Can we predict electoral outcomes from Wikipedia traffic?

by Jonathan Bright 06/12/2016

Data show that the relative change in page views to the general Wikipedia page on the election can offer an estimate of the relative change in election turnout.

by Jonathan Bright 06/12/2016

2016 presidential candidate Donald Trump in a residential backyard near Jordan Creek Parkway and Cody Drive in West Des Moines, Iowa, with lights and security cameras. Image by Tony Webster (Flickr).

As digital technologies become increasingly integrated into the fabric of social life their ability to generate large amounts of information about the opinions and activities of the population increases. The opportunities in this area are enormous: predictions based on socially generated data are much cheaper than conventional opinion polling, offer the potential to avoid classic biases inherent in asking people to report their opinions and behaviour, and can deliver results much quicker and be updated more rapidly. In their article published in EPJ Data Science, Taha Yasseri and Jonathan Bright develop a theoretically informed prediction of election results from socially generated data combined with an understanding of the social processes through which the data are generated. They can thereby explore the predictive power of socially generated data while enhancing theory about the relationship between socially generated data and real world outcomes. Their particular focus is on the readership statistics of politically relevant Wikipedia articles (such as those of individual political parties) in the time period just before an election. By applying these methods to a variety of different European countries in the context of the 2009 and 2014 European Parliament elections they firstly show that the relative change in number of page views to the general Wikipedia page on the election can offer a reasonable estimate of the relative change in election turnout at the country level. This supports the idea that increases in online information seeking at election time are driven by voters who are considering voting. Second, they show that a theoretically informed model based on previous national results, Wikipedia page views, news media mentions, and basic information about the political party in question can offer a good prediction of the overall vote share of the party in question. Third, they present a model for predicting change in vote share (i.e., voters swinging towards and away from a party), showing that Wikipedia page-view data provide an important increase…

Politics & Government

Crowdsourcing for public policy and government

by Jonathan Bright 27/08/2015

The growing interest in crowdsourcing for government and public policy must be understood in the context of the contemporary malaise of politics, which is being felt across the democratic world.

by Jonathan Bright 27/08/2015

If elections were invented today, they would probably be referred to as “crowdsourcing the government.” First coined in a 2006 issue of Wired magazine (Howe, 2006), the term crowdsourcing has come to be applied loosely to a wide variety of situations where ideas, opinions, labor or something else is “sourced” in from a potentially large group of people. Whilst most commonly applied in business contexts, there is an increasing amount of buzz around applying crowdsourcing techniques in government and policy contexts as well (Brabham, 2013). Though there is nothing qualitatively new about involving more people in government and policy processes, digital technologies in principle make it possible to increase the quantity of such involvement dramatically, by lowering the costs of participation (Margetts et al., 2015) and making it possible to tap into people’s free time (Shirky, 2010). This difference in quantity is arguably great enough to obtain a quality of its own. We can thus be justified in using the term “crowdsourcing for public policy and government” to refer to new digitally enabled ways of involving people in any aspect of democratic politics and government, not replacing but rather augmenting more traditional participation routes such as elections and referendums. In this editorial, we will briefly highlight some of the key emerging issues in research on crowdsourcing for public policy and government. Our entry point into the discussion is a collection of research papers first presented at the Internet, Politics & Policy 2014 (IPP2014) conference organised by the Oxford Internet Institute (University of Oxford) and the Policy & Internet journal. The theme of this very successful conference—our third since the founding of the journal—was “crowdsourcing for politics and policy.” Out of almost 80 papers presented at the conference in September last year, 14 of the best have now been published as peer-reviewed articles in this journal, including five in this issue. A further handful of papers from the conference focusing on labor…

Politics & Government, Social Data Science

How big data is breathing new life into the smart cities concept

by Jonathan Bright 23/07/2015

If all the cars have GPS devices, all the people have mobile phones, and all opinions are expressed on social media, then do we really need the city to be smart at all?

by Jonathan Bright 23/07/2015

“Big data” is a growing area of interest for public policy makers: for example, it was highlighted in UK Chancellor George Osborne’s recent budget speech as a major means of improving efficiency in public service delivery. While big data can apply to government at every level, the majority of innovation is currently being driven by local government, especially cities, who perhaps have greater flexibility and room to experiment and who are constantly on a drive to improve service delivery without increasing budgets. Work on big data for cities is increasingly incorporated under the rubric of “smart cities”. The smart city is an old(ish) idea: give urban policymakers real time information on a whole variety of indicators about their city (from traffic and pollution to park usage and waste bin collection) and they will be able to improve decision making and optimise service delivery. But the initial vision, which mostly centred around adding sensors and RFID tags to objects around the city so that they would be able to communicate, has thus far remained unrealised (big up front investment needs and the requirements of IPv6 are perhaps the most obvious reasons for this). The rise of big data—large, heterogeneous datasets generated by the increasing digitisation of social life—has however breathed new life into the smart cities concept. If all the cars have GPS devices, all the people have mobile phones, and all opinions are expressed on social media, then do we really need the city to be smart at all? Instead, policymakers can simply extract what they need from a sea of data which is already around them. And indeed, data from mobile phone operators has already been used for traffic optimisation, Oyster card data has been used to plan London Underground service interruptions, sewage data has been used to estimate population levels, the examples go on. However, at the moment these examples remain largely anecdotal, driven forward by a few…

Politics & Government

The life and death of political news: using online data to measure the impact of the audience agenda

by Jonathan Bright 09/09/2014

Editors must now decide not only what to publish and where, but how long it should remain prominent and visible to the audience on the front page of the news website.

by Jonathan Bright 09/09/2014

Image of the Telegraph's state of the art "hub and spoke" newsroom layout by David Sim.

The political agenda has always been shaped by what the news media decide to publish—through their ability to broadcast to large, loyal audiences in a sustained manner, news editors have the ability to shape ‘political reality’ by deciding what is important to report. Traditionally, journalists pass to their editors from a pool of potential stories; editors then choose which stories to publish. However, with the increasing importance of online news, editors must now decide not only what to publish and where, but how long it should remain prominent and visible to the audience on the front page of the news website. The question of how much influence the audience has in these decisions has always been ambiguous. While in theory we might expect journalists to be attentive to readers, journalism has also been characterised as a profession with a “deliberate…ignorance of audience wants” (Anderson, 2011b). This ‘anti-populism’ is still often portrayed as an important journalistic virtue, in the context of telling people what they need to hear, rather than what they want to hear. Recently, however, attention has been turning to the potential impact that online audience metrics are having on journalism’s “deliberate ignorance”. Online publishing provides a huge amount of information to editors about visitor numbers, visit frequency, and what visitors choose to read and how long they spend reading it. Online editors now have detailed information about what articles are popular almost as soon as they are published, with these statistics frequently displayed prominently in the newsroom. The rise of audience metrics has created concern both within the journalistic profession and academia, as part of a broader set of concerns about the way journalism is changing online. Many have expressed concern about a ‘culture of click’, whereby important but unexciting stories make way for more attention grabbing pieces, and editorial judgments are overridden by traffic statistics. At a time when media business models are under great strain, the…