New commentary from me in today’s The Conversation:

When authenticity and advertising collide on social media

Tama Leaver, Curtin University

Be true to yourself! Embrace the real you! Fundamental philosophical imperatives or contrived marketing slogans?

The answer, of course, is both. And 19-year-old Instagram model Essena O’Neill’s very public rejection of the inauthentic nature of social media last week can been read through both lenses.

On the one hand, O’Neill deleted her heavily trafficked Instagram, YouTube and Tumblr accounts, and re-directed her audience to her new blog decrying the artificiality of social media life. She was embraced by many for revealing the inner workings of a poorly understood social media marketplace. Deleting accounts with more half a million followers certainly does make a statement.

On the other hand, O’Neill’s actions have also been interpreted as a rebranding effort, shifting away from the world of modelling toward a new online identity as a vegan eco-warrior.

Influencing the influencers

O’Neill was – and largely remains – what is referred to by marketers as an “influencer” or by some academics as a “microcelebrity”.

Given the large numbers of followers, they are very attractive platforms for brands and marketers wanting to reach these “organic” social media audiences. Yet, while these social media channels often depict idyllic lives, O’Neill’s dramatic revelations have raised questions about the authenticity of many influencers.

Or, more specifically, questions about exactly what sort of money is changing hands, and how visible sponsored and paid posts ought to be on social media.

Clashes between authenticity and commerce have a long history on social media. A notable example occurred in 2009 when Nestlé courted influential “mommy bloggers”, effectively dividing the community between those happy to be flown to a Nestlé retreat and those who argued Nestlé’s history of unethical business practices in relation to breastfeeding were unforgivable.

More recently, influential YouTube star and fashion blogger Zoe “Zoella” Sugg faced a backlash following the revelations that her best-selling debut novel, Girl Online, was written at least in part by a ghostwriter.

Anthropologist and social media researcher Crystal Abidin has extensively studied and documented Singaporean influencers, noting a range of different practices, from explicit tags to implicit mentioning of brands, to indicate paid or sponsored posts.

Recognising these various tags and indicators requires a level of Instagram literacy that regular viewers will likely develop, but casual audiences could easily miss. Indeed, as Abidin and Mart Ots have argued, this lack of transparent standards can be understood as “the influencer’s dilemma”.

As Singaporean influencers have been around for a decade, some have aged sufficiently to shift from their own sponsored posts to endorsements featuring their children, becoming what Abidin describes as micro-microcelebrities.

Australia also has its own infant influencers, the most visible being PR CEO Roxy Jacenko’s daughter, four year old Instagram star Pixie Curtis. As a second generation influencers emerge, clear social norms about sponsorship and advertising transparency on Instagram become more pressing.

Leveraging authenticity

Australian newly launched marketing company Tribe has positioned itself as a broker between influencers – “someone with 5000+ real followers” on Facebook, Twitter or Instagram – and brands.

As Tribe notes, the ACCC does not currently require individuals on social media to reveal paid posts. However, it does recommend influencers add #spon to sponsored posts to flag identify paid content.

Tribe influencer marketing in action. Tribe Group

The difference between a recommendation and a rule aside, while a quick search reveals some 47,000 Instagram images tagged with #spon, many of these are not sponsored posts.

Top images tagged #spon on Instagram, 9 November 2015. Instagram

Of the top #spon tagged posts on Instagram yesterday (9 November), they feature influencers spruiking tea, videogames, resorts, beer and a mobile service provider along with two pets sponsored by a dog show and, as seems fitting, a dog food company.

An explicit marker like #spon would at least make sponsored posts identifiable, but no such norm currently exists, and even Tribe only “strongly recommends” rather than mandates its use.

See through

In a post ironically titled “How To Make $$$ on Social Media”, Essena O’Neill notes that she was charging A$1,000 to feature a product on her Instagram feed, a fact she did not disclose until her recent rejection of her social media modelling past.

O’Neill’s own authenticity might not be helped by the fact that she took to Vimeo – another social media platform – and her own blog, to denounce social media.

This could be read as a clear reminder that social media isn’t inherently morally charged: the value of communication platforms depends in large part on what’s being communicated.

Moreover, as O’Neill’s actions have inspired other Instagram users and influencers to add “honest” captions about the constructedness of their images, if nothing else O’Neill has provoked a very teachable moment, potentially increasing the media literacy of many social media users.

Traditional media industries have long had regulations that ensure advertising and other content are clearly differentiated. While regulating social media is challenging, calling for social media influencers to self-regulate should not be.

Far from damaging their influence, such transparency may just add to what audiences perceive as their authenticity.

The Conversation

Tama Leaver, Senior Lecturer in Internet Studies, Curtin University

This article was originally published on The Conversation. Read the original article.

A slightly longer version of this piece, with the title I’d originally suggested – The Cost of Authenticity on Instagram – is available on Medium.

Print Friendly, PDF & Email

Yesterday, as part of the fantastic ‘Presence, Privacy and Pseudonymity ‘panel at Internet Research 15: Boundaries and Intersections in Daegu, South Korea, I presented an expanded and revised version of the paper first gave in Dunedin earlier this year. The paper has been retitled slightly as ‘Captured at Birth? Presence, Privacy and Intimate Surveillance’; the slides are available now:

If you’re interested, Axel Bruns did a great liveblog summary of the paper, and for the truly dedicated there is an mp3 audio copy of the talk. The paper itself is in the process of being written up and should be in full chapter form in a month or so; if you’d like to look over a full draft once it’s written up, just let me know.

Print Friendly, PDF & Email

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

Print Friendly, PDF & Email