In this project, we worked to find design implications that can help system developers to design the next generation of open online feedback exchange systems.


I worked in the UCSD Design lab as an UX researcher and data analyst along with Regina Cheng from University of Washington, Maysnow Liu from University of California Davis, under the supervise of Professor Steven Dow. We are currently working on a research paper aiming for ACM CHI Conference on Human Factors in Computing Systems​ 2020. Our final goal is to embed our system in to a large open Civic Design competition (D4SD).

What we did:
  1. 1. We scraped and analyzed large scale data from a popular open online community dedicated for feedback exchanges

  2.  We recruited 12 active community members and conducted 12 semi-structured interviews on    strategies and challenges of online feedback exchanges.

  3. We developed a qualitative coding scheme via a semi-Grounded Theory approach

​Summary of Data Analysis Skill we used

Semantic Analysis 

  1. Bag of Words

  2. Latent Semantic Analysis 

  3. Topic Modeling 

  4. Cosine Similarity

Sentiment Analysis  

  1. Sentiment Polarization

  2. Grammar Mood


Inferential statistics 

  1. Generalized Linear Regression model

  2. Poisson Regression Model

I'll keep posted more details after CHI2020 submission.