Twitter shut off it’s API to LinkedIn, and released a post about delivering a consistent twitter experience. I’ve seen interpretations of the Twitter post ranging from ‘don’t mimic twitter’s functionality and you’ll be alright’ to ‘Twitter is killing its own ecosystem‘. Are you entitled to your Twitter entitlement? Why Twitter Has An API in the first place Offering an API is a strategic choice. They involve tradeoffs. An API costs Twitter: Money to serve, develop, and maintain Risk, from consumers and competitors alike What Twitter gets in return: Scale, in the form of features that are not, will not, or cannot be built by Twitter itself, that are built by other companies Innovation, in the form of observing the ecosystem[…]
Author: Christopher Berry
I present to you, a Safe Harbor Statement: “Our discussion may include predictions, estimates or other information that might be considered forward-looking. While these forward-looking statements represent our current judgment on what the future holds, they are subject to risks and uncertainties that could cause actual results to differ materially. You are cautioned not to place undue reliance on these forward-looking statements, which reflect our opinions only as of the date of this presentation. Please keep in mind that we are not obligating ourselves to revise or publicly release the results of any revision to these forward- looking statements in light of new information or future events. Throughout today’s discussion, we will attempt to present some important factors relating to[…]
Boxplots are a good way to examine the distribution of data. They allow you to see outliers and understand how it skews. The image below comes from the the US Labor Department 2011 Time Use Survey. The X-axis represents days of the week, Sunday = 1 and Saturday = 7. Along the Y-axis is t010101, the variable for ‘time sleeping’, and it is expressed in the form of minutes. This is what I see when I first crack open some data. It’s raw. You see a box and you see a dark line inside that box. The dark line is the MEDIAN, and the box contains half of all the observations in the sample. the dots represent individuals at the[…]
Mike Miller (@mlmilleratmit) wrote a piece entitled “Why the days are numbered for Hadoop as we know it.” The key paragraph is: “In summary, Hadoop is an incredible tool for large-scale data processing on clusters of commodity hardware. But if you’re trying to process dynamic data sets, ad-hoc analytics or graph data structures, Google’s own actions clearly demonstrate better alternatives to the MapReduce paradigm. Percolator, Dremel and Pregel make an impressive trio and comprise the new canon of big data. I would be shocked if they don’t have a similar impact on IT as Google’s original big three of GFS, GMR, and BigTable have had.” To simplify, in my words: The software package known as Hadoop is incredible for processing[…]
This is the final post in a series on how Americans live, based off the The US Labor Department 2011 Time Use Survey. In sum, Americans work hard. Those with household children under 6 spend on average: 2.85 hours a day doing housework (Women: 3.16) 2.33 hours a day caring for children (Women: 2.59) 30 minutes a day on education And that excludes the hours they spend in the paid workforce! You can’t say they play hard from the ATUS. If children or the elderly aren’t around to be looked after, the leisure time gets dumped into the Television sink – 2.57 weekday hours, 3.19 weekend hours. General (unattributable) game playing time is highest amongst youth – 1.03 weekday hours[…]
This is part 4 in a series on How Americans Live. The US Labor Department released the 2011 Time Use Survey on June 22. So far, we’ve seen how the American Time Use Survey (ATUS) is designed, why the hours worked measure appears to be low, and, why the computer use measure of 7 minutes is a product of coding design. On Simultaneous Activities ATUS focuses on quantifying primary activities only. And yet, it is the rise of the simultaneous activity that explains a lot about how Americans live. On average, an American spends 1.7 minutes a day listening to music (not radio), as a primary activity. That keyword – primary – is really important. On average, an American spends[…]
This is part 3 in a series on How Americans Live. The US Labor Department released the 2011 Time Use Survey on June 22. A few facts should raise questions: In 2011, each day, at the highest aggregated level, on average, an American spends: 2.75 hours watching TV 43 minutes buying goods and services 18 minutes exercising, playing sports, and recreating 10 minutes on telephone calls, mail, and email 7 minutes on leisure computer use (excluding games) 2.75 hours watching TV, 7 minutes computer use That 2.75 hour watching TV figure ought to stick out like a craw for many analysts, because, by some estimates, 19.25 hours a week is a really low figure. The same goes for 7 minutes[…]
Understanding how Americans live has a lot to do with understanding what they do. Or more specifically, what they remember about doing and how it’s recorded. The following fact from the 2011 Time Use Study (ATUS) should cause some anxiety. “In 2011, each day, at the highest aggregated level, on average, an American spends: 3.57 hours working” How does the US Bureau of Labor know? What if you called 12,479 people randomly on random days and asked them what they did yesterday? That’s pretty much how it’s done. Every day, with a few exceptions (the call center took the day after Christmas off in 2011. The bureau also has no data about New Year’s Day 2007, Christmas Day 2008, and[…]
This is part one of a series on how Americans live. The US Labor Department released the 2011 Time Use Survey on June 22. You are welcome to replicate results using the data files* to mix and mash. In 2011, each day, at the highest aggregated level, on average, an American spends: 8.7 hours sleeping 3.57 hours working 2.75 hours watching TV 1.24 hours eating and drinking 43 minutes buying goods and services 42 minutes socializing and communicating 34 minutes preparing food 18 minutes exercising, playing sports, and recreating 10 minutes on telephone calls, mail, and email 7 minutes on leisure computer use (excluding games) Focus on the drop off. It’s not in a stacked bar chart so you can[…]
Do normative statements cause harm to analytics programs in the long run? This may be a bit meta because I’m talking about the effect that an activity that analysts do every day has on what gets selected to study. A normative statement expresses a value judgement. Consider the following three statements: The strawberry campaign contributed to the acquisition of 1000 new customers out of the 10000 acquired last month. The strawberry campaign only contributed to the acquisition of 1000 new customers out of the 10000 acquired last month. The strawberry campaign failed, only contributing to 10% of new customers acquired last month. Which is the most normative? Consider the next three statements: The strawberry campaign contributed to the acquisition of[…]