The Pew Research Center has been experimenting with mobile apps for “signal-contingent experience sampling” to gather data about how Americans use their smartphones. They have just released a report examining the possibilities of this method:
This report utilizes a form of survey known as “signal-contingent experience sampling” to gather data about how Americans use their smartphones on a day-to-day basis. Respondents were asked to complete two surveys per day for one week (using either a mobile app they had installed on their phone or by completing a web survey) and describe how they had used their phone in the hour prior to taking the survey. This report examines whether this type of intensive data collection is possible with a probability-based panel and to understand the differences in participation and responses when using a smartphone app as opposed to a web browser for this type of study.
In 1848, newspaper magnate and Representative Horace Greeley used open records to compare the mileage reimbursements of his fellow representatives to the postal routes (which should have been the shortest routes between districts and the U.S. capital). He found several, including Abraham Lincoln, overcharged significantly.
See Scott Klein’s story at ProPublica.
Ben Casselman of FiveThirtyEight examines the legal, bureaucratic and practical impediments the U.S. government faces in collecting and disseminating data about U.S. citizens.
When the government wants to know how many people are unemployed, it calls people and asks them whether they’re working. When it wants to know how quickly prices are rising, it sends researchers to stores to check price tags. And when it wants to know how much consumers are spending, it mails forms to thousands of retailers asking about their sales.
“Big data” may have revolutionized industries from advertising to transportation, but many of our most vital economic statistics are still based on methods that are decidedly, well, small.
Read the full article
The is an excellent summary of the consequences of the demise of the 3-year ACS tabular products. Please follow through and contact the relevant government officials:
ACS 3-Year Summary Products: Please take action to save the ACS 3-year data products
Steve Ruggles | PAA President and Director of the Minnesota Population Center
March 4, 2015
Gentrification in America Report
Mike Maciag | Governing
This resource is city-specific and provides both counts and maps of gentrified census tracts for the 50 largest cities. To be eligible for gentrification a census tract’s median household income and median home value were both in the bottom 40th percentile of all tracts within a metro area at the beginning of the decade. The gentrified tracts recorded increases in the top third percentile for both measures when compared to all others in a metro area.
And more broadly, this resource has a special issue on gentrification:
The G-Word: A Special Series on Gentrification
The titles in this series are:
Do Cities Need Kids?
The Neighborhood Has Gentrified, But Where’s the Grocery Store?
Just Green Enough
Gentrification’s Not So Black and White After All
The Downsides of a Neighborhood ‘Turnaround
Some Cities Are Spurring the End of Sprawl
Keeping Cities from Becoming “Child-Free Zones”
From Vacant to Vibrant: Cincinnati’s Urban Transformation
Can Cities Change the Face of Biking?
President Obama recently appointed Dr. DJ Patil the Deputy U.S. CTO for Data Policy and Chief Data Scientist.
Read Patil’s Memo to the American People from February 20 and watch his address, Data Science: Where are We Going? with an introduction by President Obama.
This is an index of happiness created from tweets. The index provides a daily score, which can be toggled to exclude weekends, Mondays, etc.
This is an excellent resource because the creators of this happiness index describe the calculation of the index, the words used in it, provide an API, have links to articles based on the index, etc. It is a valuable resource, even if you do not care about happiness as it provides a template for many other uses of data from Twitter.
Instructions [Documenation of index via video or written – click on links]
Words [Words used in index, ranks, etc.]
Blog [The Computational Story Lab. . . mostly related to happiness]
Press [press coverage]
Papers [refereed papers by research team]
Talks [maybe you need a clip for a lecture]
API [lots of examples]
I ran across this in the Wall Street Journal (slide 58 of 93):
Can happiness from tweets reduce drawdowns from selling VIX?
Selling VIX futures has been profitable historically. However, the strategy can be subject to drawdowns, when there is risk aversion . . . . Using the Hedometer index as an input, we have created a Happiness Sentiment Index (HSI), which can be sued to proxy market risk sentiment. . . .
See next post for more on the Hedometer Index.
Nathan Yau of Flowing Data recently published a tutorial on loading data and basic formatting in R. The tutorial covers loading data from CSV files, subsetting data frames, editing data to make it easier to manage and merging multiple datasets.