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Gaurav

Snakes on Ladders: Encouraging People to Climb the Engagement Ladder

Marketers love engagement ladders. To increase engagement with a product, many companies segment their users based on usage, for instance, into heavy (super), medium (average), and light, and prod their users to climb the ladder by suggesting they do things that people in the segment above them are doing and

Why do We Fail? And What to do About It?

I recently read Gawande’s The Checklist Manifesto. (You can read my review of the book here and my notes on the book here.) The book made me think harder about failure and how to prevent it. Here’s a result of that thinking. We fail because we don’t

Wanted: Effects That Support My Hypothesis

Do survey respondents account for the hypothesis that they think people fielding the survey have when they respond? The answer, according to Mummolo and Peterson, is not much. Their paper also very likely provides the reason why people don’t pay much attention. Figure 3 provides data on manipulation checks—

Interview with InfoQ

I recently gave an interview to InfoQ about my paper (and associated open source software) on predicting the race and ethnicity of a person using the sequence of characters in a name. Here a relevant excerpt: InfoQ: Can you discuss how we can learn from names? What ML/DL algorithms

Estimating the Trend at a Point in a Noisy Time Series

Trends in time series are valuable. If the cost of a product rises suddenly, it likely indicates a sudden shortfall in supply or a sudden rise in demand. If the cost of claims filed by a patient rises sharply, it plausibly suggests rapidly worsening health. But how do we estimate

Rocks and Scissors for Papers

Zach and Jack* write: What sort of papers best serve their readers? We can enumerate desirable characteristics: these papers should (i) provide intuition to aid the reader’s understanding, but clearly distinguish it from stronger conclusions supported by evidence; (ii) describe empirical investigations that consider and rule out alternative hypotheses

What Clicks With the Users? Maximizing CTR

Given a pool of messages, how can you maximize CTR? The problem of maximizing CTR reduces to the problem of estimating the probability that a person in a specific context will click on each of the messages. Once you have the probabilities, all you need to do is apply the

Quitting at 40

Recently, I had the pleasure of interviewing Walter Guillioli. Walter is one of those few brave people who has had the courage to take the reins of his life. Walter carefully and smartly worked to save enough to live off the savings and then quit a well-paying job at 40

Citing Working Papers

Public versions of working papers are increasingly the norm. So are citations to them. But there are four concerns with citing working papers: 1. Peer review: Peer review improves the quality of papers, but often enough it doesn’t catch serious, basic issues. Thus, a lack of peer review is

A/B Testing Recommendation Systems

Say that you are building a news recommender that lists which relevant news items are in each person’s news feed. Say that your first version of the news recommender is a rules-based system that uses signals like how many people in your network have seen the news, how many