Communication Research”
- 13:10- 13:40: Keynote 2: Prof. Conrad S. Tucker: “From Data to Knowledge: Leveraging the Power of Big Data and Machine Learning in Healthcare”.
- 13:40-13:55: Discussion
Register: If you only wish to attend the distinguished lectures, no registration is needed. If you want to attend the symposium “Digitale (big) data en gezondheidscommunicatie: hoe onderzoek en praktijk verandert” (in Dutch) including the distinguished lectures (in English), please register here. For the full programme of the symposium click here.
First lecture: Prof. Dhavan V. Shah
Digital Traces and Social Ties: How Computational Social Science is Transforming Communication Research
This talk examines the growing role of social and digital media in communication research, arguing that the turn toward computational social science is transforming this work through increased attention to digital trace and electronic text data. This is certainly true for work connecting communication and health management, especially as it relates to chronic care of long-term diseases such as cancer and addiction.
The framework for research shared in this talk emphasizes the role of networks, the effects of expression, and the power of text in addressing pressing social concerns and communication questions. Examples will be drawn from data collected through multiple NIH-funded studies of health technology to point to larger conclusions about the intersection of “big data,” communication technologies, and changing research and industry practices around health management.
Dhavan V. Shah is the Louis A. & Mary E. Maier-Bascom Professor at the University of Wisconsin, where he is Director of the Mass Communication Research Center (MCRC) and Scientific Director in the Center for Health Enhancement System Studies (CHESS).
Shah’s research focuses on communication influence on social judgments, civic engagement, and health support. He has developed three major lines of inquiry: (1) the influence of message framing and processing on decision-making and opinion formation; (2) the capacity of mass and interpersonal communication, especially online communication, to encourage civic and political participation; and (3) the effects of computer-mediated interactions, particularly the expression of social support, on the management of cancer, aging, and addiction.
This work has been supported by grants and awards totaling over $34.9 million from sources such as the Ford Foundation, PBS, CPB, Rockefeller Brothers, Carnegie Corporation, Russell Sage, Spencer, Social Science Korea, National Cancer Institute (NIH-NCI), Agency for Health Research and Quality (NIH-AHRQ), National Heart, Lung, And Blood Institute (NIH-NHLBI), and the National Institute for Drug Abuse (NOH-NIDA). Across these domains, he has increasingly applied computational techniques to social science questions, employing computer-assisted text analysis, machine learning, network mapping, and predictive analytics to politics and health.
Second lecture: Prof. Conrad S. Tucker
From Data to Knowledge: Leveraging the Power of Big Data and Machine Learning in Healthcare
“We are drowning in data but thirsting for knowledge” is a phrase that is typically used to define the challenges of the 21st century regarding big data. Big data is typically characterized into “5Vs”, with velocity being the speed at which data is captured, volume being the size of the data, variety being the types of data acquired (e.g. textual data, medical image data, genomic data, etc.), veracity being the accuracy of the resulting predictive models and value being the tangible benefits of these models to both patients and health care decision makers. This research explores how digital health data is collected and mined, in order to facilitate the early detection, as well as long-term management of patients’ health-related abnormalities. By developing machine learning methods to capture patient data, researchers aim to remotely (e.g., a patient’s home) model and predict the emergence (or lack therefore) of deviations from a patients’ wellness state and provide intervention solutions designed to attenuate patient health issues.
Dr. Conrad Tucker holds a joint appointment as Associate Professor in Engineering Design and Industrial and Manufacturing Engineering at The Pennsylvania State University. He is also affiliate faculty in Computer Science and Engineering. Dr. Tucker is the director of the Design Analysis Technology Advancement (D.A.T.A) Laboratory. His research focuses on the design and optimization of systems through the acquisition, integration and mining of large scale, disparate data.
Dr. Tucker has served as PI/Co-PI on several federally funded grants from the National Science Foundation (NSF), the Air Force Office of Scientific Research (AFOSR), the Defense Advanced Research Projects Agency (DARPA) and the Office of Naval Research (ONR). He is currently serving as PI and Site Director of the NSF Center for Health Organization Transformation (CHOT), an NSF Industry/University Cooperative Research Center at Penn State. He received his Ph.D., M.S. (Industrial Engineering), and MBA degrees from the University of Illinois at Urbana-Champaign, and his B.S. in Mechanical Engineering from Rose-Hulman Institute of Technology. Dr. Tucker is part of the inaugural class of the Gates Millennium Scholars (GMS) program, funded by a $1 billion grant from the Bill and Melinda Gates Foundation.
The lectures take place in REC C10.20 (common room)
Roeterseilandcampus - building B/C/D (entrance B/C)
Nieuwe Achtergracht 166 | 1018 WV AmsterdamGo to detailpage
Building B: +31 (0)20 525 5340 | Building C: +31 (0)20 525 5470