HELPING PEOPLE'S

Brian Head is a research methodologist at RTI International. This post first appeared on SurveyPost on 20 May, 2014. You can follow Brian on Twitter @BrianFHead . Survey researchers have become interested in big data because it offers potential solutions to problems we’re experiencing with traditional methods. Much of the focus so far has been on social media (e.g., Tweets), but sensors (wearable tech) and the internet of things (IoT) are producing an increasingly rich, complex, and massive source of data. These new data sources could lead to an important change in how individuals see the data collected about them, and thus have ramifications for those interested in gathering and analyzing those data. Who compiles data? Quantitative data about people have been gathered for millennia. But with technological advances and identification of new purposes for it, the past 100 years have seen significant increases in the amount of data produced and collected—e.g., data on consume...

Ashley Richards is a survey methodologist at RTI International. This post first appeared on SurveyPost on 29, July 2014.   Last fall at MAPOR  , Joe Murphy presented the findings of a fun study he did with our colleague, Justin Landwehr, and me. We asked survey respondents if we could look at their recent Tweets and combine them with their survey data. We took a subset of those respondents and masked their responses on six categorical variables. We then had three human coders and a machine algorithm try to predict the masked responses by reviewing the respondents’ Tweets and guessing how they would have responded on the survey. The coders looked for any clues in the Tweets, while the algorithm used a subset of Tweets and survey responses to find patterns in the way words were used. We found that both the humans and machine were better than random in predicting values of most of the variables. We recently took this research a step further and compared the accuracy of ...

In 2011 then Census Director Robert Groves  wrote  on the Census Director’s Blog about the burgeoning volume of “organic data”—data that, as opposed to “designed data,” have no meaning until they are used (surveys are a primary example of the latter). He noted that finding ways to combine these two types of data to increase the “information-to-data ratio” was a challenge, but also represented the future of surveys. Using terms identified as “big data descriptors” in Groves’ piece, as well as a few other terms I think qualify, I put together the graph below to show the number of AAPOR presentation titles between 2010 and 2013 that contain a big data descriptor. 1,2 One take away is the increased interest researchers have shown in big data over the past few years. An equally important lesson is that almost all of the attention big data has received from AAPOR members—at least measured by the number of presentations they’ve done—has been on social networking sites (SNS). I f...