Studying Up,
Using Mixed Methods.
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I combine experimental, computational, and qualitative methods to pursue two lines of research, one focusing on high-status consumers and the other exploring various place entrepreneurs.
I combine experimental, computational, and qualitative methods to pursue two lines of research, one focusing on high-status consumers and the other exploring various place entrepreneurs.
Combining insights from the gentrification scholarship and the literature on omnivorousness, I study how gentrifiers select neighborhoods and consume located institutions, and their implications on class and racial segregation/integration.
I study how place entrepreneurs - like business owners, landlords, and travel writers - produce the symbolic and physical value of places in ways that reproduce or shift the status hierarchy of places.
Click the image or the title to learn more about each line of research
Innovative Data and Methods
Innovative Data and Methods
I am a versatile, mixed-method researcher using different data and methods to answer my questions most effectively and creatively. I combine traditional and emerging sources of data and methods to capture and measure cultural factors and processes contributing to spatial inequality. Data sources include online survey experiments, business data, Google Street View images, geo-tagged text data, and in-depth interviews. I use both computational and qualitative analyses to gain a deeper understanding and extract insights from these data sources.
- Online survey experiments
Designed online surveys using Qualtrics
Ran experiments using Amazon Mechanical Turk and Prolific
Conducted quantitative analysis using STATA, Python, and R (e.g., mediation analysis)
Conducted qualitative content analysis using NVivo
- Survey, spatial, text, and image data and computational analysis
Proficient in using demographic, business, and administrative data (e.g., the US Census Data, American Community Survey data, and Data Axle Business data)
Conducted quantitative analysis using STATA, R, and Python (e.g., linear/logistic regression models, multi-level regression models)
Experienced in using web-scrapped text data (e.g., Airbnb text descriptions, the New York Times travel articles)
Conducted computational text analysis using R and Python (e.g., dictionary method, topic modeling - LDM/STM)
Conducted text network analysis using R
Experienced in using spatial data
Conducted geocoding and created maps using ArcGIS/QGIS/R and Tableau
Used Google Street View (GSV) images
Webscraped GSV images using API in Python
Managed image data labeling website
Conducted pre-processing and segmentation of image data using R
- Qualitative data and analysis
Designed in-depth interview protocols
Recruited and interviewed various populations from residents, business owners, fashion designers, landlords, and property managers
Conducted qualitative coding and analysis using Nvivo and DeDoose
Developed a qualitative coding scheme for digital ethnography, trained coders, and managed the data
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