# talks

## upcoming talks

None

## past talks

**The Low Hanging Fruit of the Twitter Following Graph**

2021-08-11, Joint Statistical Meetings

In recent applied work on the Twitter media ecosystem, we have found that Twitter metadata (such as follows, likes, quotes, retweets, mentions, etc) is often more informative than the actual content of tweets themselves. The metadata, in some sense, is the right data to use for many inference tasks. In particular, we find that embedding the Twitter following graph is highly informative. However, collecting the following graph is rather challenging due to API rate limits, and storing graphs can also be challenging. We present some computational infrastructure to make access and storage of this high signal data more straightforward, and suggest that research progress would be well served by an increased focus on instrumentation. slides

**Solving the model representation problem with broom**

2019-01-25, `rstudio::conf(2019)`

The R objects used to represent model fits are notoriously inconsistent, making data analysis inconvenient and frustrating. The broom package resolves this issue by defining a consistent way to represent model fits. By summarizing essential information about fits in tidy tibbles, broom makes it easy to programmatically work with model objects. Combining broom with list-columns results in an especially powerful way to work with many model fits at once. This talk will feature several case studies demonstrating how broom resolves common problems in data analysis. video, slides

**Solving the model representation problem with broom**

2018-09-19, Statistics Graduate Student Seminar

slides

**Convenient data analysis with broom**

2018-11-30, RStudio Webinar Series

Broom is a package that converts statistical objects into tibbles. This consistent structure makes it easier to accomplish many standard modelling tasks. In this webinar I’ll demonstrate how to use to broom to work with many models at once. We’ll see how broom makes it easier to visualize models, work with bootstrapped fits and assess model diagnostics. video, slides

**Solving the model representation problem with broom**

2018-09-19, Madison R User Group

slides

## slides from various informal presentations

**Identifiability of homophily and contagion in social networks**

2022-02-23, Madison Networks Reading Group

slides

**Triangles & networks**

2021-02-17, STAT 992 Seminar on Tensors

slides

**A new way to think about citations**

2020-11-17, Rohe Lab Group Meeting

slides

**The linear probability model**

2019-11-19, STAT 992 Seminar Course presentation

slides

**rstudio internship progress update**

2018-07-23, RStudio tidyverse team

slides

**Locally Interpretable Model-Agnostic Explanations**

2018-03-29, Rice DataSci club

slides

**Your First R Package**

2018-02-22, Rice DataSci club

slides

**COMP 540 Prediction Project Advice**

2018-03-09, Rice University

slides

**Super Learner**

2018-01-23, Allen Lab Group Journal Club

slides

Last updated on 2022-04-27.