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Youtube: Digital Scrapbooking in the 21st Century

New media has provided a multitude of engagement opportunities for fans and consumers of entertainment. Much of this can be owed to the affordances that technology allows both producers and consumers in making, distributing, accessing and engaging with content. These include the rise of participatory fandom (Shefrin, 2004) and the ability to use entertainment as self-formation (Burgess, 2009).

New media such as YouTube and Vine allow the audience to play a role as entertainers and take advantage of online methods of self-formation. Burgess (2009, 25) says there are increasingly “interpersonal, playful and identity-forming uses for information, communication technology.” Indeed, sites such as this have been used to platform many users to internet stardom. Jenna Marbles, Jamie Curry and Chris Crocker (of “Leave Britney Alone!” fame) have all enjoyed online success from their use of YouTube and have even been able to take advantage economically by gaining advertisement revenue from their high visitor count or even getting involved with offline promotional opportunities. Some scholars have correctly pointed out that this doesn’t always translate into true celebrity though and that YouTube could not be seen as a solid platform to achieving ongoing world-wide recognition. Indeed it is true that for the vast majority of people, bridging the gap is virtually impossible if you don’t have the support of pre-existing media outlets and organisations, such as Justin Bieber did when he was apparently discovered by Usher and marketing executive, Scooter Braun.

Burgess (2009) reminds us though that amateur videos are not necessarily aimed at achieving super stardom or even a fan base, they can be created social history and used to document lives. Indeed, participant uploads on sites such as Instagram, Vine and YouTube can even be described as a 21st century digital scrapbook of memories. The video sharing site Vine has recently gained more popularity as it showcases 6 second home made videos that can be broadcast to the world. Many of the uploaders will never achieve internet fame however that does not prevent millions from being uploaded everyday. Each video involve some level of planning, creativity and personal touch that combines to form the mix of “productive play, media consumption and cultural performance” that Burgess highlights as a semi-private space of cultural participation (2009: 18)

The abundance of creation methods that assist users to pre-produce, produce, circulate and consume makes the Big Brother formula of filming normal people go about daily activities seem old-hack. It is easy to see how new media affordances and the rise of online self-expression could have contributed to a waning interest in the Big Brother series. Video sharing sites allow users to have 100% control over their image and content production, and the level of exhibitionism or surveillance is controlled by participants themselves. The supposed ‘reality’ of the Big Brother set up is far surpassed by the seemingly endless supply of personal vlogs and content that can be accessed on YouTube or Vine at any given time.

Big Brother 2013 winner Tim in the diary room

YouTube user SHAYTARDS vlogs the birth of his baby

Online video outlets have provided a range of methods for self-expression. Whilst some have reached Internet stardom, it is still difficult to bridge the gap to fully-fledged celebrity. However many users upload regardless, so they can have an opportunity for meaningful identity building and creative online play, unlike the limited and inaccessible ‘broadcast reality’ of a show like Big Brother.

  References: 

Burgess, Jean and Joshua Green. 2009. “You Tube and the Mainstream Media.” In YouTube: Online Video and Participatory Culture edited by JeanBurgess, Joshua Green and Henry Jenkins, 15-37. Cambridge, MA: Polity Press  

Glenn Dyer. 2013. “Nine continues to tank, Big Brother beaten by thnews.” Crikey. August 7. Accessed April 1, 2014. http://www.crikey.com.au/2013/08/07/glenn-dyers-tv-ratings-nine-continues-to-tank-big-brother-beaten-by-the-news/

Sauter, Theresa, March 26, 2014. “Week 5 – New Media and Entertainment.” Accessed March 31, 2014. http://blackboard.qut.edu.au/

Shefrin, Elana. 2004. “Lord of the Rings, Star Wars, and Participatory Fandom: Mapping New Congruencies Between the Internet and Media Entertainment Culture.” Critical Studies in Media Communication 21 (3): 261-281.

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Big Data: Knows You Better Than You Do!

Before the boom of online engagement and Web 2.0, the natural method of data collection was through human input into records or computers. These days, any individual that participates online essentially creates their own data imprint; automatically recorded whenever they click on an ad, ‘like’ a Facebook page or enter a website. The ever-present role of the Internet in our everyday lives means data now grows by 2.5 quintillion bytes per day (Siegel, 2013, 2). The sum of this huge, growing resource can only properly be measured by what Siegal (2013, 3) describes as “machine learning”: the use of computers to quantify and process this data to develop new knowledge and capabilities, such as predictions. "Predictive Analytics" describes the method of using data mining to determine likely outcomes, which organisations use determine the likely outcome of their products and services. Examples include the prediction of mouse clicks for websites with pay per click advertisements (Siegal, 3), dating predictions for online sites such as Match.com; and the ability of companies such as Hewlett Packard (HP) to predict the chance of an employee’s 'flight risk’ (whether they will quit their job).

Our willingness to contribute data to companies like Facebook allow them to monitor personal usage and on-sell information to interested parties such as advertising agencies. Algorithms developed by Cambridge University and Microsoft allow Facebook to make predictions based on characteristics such as demoraphics, page likes, Facebook usage, location and language and purchasing activity (Cohen, 2014). This following video provides a really good simple explanation of the type of data Facebook mines and how.

Facebook advertisements and increasingly their ‘page suggestions’ (subtly weaved into News Feeds), are based on individual user characteristics. For example, both my housemates are females in their late twenties – their Facebook pages constantly include ads for weight loss products, bridal advertisements and dating websites with ‘single, faithful policemen’ in their local area: all products for which they would be classified as the target audience. I recently went kayaking and posted a status about it along with photos and ever since, I have received ads for kite surfing on the side of my home page.

Similarly, I recently changed by mobile data plan and ever since, there has been an advertisement for Vodaphone’s new data plan on the side of my page. It seems impossible Facebook could know the details of my phone contract, but perhaps the mere fact that I am on Facebook regularly means I am a good target audience for affordable data products.

Below is a snapshot of Facebook’s Data Use Policy. Whilst it is extremely simple and easy to read, it raises some questions like:

What does it actually mean that we own our data?

What legal avenues are available to enforce these rights?

Is there a way we can extract our data and move or save it elsewhere?

Policies such as this are helpful and important but often vague, and fail to give meaningful examples to users of what the actual consequences of their participation could be. Facebook has certainly faced criticised for this before.

For those that are concerned about the invasive accuracy of data mining and predictive analytics, one has to wonder whether it is that different from any sort of audience research. Television ratings and research have been used to sell audiences to advertisers for years. Classic methods of measurement include written viewing diaries and the people-meter (introduced in 1987), to track television consumption in the home (Sullivan, 2013). Both these methods rely on volunteer provision of information by participants. In many ways, data mining is not that different, except that it has extremely widespread participation and as a result, is conducted on a much grander scale. This can result in targeted, efficient advertising and information about products that consumers might actually enjoy or value.  

Whilst data mining is considered by many as a form of surveillance, it is important that participants educate themselves about how their data could be used, however companies such as Facebook must also ensure honest and transparent policy disclosure.

References:

Dara Kerr. 2013. "Facebook faces criticism over its privacy policy." CNET. September 5. Accessed May 12, 2014. http://www.cnet.com/au/news/facebook-faces-criticism-over-its-privacy-policy/ 

David Cohen. 2014. "Facebook Audience Insights gives marketers an overview of their potential audiences." Inside Facebook. May 8. Accessed May 12, 2014. http://www.insidefacebook.com/2014/05/08/facebook-audience-insights-gives-marketers-a-better-overview-of-their-potential-audiences/ 

Siegel, Eric. 2013. “Introduction – The Prediction Effect.” In Predictive Analytics, 1-16. Hoboken, NJ: John Wiley and Sons Inc.

Sullivan, John L. (2013), “Chapter 4: Media ratings and target marketing”, Media Audiences: Effects, Users, Institutions and Power, Los Angeles: Sage

Woodford, Darryl, April 24, 2014. “Week 9 – Big Data and Telemetrics.” Accessed May 13, 2014. http://blackboard.qut.edu.au/

DNews. 2013. “Your Facebook Likes Reveal Everything.” YouTube video, posted March 12. Accessed May 11, 2014. https://www.youtube.com/watch?v=3SNeQXWn3xk

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I <3 U: Expressing emotion and context online

Mediated communication describes the use of tools and technology to communicate and record information across time and space. In 2014, perhaps the most common form is Computer Mediated Communication (CMC) or “netspeak” (Crystal, 2006: 27). Not quite writing, not quite speech, CMC takes elements from both and also employs new techniques for us to engage with the world, each other and ourselves (Baym, 2010).

 Many researchers have claimed that the increase in CMC will eventually lead to overall impoverishment of communication, for example due to the decay of  the human language, the reclusive nature of the internet or the inadequacy of online interactions that fail to have verbal and non-verbal cues such as body language and rhythm of conversation. To the contrary, Nancy Baym argues that a “communication imperative” pushes us to use new media for interpersonal purposes and come up with creative ways to work around online barriers, rather then submit ourselves to a content- and emotion-less communication experience (2010).

 There are four obvious methods Internet users have created to add context to online social experiences which include emoticons, adapted language, hashtags and audio-visual cues. 

Emoticons can best be described as graphic signs used to indicate an emotional state. Two of their key uses are to:

a)    eliminate ambiguities, for example clarifying sarcasm; and

b)   build rapport, often in the workplace or with strangers of acquaintances in social media contexts.

Twitter recently acknowledged how important emoticons are to online communication and actually made their platform Emoji compatible.

Language adaptations are also incredibly common, particularly in mediums which require brevity, like mobile texting or Twitter. Abbreviations such as ‘lol’, symbols like <3 to depict a love heart, or use of caps lock can convey complex emotions in just a short word or phrase, instantly providing framework to online messages.

Hashtags play a key part in the searchability and identity of online users. They can be topical such as #auspol, or non-topical, such as emotive hashtags like #fail. Hashtags can increase visibility to posts, allow users to define how they want their photo or tweet to be interpreted, as well as determine the terms on which it will be accessed. This kind of categorisation can give rise to a feeling of community or network and connect users with likeminded people.

For example, a quick glance of the “paleo” hashtag on Instagram immediately brings up almost two million photos of food, recipes, selfies and personal stories related to the lifestyle practice.Similarly, the trending tag on Twitter is #coachella, which is a music festival currently on in California.

By including that tag in a tweet, Twitter users can immediately:

join the conversation

read and hear about audience reactions

get real time photos and videos from the event

refine their search by only looking at "news" articles

Even if you are solitary in your own home, this could hardly be described as reclusive behaviour when considering the ability to interact with millions is a mouse click away. Hashtags are a simple way of expressing what you want to talk about, and make it easy to find like-minded communities or topics that you’re interested in.

The final common method for adding context to CMC is the use of audio-visual cues such as uploading pictures on Facebook, sending a Snapchat or broadcasting a Vine. Probably the most prevalent technique, it is hard to argue that the Internet has caused us to be ‘disembodied’ when Facebook profile pictures follows users wherever they post, comment or chat. Skype is another obvious example that allows users to transcend the online barriers of time and space to fill their emotional needs and provide intimacy (Valentine, 2006). Whether it be parents skyping a child overseas, or perhaps a father skyping his family while he is away in combat, the audio-visual aspects allows physical bodies to become more visible and more spontaneity and instanteity to be achieved.

Despite the lack of traditional verbal and non-verbal cues, technology users have created new techniques convey social and emotional contexts online and engage with the world, each other and with themselves.. Much of this digital language depends on the mode used, the purpose, the norms of the group and the styles of participants offline (Baym, 2010: 63), however the more universal techniques discussed above are the most important in creating online connection and expression.

References

Baym, Nancy. 2010. “Ch 3: Communication in Digital Spaces.” In Personal Connections in the Digital Age, 50-70. Cambridge MA: Polity Press

Crystal, David. 2006. “Ch 2: The Medium of Netspeak.” In Language and the Internet. 2nd ed, 26-65. Cambridge: Cambridge University Press. 

Sauter, Theresa, April 03, 2014. “Week 6 – New Media Communication.” Accessed April 6, 2014. http://blackboard.qut.edu.au/

Valentine, Gill. (2006) ‘Globalizing Intimacy: The Role of Information and Communication Technologies in Maintaining and Creating Relationships’, Women’s Studies Quarterly 34(1/2): 365-394 

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Society's role in shaping our technological future.

Facebook, Twitter, smart phones, tablets, wifi – the list of new tools and technologies in the 21st century seems endless. However it is not merely platforms and devices that can be considered ‘new media’. A comprehensive definition also incorporates the social arrangements and contexts of our engagement with technology, and how they are incorporated into institutions, laws and society (Flew, 2014). 

With technology growing increasingly entangled, there is a tendency of the media and government to argue technologies are causal agents: directly impacting society and leaving us over-stimulated and permanently effected. However is it true to say society is hopelessly devoted to new invasive technologies? Or is our relationship with new media a little more complex?

The idea that technology can change and control us is referred to as technological determinism and has appeared throughout history at various points of technological advancement. Even Socrates decried the invention of the alphabet and written word as a threat to the oral tradition of Greek society (c 370 BCE).

Common examples of ongoing claims about technological determinism include:

Atlantic writer Nick Carr (2008) who argued that Google was shortening his attention span and making him stupid

That people will lose capacity for ‘deep reading’ and critical reflection as internet encourages rapid sampling of small bits of info (eg YouTube and Twitter): Nick Carr (2010)

That some video games are making young people increasingly violent eg correlations drawn when violent films or games were found in Martin Bryant (of the Port Arthur massacre) and other serial killers’ homes.

Nancy Baym, in her work Personal Connections in the Digital Age, argues these claims and similar are merely fuelled by moral panic that commonly occurs when “anxieties about issues are misplaced onto the use of new technology that is not yet understood”. An example is the common claim that more accessible porn and sexual content in television and advertising is causing the sexualisation of children and leads to greater gender inequality (Rush and La Nauze, 2006). However this is simply untrue - women experience higher levels of equality in 2014 then ever before, and there is currently the lowest rates of sexual crime in Australia’s history (McNair, 2013).

Moral panics about technological determinism are dangerous because they treat their subjects as susceptible to new technology and don’t take into account social contexts, new media uses and consumer experiences and interpretations (Gauntlett, 1998). 

Aside from the inaccuracy of moral panics it is also clear that in some cases we positively influence technology, by developing or altering products and devices to suit our needs. A classic example of this is the evolution of smartphones. Mobile phones were initially designed as merely communication devices, but now they fuel entertainment, participation and the construction of self-identity. A camera has even been incorporated on the front of all smartphones to assist with taking ‘selfies’ and video conferencing/‘Facetiming’. They allow us to be on social media anytime, anywhere, and accelerate existing trends such as growing participation in online communities.

However, it would be hard to deny, mobiles also encourage us to engage in constant phone checking and status updating that would not otherwise be possible. It is clear that technology allows us certain affordances in relation our new media usage, which society takes advantage of in shaping social, and often economic, needs (Baym, 2010). 

As Douglas so eloquently put it in his 2004 work, “Machines don’t make history themselves, but they can help make different kinds of histories and different kinds of people” (at 21).

  Bibliography

Baym, Nancy. 2010. “Ch 2: Making New Media Make Sense.” In Personal Connections in the Digital Age, 22-45. Cambridge MA: Polity Press 

Flew, Terry. 2014. “Ch 1: Introduction to New Media.” In New Media. 4th ed, 1 - 17 Melbourne: Oxford University Press

Gauntlett, David. (1998) “Ten Things Wrong with the ‘Effects Model’,” in R. Dickinson, R. Harindranath and O. Linne (eds) Approaches to Audiences: A Reader, London: Arnold, pp. 120-145.

McNair, Brian. (2013) Chapter 5: ‘What Has Pornography Ever Done for Us?: The Argument from Evidence’, in Porno? Chic! How Pornography Changed the World and Made it a Better Place, London: Routledge. pp. 79-90.

Rush, Emma and La Nauze, Andrea. (2006) Corporate Paedophilia Report: Sexualisation of children in Australia. The Australia Institute. Accessed March 9, 2014. http://www.tai.org.au/documents/dp_fulltext/DP90.pdf 

Sauter, Theresa. February 27, 2014a. “Week 1 – Introduction: What are “New” Media and where did they come from?” Accessed March 1, 2014.http://blackboard.qut.edu.au/ 

Sauter, Theresa, March 6, 2014b. “Week 2 – New Media and Society, New Media and Identity.” Accessed March 9, 2014. http://blackboard.qut.edu.au/