blumenstock in A Sentence

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    Blumenstock Cadamuro and On.

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    Blumenstock and Eagle.

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    The work of Blumenstock and colleagues is again illustrative.

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    That is, Blumenstock and colleagues didn't inherently care about call records;

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    For example, Joshua Blumenstock and colleagues were part Duchamp and part Michelangelo;

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    In this case, Blumenstock used logistic regression, but he could have used a variety of other statistical or machine learning approaches.

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    Next, in the supervised learning step, Blumenstock built a model to predict the survey response for each person based on their features.

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    The research of Blumenstock and colleagues(2015) involved building a machine learning model that could use digital trace data to predict survey responses.

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    Next, in the supervised learning step, Blumenstock built a statistical model to predict the survey response for each person based on their features.

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    In this case, Blumenstock used logistic regression with 10-fold cross-validation, but he could have used a variety of other statistical or machine learning approaches.

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    An important example of amplified asking comes from the work of Joshua Blumenstock, who wanted to collect data that could help guide development in poor countries.

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    But just one year later, Blumenstock and two colleagues- Gabriel Cadamuro and Robert On- published a paper in Science with substantially better results(Blumenstock, Cadamuro, and On 2015).

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    However, just one year later, Blumenstock and two colleagues- Gabriel Cadamuro and Robert On- published a paper in Science with substantially better results(Blumenstock, Cadamuro, and On 2015).

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    More generally, figure 3.15 shows that for some traits Blumenstock did not improve much beyond just making the simple baseline prediction, but that for other traits there was some improvement.

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    Blumenstock's research began when he partnered with the largest mobile phone provider in Rwanda, and the company provided anonymized transaction records from about 1.5 million customers between 2005 and 2009.

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    Although these two approaches produced similar estimates in this case, the approach of Blumenstock and colleagues was about ten times faster and fifty times cheaper than the traditional Demographic and Health Surveys.

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    After all, one way of viewing them is to say that by using big data and machine learning, Blumenstock and colleagues were able to produce estimates that could be made more reliably by already existing methods.

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    For example, for each person, Blumenstock calculated the total number of days with activity, the number of distinct people a person has been in contact with, the amount of money spent on airtime, and so on.

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    I would like to thank Arnout van de Rijt and David Rothschild for providing data used to recreate some of the graphs from their papers and Josh Blumenstock and Raj Chetty for making public replication files available.

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    The cost and time estimates in Blumenstock, Cadamuro, and On(2015) refer more to variable cost- the cost of one additional survey- and do not include fixed costs such as the cost to clean and process the call data.

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    For example, 97.3% reported owning a radio so if Blumenstock had predicted that everyone would report owning a radio he would have had an accuracy of 97.3%, which is surprisingly similar to the performance of his more complex procedure(97.6% accuracy).

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    For example, 97.3% of respondents reported owning a radio so if Blumenstock had predicted that everyone would report owning a radio he would have had an accuracy of 97.3%, which is surprisingly similar to the performance of his more complex procedure(97.6% accuracy).

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    But when Blumenstock and colleagues aggregated their estimates to Rwanda's thirty districts, they found that these estimates were very similar to those from the demographic and Health Survey, which is widely considered to be the gold standard of surveys in developing countries.

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