|1:30pm - 3:00pm: Individual talks with short Q&A section|
|3:00pm - 3:30pm: Coffee Break|
|3:30pm - 5:00pm: Panel discussion|
Addressing Big Societal Challenges with Digital Behavioral Data
Workshop at the 1st European Symposium on Societal Challenges in Computational Social Science (http://symposium.computationalsocialscience.eu/)
November 15, 2017
Mathieu Génois, GESIS
Julian Kohne, GESIS
Katrin Weller, GESIS
Claudia Wagner, GESIS and University of Koblenz
Markus Strohmaier, University of Aachen and GESIS
Open questions to be discussed include, but are not limited to:
- Which new sources for Digital Behavioral Data can be used for Computational Social Science research (e.g. wearable sensors, mobile phones, online data)?
- Which major societal challenges can be studied through the use of Digital Behavioral Data?
- How can digital traces be combined with traditional surveys or experimental designs?
- What kind of research infrastructure is needed to maximize the potential of Digital Behavioral Data (education/open access/open data)?
- Which legal and ethical challenges do we face (e.g. privacy/informed consent)?
- What are our visions for the future?
Nowadays, numerous aspects of human life are recorded and stored in databases which are increasingly available for researchers. Prominent examples include data on shopping, travel, housing, political expression, dating, finances, or professional work. This ever increasing digitalization of every aspect of modern life has created ample opportunity to use digital traces for studying human behavior and interactions. Interestingly, this new approach has been partly led by researchers outside of the area of social sciences. In the relatively new field of Computational Social Science (CSS), researchers from the Social Sciences, Applied Mathematics, Statistical Physics and Computer Science work together to study classic research questions from the Social Sciences with new kinds of data, tools and methods. These research questions often relate to major societal challenges of the 21st century such as social inequality, discrimination and (political) radicalization. The aim of this workshop is to bring together these communities to discuss how Digital Behavioral Data can be used to study societal challenges and human behavior, how new wearable sensors, apps and personalized web tracking are creating new research questions, how we can integrate Digital Behavioral Data with classic survey or experimental research, which kinds of infrastructural changes would benefit the community, how we should deal with legal and ethical concerns, and which directions are most promising for the future.
This half-day workshop will take place in the afternoon of November 15, 2017. It will be an interactive workshop, featuring invited experts as panelists and lots of room for discussion.
Invited speakers with expertise in working with different types of Digital Behavioral Data will provide insights into the current state of the art, give examples for recent research results, and explain the technical background and current limitations of technology.
We are addressing an audience of interdisciplinary researchers in the field of CSS. We particularly welcome researchers who are interested in working with new types of Digital Behavioral Data in addition to traditional social science approaches (e.g. surveys). We invite the audience to actively engage in the discussion and to contribute ideas for using different methods to analyze Digital Behavioral Data as well as to voice concerns about their usage.
The workshop will take place in the afternoon on November 15, 2017 at the Alan Turing Institute. The Alan Turing Institute is located at the British Library:
96 Euston Rd
Participants for the workshop need to register for the 1st European Symposium on Societal Challenges in Computational Social Science (http://symposium.computationalsocialscience.eu/), and select this workshop in the registration form. Tickets for the workshop/tutorial day + main symposium will be 60 GBP. Tickets for tutorial day only are for free. The number of participants will be limited based on the room capacities.