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Predicting Google closures

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2022-10-01 05:30:17

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Prompted by the shutdown of Google Reader, I ponder the evanescence of online services and wonder what is the risk of them disappearing. I collect data on 350 Google products launched before March 2013, looking for variables predictive of mortality (web hits, service vs software, commercial vs free, FLOSS, social networking, and internal vs acquired). Shutdowns are unevenly distributed over the calendar year or Google’s history. I use logistic regression & survival analysis (which can deal with right-censorship) to model the risk of shutdown over time and examine correlates. The logistic regression indicates socialness, acquisitions, and lack of web hits predict being shut down, but the results may not be right. The survival analysis finds a median lifespan of 2824 days with a roughly Type III survival curve (high early-life mortality); a Cox regression finds similar results as the logistic - socialness, free, acquisition, and long life predict lower mortality. Using the best model, I make predictions about probability of shutdown of the most risky and least risky services in the next 5 years (up to March 2018). (All data & R source code is provided.)

Google has occasionally shut down services I use, and not always with serious warning (many tech companies are like that - here one day and gone the next - though Google is one of the least-worst); this is frustrating and tedious.

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