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A Methodology for Mapping Instagram Hashtags
At this week’s Digital Humanities Australasia 2014 conference in Perth, Tim Highfield and I presented the first paper from a new project looking a visual social media, with a particular focus on Instagram. The slides and abstract are below (sadly with Slideshare discontinuing screencasts, I’m not sure if I’ll be adding audio to presentations again):
Social media platforms for content-sharing, information diffusion, and publishing thoughts and opinions have been the subject of a wide range of studies examining the formation of different publics, politics and media to health and crisis communication. For various reasons, some platforms are more widely-represented in research to date than others, particularly when examining large-scale activity captured through automated processes, or datasets reflecting the wider trend towards ‘big data’. Facebook, for instance, as a closed platform with different privacy settings available for its users, has not been subject to the same extensive quantitative and mixed-methods studies as other social media, such as Twitter. Indeed, Twitter serves as a leading example for the creation of methods for studying social media activity across myriad contexts: the strict character limit for tweets and the common functions of hashtags, replies, and retweets, as well as the more public nature of posting on Twitter, mean that the same processes can be used to track and analyse data collected through the Twitter API, despite covering very different subjects, languages, and contexts (see, for instance, Bruns, Burgess, Crawford, & Shaw, 2012; Moe & Larsson, 2013; Papacharissi & de Fatima Oliveira, 2012)
Building on the research carried out into Twitter, this paper outlines the development of a project which uses similar methods to study uses and activity on through the image-sharing platform Instagram. While the content of the two social media platforms is dissimilar – short textual comments versus images and video – there are significant architectural parallels which encourage the extension of analytical methods from one platform to another. The importance of tagging on Instagram, for instance, has conceptual and practical links to the hashtags employed on Twitter (and other social media platforms), with tags serving as markers for the main subjects, ideas, events, locations, or emotions featured in tweets and images alike. The Instagram API allows queries around user-specified tags, providing extensive information about relevant images and videos, similar to the results provided by the Twitter API for searches around particular hashtags or keywords. For Instagram, though, the information provided is more detailed than with Twitter, allowing the analysis of collected data to incorporate several different dimensions; for example, the information about the tagged images returned through the Instagram API will allow us to examine patterns of use around publishing activity (time of day, day of the week), types of content (image or video), filters used, and locations specified around these particular terms. More complex data also leads to more complex issues; for example, as Instagram photos can accrue comments over a long period, just capturing metadata for an image when it is first available may lack the full context information and scheduled revisiting of images may be necessary to capture the conversation and impact of an Instagram photo in terms of comments, likes and so forth.
This is an exploratory study, developing and introducing methods to track and analyse Instagram data; it builds upon the methods, tools, and scripts used by Bruns and Burgess (2010, 2011) in their large-scale analysis of Twitter datasets. These processes allow for the filtering of the collected data based on time and keywords, and for additional analytics around time intervals and overall user contributions. Such tools allow us to identify quantitative patterns within the captured, large-scale datasets, which are then supported by qualitative examinations of filtered datasets.
References
Bruns, A., & Burgess, J. (2010). Mapping Online Publics. Retrieved from http://mappingonlinepublics.net
Bruns, A., & Burgess, J. (2011, June 22). Gawk scripts for Twitter processing. Mapping Online Publics. Retrieved from http://mappingonlinepublics.net/resources/
Bruns, A., Burgess, J., Crawford, K., & Shaw, F. (2012). #qldfloods and @ QPSMedia: Crisis Communication on Twitter in the 2011 South East Queensland Floods. Brisbane. Retrieved from http://cci.edu.au/floodsreport.pdf
Moe, H., & Larsson, A. O. (2013). Untangling a Complex Media System. Information, Communication & Society, 16(5), 775–794. doi:10.1080/1369118X.2013.783607
Papacharissi, Z., & de Fatima Oliveira, M. (2012). Affective News and Networked Publics: The Rhythms of News Storytelling on #Egypt. Journal of Communication, 62, 266–282. doi:10.1111/j.1460-2466.2012.01630.x
Captured at Birth? Intimate Surveillance and Digital Legacies
At the end of January 2014 I was delighted to participate in the Surveillance, Copyright, Privacy: The end of the open internet conference held at the University of Otago in New Zealand. It was an inspiring three days looking critically at the way privacy and surveillance are increasingly at war in contemporary culture, which the eternal bugbear of copyright continues to look large. For a sense of the conference, Rosie Overell has collated the tweets from the event in four Storify collections: day one; morning of day 2; afternoon of day 2; and day 3.
The paper I presented was entitled ‘Captured at Birth? Intimate Surveillance and Digital Legacies’. Here’s the slides and abstract:
From social media to CCTV cameras, surveillance practices have been largely normalised in contemporary cultures. While sousveillance – surveillance and self-surveillance by everyday individuals – is often situated as a viable means of subverting and making visible surveillance practices, this is premised on those being surveyed having sufficient agency to actively participate in escaping or re-directing an undesired gaze (Albrechtslund, 2008; Fernback, 2013; Mann, Nolan, & Wellman, 2002). This paper, however, considers the challenges that come with what might be termed intimate surveillance: the processes of recording, storing, manipulating and sharing information, images, video and other material gathered by loved ones, family members and close friends. Rather than considering the complex negotiations often needed between consenting adults in terms of what material can, and should, be shared about each other, this paper focuses on the unintended digital legacies created about young people, often without their consent. As Deborah Upton (2013, p. 42) has argued, for example, posting first ultrasound photographs on social media has become a ritualised and everyday part of process of visualising and sharing the unborn. For many young people, their – often publicly shared – digital legacy begins before birth. Along a similar line, a child’s early years can often be captured and shared in a variety of ways, across a range of platforms, in text, images and video. The argument put forward is not that such practices are intrinsically wrong, or wrong at all. Rather, the core issue is that so many of the discussions about privacy and surveillance put forward in recent years presume that those under surveillance have sufficient agency to at least try and do something about it. When parents and others intimately survey their children and share that material – almost always with the very best intentions – they often do so without any explicit consideration of the privacy, rights or (likely unintended) digital legacy such practices create. A legacy which young people will have to, at some point, wrestle with, especially in a digital landscape increasingly driven by ‘real names’ policies (Zoonen, 2013). Inverting the overused media moral panic about young people’s sharing practices on social media, this paper argues that young people should be more concerned about the quite possibly inescapable legacy their parents’ documenting and sharing practices will create. Ensuring that intimate surveillance is an informed practice, better educational resources and social media literacy practices are needed for new parents and others responsible for managing the digital legacies of others.
References
Albrechtslund, A. (2008). Online Social Networking as Participatory Surveillance. First Monday, 13(3). Retrieved from http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/view/2142/1949
Fernback, J. (2013). Sousveillance: Communities of resistance to the surveillance environment. Telematics and Informatics, 30(1), 11–21. doi:10.1016/j.tele.2012.03.003
Lupton, D. (2013). The Social Worlds of the Unborn. Basingstoke: Palgrave MacMillan.
Mann, S., Nolan, J., & Wellman, B. (2002). Sousveillance: Inventing and Using Wearable Computing Devices for Data Collection in Surveillance Environments. Surveillance & Society, 1(3), 331–355.
Zoonen, L. van. (2013). From identity to identification: fixating the fragmented self. Media, Culture & Society, 35(1), 44–51. doi:10.1177/0163443712464557
For me the trip to Dunedin had the added bonus of spending some time visiting family and reacquainting myself after far too long away with the beautiful city I was born in.
Birth, Death and Facebook
Last week, as the inaugural paper in CCAT’s new seminar series Adventures in Culture in Technology (ACAT), I presented a more in depth, although still in progress, talk based on a paper I’m finishing on Facebook and the questions of birth and death. Here’s the slides along with recorded audio if you’re interested:
The talk abstract: While social media services including the behemoth Facebook with over a billion users, promote and encourage the ongoing creation, maintenance and performance of an active online self, complete with agency, every act of communication is also recorded. Indeed, the recordings made by other people about ourselves can reveal more than we actively and consciously chose to reveal about ourselves. The way people influence the identity and legacy of others is particularly pronounced when we consider birth – how parents and others ‘create’ an individual online before that young person has any identity in their online identity construction – and at death, when a person ceases to have agency altogether and becomes exclusively a recorded and encoded data construct. This seminar explores the limits and implications for agency, identity and data personhood in the age of Facebook.
Visualising Locative Media with Foursquare’s Time Machine
I’m currently working on a chapter for the forthcoming Locative Media edited collection; the piece I’m co-writing with Clare Lloyd examines some of the pedagogical strategies that have arisen to better inform users about the data that they generate whilst using locative media in various forms (from explicit check-ins with Foursquare to less obvious locative metadata on photographs, tweets and so forth). We’ve been looking at several tools and services like PleaseRobMe.com, I Can Stalk U and Creepy which visualise the often hidden layer locative media layers of mobile devices and services.
Given this context, I was fascinated to see Foursquare’s release of their ‘Time Machine’ (deployed as a promotion for Samsung’s S4) which creates an animation and eventual infographic visualising the a user’s entire Foursquare check-in history. Since I’m very conscious of where I do and don’t use Foursquare, I was fascinated to see what sort of picture of my movements this builds. The grouping of check-ins in Perth (where I live) and the places I’ve travelled to for conferences (which is the main time I use Foursquare) was very smooth, and made my own digitised journey through the world look like a personalised network diagram. The eventual infographic produced is fairly banal, but does crunch your own Foursquare numbers. I’ve embedded mine below.
While Foursquare users are probably amongst the most aware locative media users and generators of locative data, it’s still fascinating to see what a rich and robust picture these individual points of data look like when aggregated. In line with the writing I’m doing, I can’t help wonder how people would respond to a similar sort of visualisation based on their smartphone photos or Facebook posts or some other service which is less explicit or transparent in the way locative metadata is produced and stored.
Digital Culture Links: May 21st
Links through to May 21st:
- Sensis Yellow Social Media Report 2013 [PDF] – The new Sensis Yellow Social Media Report is out (based on a survey of 937 Australians in March and April 2013), showing widespread social media use, with growth in mobile and second screen uses:
* 95% of AUstralian social media users use Facebook
* The typical Australian spends 7 hrs/wk on Facebook
* 67% of Australians access social sites on a smartphone
* 42% of Australians use social media while watching TV - A better, brighter Flickr [Flickr Blog] – Yahoo have majorly redesigned Flickr, giving new free (ad-supported) accounts 1Tb of storage, which is an awful lot of photos. The Android app is now almost identitcal to the iOS app, but the new aesthetics of the web-based version are a big change, looking more and more like every other photo-sharing service around today. Quite a few long-term Flickr users (of which I am one) have voiced a range of concerns about the design changes. Also, what this redesign means for people who’ve already paid for Pro accounts is deeply unclear on the main Flickr pages. (The Twitter account seems to suggest nothing changes.)
- Yahoo! to Acquire Tumblr / Yahoo [Yahoo News Centre] – Yahoo buys Tumblr for $1.1 billion and, in their words, “promises not to screw it up”. A clever buy for Yahoo, but it’ll be hard to integrate the rebellious/youth Tumblr userbase into the Yahoo brand.
- Introducing Photos of You [Instagram Blog] – Just in case you momentarily forgot that Facebook owns Instagram, the photo-sharing service has just added the ability to tag photos (remarkably similar to Facebook’s tagging function). Looks like Instagram needs a better map of your personal networks before they can harness it commercially.
- Follow the audience… [YouTube Blog] – May 2013 and YouTube users “are watching more than 6 billion hours of video each month on YouTube; almost an hour a month for every person on Earth and 50 percent more this year than last.”
The Social Media Contradiction: Data Mining and Digital Death
I’ve got a new article in the most recent issue of the M/C Journal entitled ‘The Social Media Contradiction: Data Mining and Digital Death’. Here’s the abstract:
Many social media tools and services are free to use. This fact often leads users to the mistaken presumption that the associated data generated whilst utilising these tools and services is without value. Users often focus on the social and presumed ephemeral nature of communication – imagining something that happens but then has no further record or value, akin to a telephone call – while corporations behind these tools tend to focus on the media side, the lasting value of these traces which can be combined, mined and analysed for new insight and revenue generation. This paper seeks to explore this social media contradiction in two ways. Firstly, a cursory examination of Google and Facebook will demonstrate how data mining and analysis are core practices for these corporate giants, central to their functioning, development and expansion. Yet the public rhetoric of these companies is not about the exchange of personal information for services, but rather the more utopian notions of organising the world’s information, or bringing everyone together through sharing.
The second section of this paper examines some of the core ramifications of death in terms of social media, asking what happens when a user suddenly exists only as recorded media fragments, at least in digital terms. Death, at first glance, renders users (or post-users) without agency or, implicitly, value to companies which data-mine ongoing social practices. Yet the emergence of digital legacy management highlights the value of the data generated using social media, a value which persists even after death. The question of a digital estate thus illustrates the cumulative value of social media as media, even on an individual level. The ways Facebook and Google approach digital death are examined, demonstrating policies which enshrine the agency and rights of living users, but become far less coherent posthumously. Finally, along with digital legacy management, I will examine the potential for posthumous digital legacies which may, in some macabre ways, actually reanimate some aspects of a deceased user’s presence, such as the Lives On service which touts the slogan “when your heart stops beating, you’ll keep tweeting”. Cumulatively, mapping digital legacy management by large online corporations, and the affordances of more focussed services dealing with digital death, illustrates the value of data generated by social media users, and the continued importance of the data even beyond the grave.
Read the rest at the M/C Journal (open access).
Incidentally, yes, one of the points in this article is already out of date as last month Google quietly launched their Inactive Account Manager. While far from perfect, this Inactive Account manager gives Google users more control over what happens to their Google stored assets after they pass away (well, actually, after they don’t log in for a specified period of time). It is, however, far from perfect.
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