For many of us who have been impacted by the stay-at-home isolation conditions during this global pandemic, we have turned to new forms of social media entertainment for comfort.
However, for prime-time celebrities who rely heavily on their production teams to create world-class media experiences, the transition has not been so seamless. Instead, what we have seen is the rise of those online content producers who are native to social media platforms amass new audiences of interest.
I have been researching digital first personalities around the globe to understand how single person media productions have become the go-to media source for many individuals, especially in times of isolation.
Celebrities as YouTubers? ‘That’s Chat’
On 30 March 2020, YouTubers Colin and Samir published a video ‘Is this the end of Late Night?’. On the surface this video seemed to make light of the careers of late-night hosts such as Seth Meyers, Jimmy Fallon and Stephen Colbert. In reality, these LA based YouTube creators provide a stunning commentary on the vast difference of skill and expertise levels between native YouTubers and traditional prime time celebrities.
This difference becomes bleedingly obvious when a number of these traditional celebrities were forced to take their productions out of their ‘bright-light’ studios in New York and Los Angeles, and retreat to their private family homes.
While the hosts incorporated the inadequacies of their production design into their nightly comedy routine, for example Seth Meyers making jokes about his attic door which has become something of a regular ‘guest’, the deficiencies in production qualities began to show. Some channels went into hiatus for several days at time, interviews were plagued by poor quality internet connections, lighting was experimental and the technical issues often became obvious for the audiences of these loved programs.
This is not the case for YouTubers who continue to produce high-quality content.
Colin and Samir observe that YouTubers are equipped to not only create entertaining content, but also have the technical skills to write, shoot, edit, publish and distribute at a level far beyond our well-known traditional media celebrities.
‘Good Onya Champ’ – The rise of digital first personalities
I have written about this phenomenon as digital first personalities. Digital first personalities are individuals who produce digital content for maximum visibility by engaging social influencer publication strategies that appease platform algorithms. In other words, they are experts in ensuring their content is seen by large audiences across social media platforms by utilising their entertaining and technical production skills.
Nat’s What I Reckon is one example of online content producers that are rising in popularity on social media, based on their past abilities of interacting with their audiences. As a YouTuber and Instagrammer based in Sydney, he has recently amassed a large audience through his welcomed, no-frills isolation cooking segments. Nat has been posting videos on YouTube for several years, examining the Summer Nationals in Canberra, why cruise ships ‘are weird’, chilli eating competitions, and aliens in Roswell, USA. These videos had a steady audience of just under 10,000 views on average, but as the media hungry, COVID-19 isolated audience grew, Nat’s What I Reckon channel has grown into an almost overnight success story.
As a digital first personality, Nat has spent years not only developing his unique entertaining style, but has also sharpened his interview technique, camera skills, and audio production. Additionally, this digital first personality has honed his public relations skills by strengthening his audience across Instagram and distributing his work across several other social media platforms.
I also wanted to make special mention of Laura Clery, who even makes me laugh as I write her name here – a strong example of a digital first personality, although she does some fame from her previous YouTube life.
The End of the Late Show?
Probably not. But what we are witnessing here is a shift of audience attention away from the large-scale traditional media formats and a continued growth across social media platforms as isolated audiences change their viewing habits indefinitely.
This is a unique moment for online content producers who demonstrate key digital first personality skills. Using TikTok, the demand for content is much higher than what is produced, making this a space ideal for emerging digital first personalities to build their audiences and move from influencers towards native online content celebrities.
https://i1.wp.com/jonathonhutchinson.com.au/wp-content/uploads/2020/05/Nats_What_I_Reckon.jpeg?fit=720%2C482&ssl=1482720Jonathon HutchinsonJonathon Hutchinson2020-05-12 04:03:302020-05-12 04:03:39The rise of digital first personalities during COVID-19 isolation
We performed our academic FIFO (Fly In Fly Out – thanks for the insights here Jolynna) duties recently at the first University of Sydney and Hong Kong University symposium, expertly crafted by Professor Heather Horst and Dr Tom McDonald.
During the one day symposium, all researchers were asked to respond to the somewhat broad theme around the concepts of cross border media flows and social imaginaries – in thinking through these two areas, it is a lovely way to bring sociology and media studies (communication if you will) together:
Media of various forms, and the infrastructures and communities that are associated with them, have often been strongly determined by national boundaries. This is particularly the case in different countries dispersed across the Asia-Pacific region, where media organisations are often owned by government entities and/or large companies. Such media organisations also frequently have political or commercial roles that, arguably, make them less susceptible to the kinds of disruption that have been witnessed by their European and American counterparts in recent years. At the same time, the movement of people, goods, capital, information and ideas are undergoing shifts and intensifications, owing to broader geopolitical changes, state-led infrastructure projects and the aspirations of individuals and communities shaped by such regional transformations.
Against this context, media flows are being created, worked and reworked, facilitated by new infrastructures, imaginaries and understandings. These flows frequently cross, circumvent or come up against borders, both domestic and international. For instance, countries such as China and the US increasingly compete to export infrastructures across the region through the promotion of platforms, technologies and services. Online shopping, logistics, blockchain and fin-tech are fostering new cross-border flows of goods and money. Media content is increasingly consumed internationally, posing new opportunities and challenges for media companies, regulators and governments. Users and consumers of the media are also witnessing the reworking of their media environments because of these changes, and are adopting inventive responses to and adaptations of the media in return.
This symposium, and the planned journal special issue that will result from it, explores these changing circuits of media in the Asia Pacific region. We ask contributors to consider: How are media flows redefining understandings of borders? What kinds of novel communities are being created by cross-border media flows? What forms of social imaginaries accompany the emergence of new infrastructures from “outside”? How are boundaries and borders being made, unmade or remade within and across the Asia-Pacific region?
Personally, it was a unique opportunity to apply my recent thinking around digital intermediation to the concept of social imaginaries to understand how geopolitical borders are constructed, de-constructed and enforced and reimagined – there is no better place in the world than Hong Kong to get that sort of thinking on.
If you are interested in the research I have started in this space, you can access my presentation here:
But enough about me, the better work was all around! Here are some notes and reflections from the research presented:
IBM Watson to do the classifier for the woman filmed in The Girl in the Picture
What enables the production of survivors who have crossed the borders?
There is a close connection between the state and industry – building larger goals into the process
There are a number of agencies involved in this process
Leads to the ‘Imagineering’ of content – this is the link to the hologram
The industry in Hollywood has shifted to military content –
The emergence of the Silicon Beach – the increase of tech etc in Venice Beach
Institute of Creative Technology (ICT) – military, academia and entertainment
Joyce Nip – Friends and foes: China’s connections and disconnections in the Twitter sphere
While much of the social media is blocked,
“foreign hostile networks taking over the regions”
@XHNews – one of these ‘blocked’ Chinese Twitter
CGTN, SCMP, Xianhwa News
Looking at #SouthChinaSea
Interestingly @XHNews have set the frames around
There may be not artificial warfare, but other
computational forces at work
Hub account – I think this means the sorts of
large betweenness centrality
@9DashLine and @AsiaMTI758 are the most
What is the correlation to the US based news services then picking up the ‘new’ framing of the events?
Hub accounts are super important
So are Russians more interested in global news than other countries?
Heather Horst – From Kai Viti to Kai Chica: Debating Chinese influence in Fiji
Chinese aid has been welcomed in Fiji, in anticipation of APEC 2018
Cable net offer from Oz around the islands, to ward off Chinese influence
Strong connection with the last coups between China and Fiji
Fiji states it is a relationship, not influence
The 28 WG Friendship Plaza building has difficult Chinese/Fiji relations
First instance of fake news in Fiji – China will take the island of Kadavu to recover the $500m debt
Fiji has an informal censorship process in its media system
The Wikipedia page has been adjusted to say a ‘Province of China’ but was changed back ‘quickly’
Oz support is participatory government (aid cultures), Chinese has been infrastructure support
A common thread between all papers of influence through infrastructures and countries?
What is the broader impact of social media on the Chinese influence?
‘Great Power Rivalry’ – some nation states are more
important than others. This promotes the idea of what are we missing? What if
you don’t have a ‘state’ formed around you? Jewish context and the Chinese
massacres contexts. Non-state actors (not ISIS, but the anarchist forms).
China is not one – There are a number of Chinese (Mainland,
New Territories, Hong Kong)
Bunty Avieson – Minority language Wikipedias for cultural resilience
Privilege has moved online, through connected communication
Cognitive justice – beyond tolerance is something that we need
Localised knowledge practices contribute to cultural production – this is a form of resilience
Pharmacon – a cure and a killer
Wikipedia paints one aspect of the unity of users, knowledge,
Wikipedia is drawing information from Wikipedia
Anyone can edit is a myth – Wikipedians are white global north, Christian, under 30, technical competent
Oral cultures – only 7% have been written down
Positional superiority (Said), long tail of colonialism
Tom McDonald – One Country, two payment systems: Cross-border digital money transactions between Hong Kong and Mainland China
WeChat Advertising campaign that rolled out
across Hong Kong during the time of protest
Immigration has increased significantly during
One country/two systems – the border remains
There is a focus to engage communication
technologies to secure the future
2016 the Money Authority gave the right to five
operators to launch digital wallets (Alipay, WeChat, Octopus, OlePay, TapnGo)
Users are using WeChat and/or Alipay to transfer
funds and then purchase things for cheaper (better rates) in Hong Kong
WeChat groups are emerging for money transfer
Culture is always changing, cultural dynamism is
a better term
More explanation of microplatformization, and
Can oral Wikipedia help solve the Bhutan problem?
Jolynna Sinanan – Mobile media and mobile livelihoods in Queensland’s coal mining industry
What access do miners have when away from home?
Three areas of contestation: they are not
allowed to have mobiles while working, They are often in remote areas with low
coverage, connection to home is no one’s responsibility
mobilities and families – digital media
characterized by mobilities
Literature says: Digital media is how families
do everything together, this is how users make sense of each other and their
context while they are apart from each other
Social transformations are under-developed
Jhow mobilities make sense. through ‘work’ and
Drops ‘cashed-up bogan’ as a term to describe
the impact of the stress on the workers
FIFO Life as a producer of memes
How is this different to pilots? They fly in and out, have similar digital media tools, but are vastly different in how they react with their family?
Tian Xiaoli – No escape: WeChat and reinforcing power hierarchy in Chinese workplaces
WeChat users often think about superiority
online – who is senior? Who is younger? This is reflective of offline lives
Hierarchy and behaviour studies as a background
for the workplace
Jack Linchuan Qiu (Chung Minglun & Pun Ngai) – The effects of digital media upon labor knowledge and attitudes: A study of Chinese vocational-school students
School students from poorer backgrounds – being
trained for vocational jobs (blue collar)
Effects study on the rights
The border between social classes
A study on human capital (Becker, 1964) – the
internet economy, the knowledge economy,
How is the schooling process outdating, or
distracting, or are they adding to the education process?
Passive use of internet versus active use (net
potato (Kaye, 1998))
A process that leads to individualistic usage
well (Arora, 2019)
Increased consumerist activity does not
necessarily relate to decreased labour subjectivity
Media literacy encourages reflective thinking
Is consumerist worry an elitist position?
What is the labour subjectivity if the user is Reflective/individualistic? for example
Tommy Tse – Dream, dream, dream: The interwoven national, orgnaisational, and individual goals of workers in China’s technology sector
Sociology pays more attention to the practice beyond the theoretical
Cultural practices and how they play out in labour practices
Chinese dream versus Alibaba Dream versus individual dream
https://i1.wp.com/jonathonhutchinson.com.au/wp-content/uploads/2019/08/Hong_Kong_2019.jpg?fit=1920%2C1440&ssl=114401920Jonathon HutchinsonJonathon Hutchinson2019-08-31 11:32:222019-08-31 11:32:33Cross-border Media Flows, Infrastructures and Imaginaries in a changing Asia-Pacific – USyd and HKU Symposium
I’m cooking up some ideas while I’m away on Sabbatical at the Hans Bredow Institute. My core focus at this stage is the ‘how to’ research automation and algorithms. My current approach is integrating retro engineering through ethnography and design thinking. At this stage, I’m calling it Data Ethnography and below sets out a guideline for what I think that should be.
No doubt this is the skeleton for a journal article, but what is here is the early developing of a new method I am currently working on.
If you think this methodology could be useful, or you have any feedback or suggestions, please leave them below in the comments.
Why Data Ethnography?
Humanities and social science digital research methods have been interrupted due to the prominence of privacy and surveillance concerns of platform interoperability that produces large quantities of personified data. The Facebook Cambridge Analytica scandal, especially the revelation of its ability to construct predictive models of its user’s behaviors, brought to the public interest concerns over how platform user data is harvested, shared and manipulated by third party providers. The global pushback against the platform provider’s use of these data resulted in platforms closing down some access to application programming interfaces (APIs) to inhibit data manipulation. However, these restrictions also impact on how public benefit research is conducted, providing a useful prompt to rethink how humanities, social scientists and human computer interaction scholars research the digital.
While the datafication of our digital lives has provided us with new insights, the digital methods that enable us to research our digital selves have always been mixed to understand the field of enquiry, along with its surrounding political, cultural and economic constructs.Increased digital practices built on sophisticated calculations, for example the use of algorithmic recommendations, connected devices, internet of things, and the like, have impacted on our research environments, prompting the question, how do we research what we can’t see?This article provides evidence from investigating the visual cultures that surround YouTube that a new methodology is required to research the apparent ‘black boxes’ that operate alongside our digital selves through data ethnography. Data ethnography is the combination of stakeholder consultation, top level data analysis, persona construction, fine data analysis and finally topic or genre analysis. Data ethnography enables not only what we cannot see, but provides a useful way to understand government interoperability mandates and inform appropriate policy development.
Overview of Data Ethnography
methodology emerged from asking the question, what does the Australian YouTube
visual culture look like? Building on the long-term participant observation
that is synonymous with ethnography, a researcher is able to understand the
norms, cultural affordances, communication practices, and so on. The researcher
is required to both produce and consume videos on the platform to understand
how users will create content to suit the platform constraints. Simultaneously,
viewing the content provides insights into how viewing publics are constructed,
how they communicate, what is considered important, norms and languages. In the
context of YouTube, this included the platform, but also the intermediaries
such as digital agencies, multichannel networks and other digital
intermediaries such as influencers to highlight publication strategies. The
combination of this ethnographic data provides a compelling starting point for
the additional methods that emerge.
The video content was analysed using discourse analysis reflective of Jakobson (1960) to understand the video language function as referential, poetic, emotive, conative, phatic, and/or metalingual. As such the discourse in one of four ways: contact enunciation – looking into the camera & addressing the audience; emotive enunciation which is the expressive or affective relating to the style of the YouTuber; genre including thematic content, style and compositional structure; enunciative contract which is the reading contract (Véron, 1985) between the enunciator (addressor) and enunciatee (addressee). The discourse analysis enabled the vast amounts of YouTubers to be categorised into a smaller, more manageable group of users.
on the discourse analysis, I asked the users of the platform the following
What is your gender?
What is your age?
How often do you use YouTube in a week?
What is your favourite category of YouTube video?
Are you likely to watch the next video that YouTube suggests for you?
Do you ever watch the trending videos?
When you enter this address into your web browser, what is the URL of the “up next” video that it suggests for you: https://youtu.be/4_HssY_Y9Qs
results of these several questions then guided the following snowballing
process of the additional methods.
Top Level Data Analysis
undertaking comprehensive data scraping processes that rely on platform data
availability, it is useful to observe how various incidental metrics are
available. In the case of YouTube, this related to likes, comments, views, and
the like that provide insights into what people are watching, how they engage
with the content, and how they talk about the content. These top level metric
data observations enable the researcher to direct the research or focus on
areas of interest that are not otherwise obvious through the consultation phase
of data ethnography. The top level metrics further support the user practices
on how content is produced, published, shared, and consumed amongst a wide
variety of users. Finally, the top level data analysis enables the researcher
to ask questions such as what data are available, which processes might be
automated, and how might these data be repurposed for other sorts of
YouTube, the top level data analysis translated to the following areas of
Reaction to those comments
Comments on comments
the YouTube platform, these are the metrics that are available to the
non-social science data scraping process. Researchers with no data programming
skills are able to extract these data.
Persona construction is a research approach that is based in human-computer interaction (HCI), user-centred design (UCD) and user-experience (UX). Emerging from the Design Thinking field which is human-centred to solve problems, persona construction is useful to understand how problems can be addressed between human and machine interaction. “Design Thinking is an iterative process in which knowledge is constantly being questioned and acquired so it can help us redefine a problem in an attempt to identify alternative strategies and solutions that might not be instantly apparent with our initial level of understanding” (Interaction Design, n.p.). It can have between 3 and seven stages, but these stages are not sequential or hierarchical, but rather iterative and the process typically does not abide to the dominant or common approaches of problem solving methods.
are 5 phases in Design Thinking:
Empathise – with your users
Define – your user’s needs, their problem, and your insights
Ideate – by challenging assumptions and creating ideas for innovative solutions
Prototype – to start creating solutions
Test – solutions
Construction in Design Thinking is in the second phase of the process, which
enables the researcher to define user needs and problems alongside one’s
insights. There are four types of personas: Goal-directed, Role-based,
Engaging, and Fictional personas. The data ethnography methodology uses
Fictional Personas which “The personas in the fiction-based perspective are
often used to explore design and generate discussion and insights in the field”
(Nielsen, 2013, p.16). In this environment, a persona “is represented through a
fictional individual, who in turn represents a group of real consumers with
similar characteristics” (Miaskiewicz & Kozar, 2011, p. 419). Secondly, and similarly to ethnography,
a persona is described in narrative form. This narrative has two goals: (1) to
make the persona seem like a real person, and (2) to provide a vivid story
concerning the needs of the persona in the context of the product being
the context of YouTube research, the key criteria for the fictional personas
ensure the accuracy of the process, the research was conducted behind the
university wall which has a large range of IP addresses. The research was
conducted using Firefox under a new username for each persona, the researcher
was not in a signed in state for Google or YouTube, a new Google account was
created for each persona and the location of user was set by suggesting a phone
area code as per their country. Their interests (Hobbies) became the search
terms and the algorithmically generated results were recorded in a pre-trained
and post-trained state.
Fine Grained Data Scrape
By engaging the persona construction method which reveals insights into how an algorithm will treat its users, or within the context of this research the sorts of results it will recommend, it is then possible to engage in a fine-grained data scrape. A fine grained data scrape is defined as ….[ref]. In this research, it become possible to understand which were the top related videos, which channels were the most viewed, and sorts of networks that emerge around those videos. This process is most useful for not only identifying specific nodes or videos, but also clusters which can be translated into thematic areas, issue publics (Burgess and Matamoros-Fernández, 2016), and audience clusters. I have previously written about the specific social network analysis (SNA) method so I will not go into that detail here, but in order to find these thematic clusters there is a process of data extraction, cleaning and processing which can be followed. SNA is defined as a computational practice “which draws on computational technologies to help identify, aggregate, visualise and interpret people’s social networking and social media data traces” (p.1). In the first instance, I engaged the YouTube Network Analysis Tool (Ref) to extract the network data of related videos to those which returned as popular in the persona construction method – a post trained algorithm state. This digital method tool extracts the data as a Gephi file which can then be manipulated to provide a social network analysis (SNA) across the dataset.
final method to understand how users congregate around popular content on
YouTube, and how they communicate about the material, was to engage in topic
Topic Modelling is the final method which attempts to understand
how users talk about certain things in particular ways. Specifically, I was
trying to understand how certain topics emerged in relationship to other
topics, which can be understood through the Latent Dirichlet Allocation topic
modelling approach. Smith and Graham note, “Informally, LDA represents a set of
text documents in terms of a mixture of topics that generate words with
particular probabilities” through a predetermined number of topics. This
provides the researchers with a “heuristic approach that aim[s] to maximise the
interpretability and usefulness of the topics”.
example, if we wanted to find out what are the popular topics that are
discussed by a 14 year old Australian boy, we would construct the persona with
interests, which in turn become search terms of, bike riding, Lego,
Playstation, and Phil and Dan. The top YouTube Channel recommendations for this
user before the algorithm training were: