The Parable of Google Flu: Traps in Big Data Analysis

Large errors in flu prediction were largely avoidable, which offers lessons for the use of big data. In February 2013, Google Flu Trends (GFT) made headlines but not for a reason that Google executives or the creators of the flu tracking system would have hoped. Nature reported that GFT was predicting more than double the proportion of doctor visits for influenza-like illness (ILI) than the Centers for Disease Control and Prevention (CDC), which bases its estimates on surveillance reports from laboratories across the United States ( 1, 2). This happened despite the fact that GFT was built to predict CDC reports. Given that GFT is often held up as an exemplary use of big data ( 3, 4), what lessons can we draw from this error?Other Research Uni

Google Flu Trends Still Appears Sick: An Evaluation of the 2013-2014 Flu Season

In response to its poor performance during the 2012-2013 flu season, Google Flu Trends (GFT) engineers announced a redesign of the GFT algorithm. Two changes were made: (1) dampening anomalous media spikes and (2) using ElasticNet, rather than regression, for estimation. This paper identifies several problems that persist in the new algorithm. First, the transparency problems identified in our earlier Science paper appear to have, if anything, become worse. Second, there are reasons to doubt whether a spike in media attention was the only, or primary, cause of GFT's errors. Finally, there is strong evidence that GFT is still not using all the information at its disposal to make accurate measurements of flu prevalence. While it is too early to give a complete evaluation of the new algorithm, these results are discouraging.Other Research Uni

Computational Social Science

A field is emerging that leverages the capacity to collect and analyze data at a scale that may reveal patterns of individual and group behaviors.Governmen

Rising tides or rising stars?: Dynamics of shared attention on twitter during media events

"Media events" generate conditions of shared attention as many users simultaneously tune in with the dual screens of broadcast and social media to view and participate. We examine how collective patterns of user behavior under conditions of shared attention are distinct from other "bursts" of activity like breaking news events. Using 290 million tweets from a panel of 193,532 politically active Twitter users, we compare features of their behavior during eight major events during the 2012 U.S. presidential election to examine how patterns of social media use change during these media events compared to "typical" time and whether these changes are attributable to shifts in the behavior of the population as a whole or shifts from particular segments such as elites. Compared to baseline time periods, our findings reveal that media events not only generate large volumes of tweets, but they are also associated with (1) substantial declines in interpersonal communication, (2) more highly concentrated attention by replying to and retweeting particular users, and (3) elite users predominantly benefiting from this attention. These findings empirically demonstrate how bursts of activity on Twitter during media events significantly alter underlying social processes of interpersonal communication and social interaction. Because the behavior of large populations within socio-technical systems can change so dramatically, our findings suggest the need for further research about how social media responses to media events can be used to support collective sensemaking, to promote informed deliberation, and to remain resilient in the face of misinformation. © 2014 Lin et al

Retweeting: its linguistic and epistemic value

This paper analyses the communicative and epistemic value of retweeting (and more generally of reposting content on social media). Against a naïve view, it argues that retweets are not acts of endorsement, motivating this diagnosis with linguistic data. Retweeting is instead modelled as a peculiar form of quotation, in which the reported content is indicated rather than reproduced. A relevance-theoretic account of the communicative import of retweeting is then developed, to spell out the complex mechanisms by which retweets achieve their communicative goals. The last section outlines the epistemic threats posed by the increasing prevalence of retweeting on social media, linking them to the low reputational, cognitive, and practical costs linked to this emerging form of communication

Is Necessity the Mother of Innovation? The Adoption and Use of Web Technologies among Congressional Offices

From first paragraph: Communication between legislator and constituents is fundamental to effective democratic representation, and devising the institutional means for citizen/legislator communication stands as one of the core and persistent problems in the practice of democracy. A legislator needs information about the preferences, ideals, norms, and beliefs of her constituents in order to do her job well. Similarly, citizens need information about the actions and decisions of their representative in order to maintain appropriate accountability. But as national problems become more complex, and as the political process grows more and more dominated by experts and organized groups, it is becoming more difficult for interested citizens to understand the very meaning of government action, much less to find an effective voice in the process