Janet Salmons is a network member and a contributing expert to the online team.
The cover of the
Going Viral book attracted my
attention at the Association of Internet Researchers’ conference—and stimulated
my curiosity. “Going viral” is another of those terms we commonly use, but what
does it really mean? By understanding the term, can we become better observers
of viral events? I asked the authors, Karine Nahon @karineb and Jeff Hemsley @JeffHemsley if they would share some insights with the NSMNSS
community. Our discussion went like this:
JS: Can you discuss the research or
thought process that went into your definition for “virality” as described on
page 16?
Virality is a social information flow process
where many people simultaneously forward a specific information item, over a
short period of time, within their social networks, and where the message
spreads beyond their own social network to different, often distant networks,
resulting in a sharp acceleration in the number of people who are exposed to
the message.
JH: In previous
research projects looking at blogs and videos, we looked for a definition and
couldn’t find one. We had a lot of discussion to come up with a definition that
was rigorous, that researchers could use.
KN: We started in
2008, and at the beginning, the definition was similar to those used in
marketing and communications literature. It talked about speed of virality and
distribution of information inside and in between networks. But it wasn’t
refined enough, or crystalized enough, it was missing something. The definition
has to have these components. It’s a social process-- a social information
flow, not just an information flow, and it has to be social, moving from one
person to another. It is not just broadcasting. The speed is important and also
the reach and spread, not only the number of people it reaches but also the
networks it hops through.
JS: Can you explain the
“viral information event” (p. 17)?
KN: We
distinguished between a viral “event” and a viral “topic.” An event is an
information item, a video, a text, any information item that spreads through
network. An information topic is a combination of many different viral and
non-viral events around a particular topic. For example, think of Snowden as a
topic, it was a combination of
information events that were non-viral and some went viral. So while not
all events went viral around the Snowden leaks, the whole topic is defined as a
viral topic.
JH: To say
something is a viral event is to narrow it down to something specific, one
event.
JS: Can you discuss
your thinking about many-to-many? In the book you talked about how the “many”
have a role beyond just forwarding a message.
KN: There is a
misconception that when we discuss virality, we refer to the same information
item being spread. But in many cases what happens is that when I post something
on Facebook, and add to it some text, I have reframed the item. In creating a
social information flow, people shape it according to their own values and
norms.
JH: When I share a video into my network, I
usually add a comment and when I do that I am essentially framing the message
and re-contextualizing it for my audience. That’s an important aspect of why
these events are social. The many-to-many part of it means that it subtly or
not so subtly changes the meaning of the message or augments the meaning
embedded in the content.
JS: I was
intrigued by the point that sometimes reframing actually negated the message
from the original content. Other thoughts to add about re-framing?
JH: In our first viral study of blogs and
videos, we started to realize there is this idea in networks that people create
links because they are similar in some way, this is called “homophily.” We
looked at blogs linking to viral videos, and we saw that liberal blogs linked
to the same videos that other liberal blogs do. And conservative blogs link to
the same videos. When they cross-link,
when the conservative blog links to a liberal video, it is because the
conservative can re-frame or re-cast the video in a way that supports their own
ideas. When a liberal blogs linked to a conservative video and says, those
dirty conservatives are sending out attack ads again, they are changing the way
their audience is perceiving the video. When they click it, the viewers see it
as an attack ad, without even listening to the conservative message. Instead we
are pre-conditioned to see the video as an attack ad because of the re-framing
of the message.
JS: At NSMNSS
we’ve discussed ways that social media is not neutral. There are real control
factors. Your book shows that virality is not just an organic phenomenon, there
are some real control factors. You said:
“the power of network gatekeepers is hidden…this is key to social
transformation in networked societies” (p. 48) and “…every tool we use on the
Internet is a type of gatekeeper” (p. 57). Talk about implications of Network
Gatekeepers and the power of network gatekeepers to influence politics and
society…
KN: When I developed network gatekeeper
theory in my dissertation I didn’t realize it would be popular 14 years later!
There is a lot of information control and power dynamics in social networks.
Information technology design is not neutral, it is very political, not
political in the sense of partisan. When we design social networking sites we
promote certain values, interests and political interests. Once we agree that
technology is not neutral, we can also discuss how information control
(gatekeeping) is political as well.
We see different
types of network gatekeepers. Each one of us can be potentially a network
gatekeeper, if we exercise any type of information control. If I ask my
children not to enter to certain sites, I am creating a gatekeeping process.
Network Gatekeeping Theory enlarged the traditional gatekeeping concept from
selection of information, as editors did, to encompass something larger, to encompass
information control.
What is the
connection between network gatekeeping and virality? There is a strong connection.
For something to become viral it needs to be driven by two kinds of forces.
One, which is top-down, through the network gatekeepers, where certain actors
exercise power and information control and help to spread the information. The
other is a bottom up force, about information influence, that is organic,
sharing data and interests between people and networks. When these two forces
come together, that is when virality happens.
Almost every
viral event goes through network gatekeepers. Facebook is a gatekeeper, Twitter
is a gatekeeper, the government is a gatekeeper. Each one of them exercises a
different level of gatekeeping, but viral events must go through gatekeepers.
JH: We are all gatekeepers in social media.
Each one of chooses to share, or not share, the content we come across. When we
choose share it, we broadcast it out to our network. As a gatekeeper in my
network, I don’t have the same kind of diffusion power that Huffington Post
has. But, the 150 or so followers I have, may not be exposed to that message
unless they hear it from me. So gatekeeping is a process that has to do with
the choices we make.
JS: Gatekeeping
seems to relate to a lot of wider issues of identity and the choices we make to
create networks that promote our identity.
KN: Network gatekeeping is not only about
filtering information. The main role of the new gatekeeper is to connect one
network to another, like boundary spanners that are described in management
literature - they can link one network to another, allowing the virality engine
to spark.
Virality has the
power to challenge social structures,
the institutional structures, the main basis and rules and practices that
regulate behavior of people in society.
Transparency is one of the mechanism that together with virality
challenges social structures - Virality has the force because with many people
are exposed to the message very fast. As a result, the mass demands answers,
greater accountability. It forces governments and nations, public and private
institutions and people to act and respond. This power of people to share
information can circumvent traditional gatekeepers and elites to demand
accountability and that changes the structure of society.
JH: A lot of times we think of network
gatekeepers as bad because we are afraid that they are controlling info in ways
that aren’t good, but these gatekeepers also tie us together. When gatekeepers
share and promote information, they give us a common experience that keeps our
society linked together. So on one hand, gatekeepers can hinder important
information or on the other hand they also tie us together.
JS: Can you talk about the methods used in study of
blogs.
JH: We collected and analyzed large
heterogenous data sets. One person who was key is Sean Walker. We collected a
large amount of videos from the 2008 [US] election and blogs, stored in Sql
data bases. We used social network and econometrics regression to look at
life-cycles of virality. When we categorized videos, we used content analysis.
Both statistical techniques and content analysis methods were used. For the
book, we found new cases, involving additional data and analysis. We used a lot
of existing research- with interdisciplinary synthesis of marketing,
communication, computational social science, political communication,
sociology, and network theory. We structured book and chapters in logical
groupings that could be used to teach a course.
JS: What advice can you share with researchers who are
interested in virality?
KN: Next steps involve incorporating
different disciplines and not looking from just one. Compare virality today and
before we had social networks, what has changed? Another thing that is
important to continue and study is the impact on societal structure. We are
only at the tip of the iceberg to understand the impacts.
JH: This is a new area that has really not
been touched. The people who went into this first were in marketing and there
is research in that area that is in depth. Then the computational social
scientists have started looking at very big events with millions or billions of
views or shares. But what is really missing is the qualitative social look at
virality. How is this tied to identity? When people share things, why this and
not that? Those are some really important questions we would like to
understand. There is also this question of scale.
Computational social
scientists are interested in looking at these big events, there is almost a
data fetish about looking at really big things. But a viral video that’s shared
an indigenous communities in the Northwest [of the US] that just gets 5,000
views may be more impactful on that community than Gangnam Style that got a
billion views and was seen all over the world. We need to think about virality
as scalable. What are the boundaries? When it stops, why? What about context?
Something that goes viral in the US may not go viral in Canada. We’d like to
understand why. We look at tweets and videos and talk about research in other
areas, but how is it that viral games that spread differently than videos? What
about viral tweets versus viral news stories? There are a huge number of
questions.
The methods that
people need to use are every method that every researcher uses. There is a
really strong case for doing qualitative work, we need to interview people to
ask them why they are spreading or not spreading content. We need to do
grounded theory to understand these questions from the ground up. We need to
keep doing the big data quantitative analysis, because that does give us a
perspective. But I think this is a topic that can be studied many different
ways, in different fields. I hope our book is a starting point.
KN: Virality is a complex phenomenon with
impacts on the individual level, communal and societal level. It is important
to raise the ethical issues around virality, because when something goes viral
the spread of information is out of control. Once something becomes viral, it
is hard, almost impossible to control. The non-controllable nature of virality
raises hard questions about privacy or breach of privacy of individuals. What
are the limits, what are the red lines of society? What are the ethical rules
that we employ in terms of the data we analyze? Can we use the data? The easy
way is to think it is OK if we anonymize the data. But if someone is harmed
there is no way back, the life of the person, the course of history will change
because of that virality.
The 7th
chapter attempts to think forward about the concept of virality. The question
we need to ask ourselves is: what will we be left with? What will history look
like 200 years from now because of viral events, sharing and many-to-many
interactions? It is not like the traditional gatekeepers can only give us
certain pieces of information, like they used to 200 years ago. Now that we
have viral events being curated, what will that mean for history, for the many
narratives that constitute history? Are we going to get a more equitable and
just society because we hear more narratives? Or maybe the opposite, because of
the power interactions behind the scenes? What will be the prevailing
narratives when people look back at our time? What are we leaving to the next
generation in how we archive these viral events?
__________________________________________________________________
I hope NSMNSS
readers can grasp the discussion—and research— potential for the topics covered
in the book, Going Viral. For this reason I think
it would be a terrific text in a course where generative conversations could be
had with future researchers of digital culture and communications. If you are
doing research in a related area, I hope you will use the comment area to share
ideas and links to your work.
PS. I did not
pay Jeff to make that comment about the need to do interviews about the
motivations for online sharing, but I hope it goes viral!
