YouTubeTracker is a tool in development by COSMOS (Collaboratorium for Social Media and Online Behavioral Studies) that can track, monitor, and identify influential YouTube groups and content. Through visual analytics, YouTubeTracker helps researchers identify trends, opinions, communities, and anomalous behaviors such as bots, spam, and trolls as they relate to the YouTube platform.
As a team lead for this project, I was responsible for exploring feature ideation, establishing user flow and usability best practices, communicating with end-users, and designing story-driven dashboards.
- Maintaining design patterns and user flow consistent with other COSMOS applications
- Designing a series of dashboards to display over 25 computed YouTube metrics that can be expanded as new social media forensic techniques arise
This collection of work illustrates some of my contributions as UI/UX team lead for YouTubeTracker.
I collaborated across teams to compile a feature-rich list and create concepts for initial grant funding. My sketches for user flow and page functionalities are featured in the promotional image below.
User Interface Design
I created static mock-ups and conceptualized analytic dashboards, features, and functions. The Posting Frequency page mockup below is one of 7 narrative-based dashboards I designed.
I interviewed end-users for qualitative feedback to improve designs and functionality. In the mockup below, an addition was made to dashboard navigation after researchers requested the ability to view the entire history of their dataset and then select by ranges of time.
I developed strategies for addressing beta users and began collecting measurements with Google Analytics. I created the graphics in the following images as a way to establish a more personal connection with our users.
- Condensed 25+ metrics to 7 dashboard mockups for development
- Created dashboards with a modular approach so that additional features can be later added without my involvement in this project
- Developed my abilities as a designer working with dynamic data