Alexander Lex - The reVISit User Study Platform and Applications in Studying Misinformation
Host
Arvind Satyanarayan
CSAIL
Abstract:
In this talk I introduce the reVISit framework for designing and running empirical studies online. Traditional survey tools limit the flexibility and reproducibility of online experiments. To remedy this, we introduce a domain-specific language, the reVISit Spec, that researchers can use to design complex online user studies. reVISit Spec, combined with the relevant stimuli, is compiled into a ready-to-deploy website that handles all aspects of a user study, including sophisticated provenance-based data tracking, randomization, etc. reVISit is a community focused project and ready to use! Visit https://revisit.dev/ to get started.
I will then pivot to talk about data-driven misinformation in the form of charts shared on social networks. I will demonstrate that “lying with charts” doesn’t work the way we (used to) think about it, and introduce a few strategies to “protect” charts and charting tools from being abused by malicious users. I will connect back to reVISit by illustrating how we leveraged it to run a series of crowd-sourced experiments.
Bio:
Alexander Lex is an Associate Professor of Computer Science at the Scientific Computing and Imaging Institute and the Kahlert School of Computing at the University of Utah. He directs the Visualization Design Lab where he and his team develop visualization methods and systems to help solve today’s scientific problems. Recently he is working on visualization accessibility, visual misinformation, provenance and reproducibility, and user study infrastructure. He is the recipient of an NSF CAREER award and multiple best paper awards or best paper honorable mentions at IEEE VIS, ACM CHI, and other conferences. He also received a best dissertation award from his alma mater. He co-founded datavisyn, a startup company developing visualization solutions for the pharmaceutical industry.
This talk will also be streamed over Zoom: https://mit.zoom.us/j/99703652090.
In this talk I introduce the reVISit framework for designing and running empirical studies online. Traditional survey tools limit the flexibility and reproducibility of online experiments. To remedy this, we introduce a domain-specific language, the reVISit Spec, that researchers can use to design complex online user studies. reVISit Spec, combined with the relevant stimuli, is compiled into a ready-to-deploy website that handles all aspects of a user study, including sophisticated provenance-based data tracking, randomization, etc. reVISit is a community focused project and ready to use! Visit https://revisit.dev/ to get started.
I will then pivot to talk about data-driven misinformation in the form of charts shared on social networks. I will demonstrate that “lying with charts” doesn’t work the way we (used to) think about it, and introduce a few strategies to “protect” charts and charting tools from being abused by malicious users. I will connect back to reVISit by illustrating how we leveraged it to run a series of crowd-sourced experiments.
Bio:
Alexander Lex is an Associate Professor of Computer Science at the Scientific Computing and Imaging Institute and the Kahlert School of Computing at the University of Utah. He directs the Visualization Design Lab where he and his team develop visualization methods and systems to help solve today’s scientific problems. Recently he is working on visualization accessibility, visual misinformation, provenance and reproducibility, and user study infrastructure. He is the recipient of an NSF CAREER award and multiple best paper awards or best paper honorable mentions at IEEE VIS, ACM CHI, and other conferences. He also received a best dissertation award from his alma mater. He co-founded datavisyn, a startup company developing visualization solutions for the pharmaceutical industry.
This talk will also be streamed over Zoom: https://mit.zoom.us/j/99703652090.