Lucas Shen Y.S.

Measuring Political Media Slant Using Text Data

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Substring accuracy across time

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Effect Sizes

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International Trafficking in Persons and Global Health Security: Evidence from Two Modern Pandemics

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Reduced form: Coastlines and Covid-19

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Contact rate in SIRD, interactions by months

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Deconstructing the MeToo Movement and the Blue Wave in the 2018 House Elections

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Timeline of MeToo tweets (2018)

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Conditional relationship b/w MeToo tweets and individual returns

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Strategic candidacy of Democratic women challengers

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Income and Productivity Trends of Guangdong: A Data-Driven Case Study of the Greater Bay Area

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Permutation tests

Neighborhood Asymmetries and Visits

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Scale & borders in the Singapore context

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Two neighbourhoods (Mount Pleasant & Toa Payoh Central)

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Asymmetries in mismatch and visits

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EIP and increases in neighborhood visits

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Measurement Gap? Effect of Survey Instrument and Scoring on the Partisan Knowledge Gap

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Different treatment groups and instruments

Does working from home work? A natural experiment from lockdowns

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Change in output (tracked changes)

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Sensitivity to geocoding

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Standard vs local time

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Local time by hour-of-day

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Global rollout of lockdowns

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Social Exposure Zones in a Small City

Neighborhoods, family, and child health outcomes

Segregation Across Neighborhoods in a Small City

Unexpected Shocks to Movement and Job Search: Evidence from COVID-19 Policies in Singapore Using Google Data

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Early changes (anomalies) in movement patterns

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Lockdown announcement effect

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Early changes in job searches

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Report on Surveying the Singapore Urban Labour Market Using Online Job Postings

LexicalRichness: A module to compute textual lexical richness
LexicalRichness computes measures of lexical richness (aka lexical diversity or language sophistication) from textual data. Lexical richness refers to the ratio of different unique words to the total number of words in a text. Measures include MTLD and HD-D, which are resilient to varying text lengths.
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runPyNB: Run Jupyter notebooks in command-line and Makefiles
runPyNB offers a command-line utility that runs (and time) Jupyter notebook files (.ipynb) without launching the IDEs (Jupyter notebooks or JupyterLab).
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Forestplot: Make publication-ready but customizable coefficient plots
Forestplot makes publication-ready coefficient plots easy to make out-of-the-box. Other names for forest plots are: coefplots, coefficient plots, meta-analysis plots, dot-and-whisker plots, blobbograms, margins plots, regression plots, and ropeladder plots. Users provide a dataframe (e.g. from a spreadsheet) where rows correspond to a variable/study with columns including estimates, variable labels, and confidence interval limits.
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