Archive | April, 2016

Taking Stock



In this post for The Person in the (Big) Data edition of EM, we hear from Giorgia Aiello @giorgishka who
demonstrates the ways in which she used both digital and traditional methods to explore the people and practices that characterise the stock photography industry. Giorgia’s stories of photographers attempting to game the algorithms that determine which photographs will come out on top in a search for cheese are compelling and memorable, and they just show how important it is to develop an expanded idea of just what ‘data’ is constituted by, even if the dominant discourse is more limited. 

Image banks like Getty Images and Shutterstock that sell ready-to-use ‘stock’ photographs online have become the visual backbone of advertising, branding, publishing, and journalism. Also, daily exposure to stock images has increased exponentially with the rise of social networking and the generic visuals used in lifestyle articles and ‘clickbait’ posts. The stock imagery business has become a global industry through recent developments in e-commerce, copyright and social media (Glückler & Panitz, 2013).

However, stock images are most often overlooked rather than looked at—both by ‘ordinary’ people in the contexts of their everyday lives and by scholars, who have rarely taken an interest in this industry and genre in its own right. There are some notable exceptions, dating back to the ‘pre-Internet’ era of stock photography, like Paul Frosh’s work on the ‘visual content industry’ in the early 2000s or David Machin’s critical analysis of stock imagery as the ‘world’s visual language’ (Frosh, 2003; Machin, 2004). As a whole, and compared to other media and communication industries, research on online image banks and digital stock imagery is virtually uncharted territory.

Why, then, should stock images be ascribed any significance or power since people do not particularly pay attention to them? Stock images are not only the ‘wallpaper’ of consumer culture (Frosh, 2003 and 2013); they are also central to the ambient image environment that defines our visual world, which is now increasingly digital and global while also remaining very much analogue and local (just think of your own encounters with such imagery at your bank branch, at your dentist or beauty salon, or on billboards in city streets). Pre-produced images are the raw material for the world’s visual media.Read More… Taking Stock

Democratic Reflection: Evaluating Real-Time Citizen Responses to Media Content



What has always impressed me about this next method for ‘The Person in the (Big) Data‘ series is the way in which research participants were able to develop their own ideals for democratic citizenship that are then used to evaluate politicians. Giles Moss discusses the evolution of the app through its various iterations and highlights the value of the data developed out of its application for further research. This grounded, value-driven application is an inspiration for people-centred research and we look forward from more of the same from Giles and the team he worked with on this!

Democratic Reflection is a web app that measures the real-time responses of audiences to media content. The app was developed by a team of researchers from the Open University and the University of Leeds in the UK, as part of a research project funded by the EPSRC, to explore how citizens respond to and evaluate televised election debates (Coleman, Buckingham Shum, De Liddo, Moss, Plüss & Wilson 2014).[1] Accessing the web app via a second screen, research participants are asked to watch live television programming and use the app to evaluate the programme by selecting from a range of twenty predefined statements. The statements are designed to capture key capabilities of democratic citizenship, allowing us to analyse how viewers evaluate media content in relation to their needs as democratic citizens rather than just media consumers. In this post, I describe how we developed Democratic Reflection and what we hope to learn from the data the app generates.

Of course, we’re not the first researchers to develop a technology to measure real-time audience responses to media content. As far back as the 1930s, Paul Lazerfield and Frank Stanton developed an instrument called the Lazarsfeld-Stanton Program Analyzer, where research participants could indicate whether they liked or disliked media content and their inputs would be recorded in real time (Levy 1982). More sophisticated variants of the Program Analyzer followed. The Ontorio Educational Communication Authority and Children’s Television Workshop created a ‘Program Evaluation Analysis Computer’, which had sixteen buttons with labels that could be altered to include new measures, and the RD Percy Company of Seattle developed VOXBOX, which allowed viewers to respond to content by indicating whether they thought it was ‘Funny’, ‘Unbelievable’, and so on (Levy 1982: 36-37). More recently, Boydstun, Glazier, Pietryka, & Resnik (2014) developed a mobile app to capture real-time responses of citizens to the first US presidential debate in 2012, offering viewers four responses: ‘Agree’, ‘Disagree’, ‘Spin’, and ‘Dodge’.

Democratic Reflection fits into this tradition of real-time response to media content, but it focuses on analysing how viewers evaluate televised election debates in terms of their communicative needs as democratic citizens. In other words, we designed the app not just to explore whether people liked or disliked what they were watching or agreed or disagreed with it, but how media content related to their more fundamental capabilities as democratic citizens. Our first task, therefore, was to identify the democratic capabilities that media content and more specifically televised election debates could affect. Read More… Democratic Reflection: Evaluating Real-Time Citizen Responses to Media Content

Algorithmic Intelligence? Reconstructing Citizenship through Digital Methods



Screen Shot 2016-04-12 at 7.56.00 AMIn the next post for ‘The Person in the (Big) Data‘ edition, Chris Birchall @birchallchris talks us through a variety of methods – big, small and mixed – that he used to study citizenship in the UK. Using some of the dominant tools for studying large data sources in one part of the study, Chris realised that the tools used had a significant impact on what can be (and is being) discovered and that this is quite different from the findings reached by deeper, mixed methods analysis. In this post, Chris asks important questions about whether big data research tools are creating some the conditions of citizenship today and what, exactly, deeper, more nuanced analysis can tell us.

People talk about politics online in many different ways and for many different purposes. The way that researchers analyse and understand such conversation can influence the way that we depict public political opinion and citizenship. In two recent projects I investigated the nature of this conversation and the forces that influence it, as well as the networks, spaces and resources that link that talk to political action. In doing so, I encountered a methodological rift in which careful, manual, time consuming approaches produce different types of conclusions from the big data driven approaches that are widespread in the commercial social media analytics industry. Both of these approaches could be framed as an illustration of human behaviour on the internet, but their differences show that the way that we embrace big data or digital methods influences the understanding of digital publics and citizenship that we gain from the translation of mass online data.

My recently submitted PhD study investigated online public political conversation in the UK. Drawing on the work of previous scholars who have focussed on the deliberative online public sphere (such as Coleman and Gotze, 2001; Coleman and Moss, 2012; Mutz, 2006; Wright and Street, 2007; Graham, 2012), the study acknowledged the importance of interpersonal exchange between participants and exposure to diverse and opposing viewpoints in the formation of preferences and informed opinion. My initial motivation was to ask how interface design might influence people as they talk about politics in online spaces, but this required an examination of the more human, less technologically determinate factors that are also, and often more significantly, involved in political expression.

Over the course of the study it became obvious that the methodology used to investigate these concepts influences the insight obtained; something that many researchers have discussed in the context of digital methods within social science (Baym, 2013; Boyd and Crawford, 2012; Clough et al., 2015; Gitelman and Jackson, 2013; Kitchin and Lauriault, 2014; Kitchin, 2014; Manovich, 2011; Van Dijck, 2014). Technologically mediated questions can be answered through technology-centric methods to give technologically focussed answers, while questions involving human nature, motivation and interaction can be answered by qualitative, human-centred methods in order to provide human-centred answers. These approaches represent the divide between the large scale, quantitative analysis of big data methods and small scale qualitative approaches. In order to address this issue, I employed a methodology which was designed to combine these approaches through directed iterations of analysis that was initially large scale and quantitative, but increasingly small scale and qualitative.Read More… Algorithmic Intelligence? Reconstructing Citizenship through Digital Methods

Thinking with selfies


Kath Albury @KathAlbury
continues our edition of ‘The Person in the (Big) Data‘ by talking about her research into young people and sexting. Instead of educating those who worked with young people about social media and the digital, Kath developed an innovative Selfie Workshop with colleagues where she got participants to produce and reflect on their own selfies through the lens of introductory media theory. Instead of telling educators about sexting and social media representation, Kath facilitated an experience in which they would be directly involved. This kind of embodied learning is a wonderful way of generating new data about the social implications of mediation and offers the opportunity to engage directly to empower the community under study. 

Having undertaken a range of research investigations into ‘hot button’ issues such as Australian pornography producers and consumers, young people’s use of social media for sexual health informationyoung people’s responses to sexting, and selfie cultures, I am regularly invited to address sexual health promotion professionals (including clinical staff and teachers) seeking to better understand ‘what media does to young people’.

In the process, I have become increasing concerned that while online and mobile media practices are now ubiquitous (if not universal) elements of young Australians’ everyday sexual cultures, many sexuality education and health promotion professionals seem to have had little (or no) access to foundational training in media and communications technologies and practices.

Consequently, the Rethinking Media and Sexuality Education project sought to investigate the desirability and utility of providing sexuality educators and health promotion professionals with an introduction to the theoretical and methodological frameworks underpinning my research on media and sexuality.

Rather than discussing young people’s media practices directly, I shared some frameworks for thinking critically about media, gender and sexuality without seeking to quantify ‘impact’ or ‘effects’, and invited participation in a series of exercises adapted from the Selfie Course, with the aim of offering a prototype toolkit that might be applied across different professional settings and contexts.

How do selfies communicate a desire for intimacy? Participants in the Selfie Workshop are tasked with creating selfies for different audiences and contexts. (Pic used with permission from creator.)

The workshop introduced participants to a range of media theories (including Stuart Hall’s ‘encoding/decoding’ model ), followed by hands-on exercises drawn from the Selfie Course, particularly the Sexuality, dating and gender module, which I co-authored with colleagues Fatima Aziz and Magdalena Olszanowski. In the context of the Rethinking Media workshop, I briefly acknowledged the stereotypical ‘duckface selfie’, then moved on to introduce other selfie genres that were clearly read as an expression of ‘identity’, without revealing the photographer’s face. These the pelfie (a pet selfie), a range of body part selfies (such as the foot selfie, aka felfie), and the shelfie – a self-portrait featuring the contents of the photographer’s bookshelf.

The first activity was adapted from ‘The Faceless Selfie’ which my Selfie Researcher Network colleagues and I described as an exercise exploring the ways that “people navigate the ubiquity of online surveillance while simultaneously wishing to connect with others on social media sites”. This activity invites participants to use their own mobile phones to create a selfie that their friends or family would definitely recognise as them, without showing their faces.Read More… Thinking with selfies