Posted by KristinTynski
The debate is over and the results are clear: the best way to
improve domain authority is to generate large numbers of earned
links from high-authority publishers.
Getting these links is not possible via:
- Link exchanges
- Buying links
- Private Blog Networks, or PBNs
- Comment links
- Paid native content or sponsored posts
- Any other method you may have encountered
There is no shortcut. The only way to earn these links
is by creating content that is so interesting, relevant, and
newsworthy to a publisher’s audience that the publisher will want
to write about that content themselves.
Success, then, is predicated on doing three things extremely
- Developing newsworthy content (typically meaning that content
- Understanding who to pitch for the best opportunity at success
and natural syndication
- Writing and sending pitches effectively
We’ve covered point 1 and point 3 on other
Moz posts. Today, we are going to do a deep dive into point 2
and investigate methods for understanding and choosing the best
possible places to pitch your content. Specifically, we
will reveal the hidden news syndication networks that can mean the
difference between generating less than a handful or thousands of
links from your data-driven content.
Understanding News Syndication Networks
Not all news publishers are the same. Some publishers behave as
hubs, or influencers, generating the stories and content that is
then “picked up” and written about by other publishers covering
the same or similar beats.
Some of the top hubs should be obvious to anyone: CNN, The New
York Times, BBC, or Reuters, for instance. Their size, brand
authority, and ability to break news make them go-to sources for
the origination of news and some of the most common places
journalists and writers from other publications go to for story
ideas. If your content gets picked up by any of these
sites, it’s almost certain that you will enjoy widespread
syndication of your story to nearly everywhere that could be
interested without any intervention on your part.
Unfortunately, outside of the biggest players, it’s often
unclear which other sites also enjoy “Hub Status,” acting as a
source for much of the news writing that happens around any
specific topic or beat.
At Fractl, our experience pitching top publishers has given us a
deep intuition of which domains are likely to be our best bet for
the syndication potential of content we create on behalf of our
clients, but we wanted to go a step further and put data to the
question. Which publishers really act as the biggest hubs of
To get a better handle on this question, we took a look at the
link networks of the top 400 most trafficked American publishers
online. We then utilized Gephi, a
powerful network visualization tool to make sense of this massive
web of links. Below is a visualization of that network.
An interactive version is available here.
Before explaining further, let’s detail how the visualization
- Each colored circle is called a node. A node represents one
- Node size is related to Domain Authority. The larger the node,
the more domain authority it has.
- The lines between the nodes are called edges, and represent the
links between each publisher.
- The strength of the edges/links corresponds to the total number
of links from one publisher to another. The more links from one
publisher to another, the stronger the edge, and the more
“pull” exerted between those two nodes toward each other.
- You can think of the visualization almost like an epic
game of tug of war, where nodes with similar link networks
end up clustering near each other.
- The colors of the nodes are determined by a “Modularity”
algorithm that looks at the overall similarity of link networks,
comparing all nodes to each other. Nodes with the same color
exhibit the most similarity. The modularity algorithm
implemented in Gephi looks for the nodes that are more densely
connected together than to the rest of the network
Once visualized, important takeaways that can be realized
include the following:
- The most “central” nodes, or the ones appearing near the
center of the graph, are the ones that enjoy links from the widest
variety of sites. Naturally, the big boys like Reuters, CNN and the
NYTimes are located at the center, with large volumes of
links incoming from all over.
- Tight clusters are publishers that link to each other very
often, which creates a strong attractive force and keeps them close
together. Publishers like these are often either owned by the same
parent company or have built-in automatic link syndication
relationships. A good example is the Gawker Network (at the 10PM
position). The closeness of nodes in this network is the
result of heavy interlinking and story syndication, along with the
effects of site-wide links shared between them. A similar
cluster appears at the 7PM position with the major NBC-owned
publishers (NBC.com, MSNBC.com, Today.com, etc.). Nearby, we also
see large NBC-owned regional publishers, indicating heavy story
syndication also to these regional owned properties.
- Non-obvious similarities between the publishers can also be
gleaned. For instance, notice how FoxNews.com and TMZ.com are very
closely grouped, sharing very similar link profiles and
also linking to each other extensively. Another
interesting cluster to note is the Buzzfeed/Vice cluster. Notice
their centrality lies somewhere between serious news and lifestyle,
with linkages extending out into both.
- Sites that cover similar themes/beats are often located close
to each other in the visualization. We can see top-tier lifestyle
publishers clustered around the 1PM position. News publishers
clustered near other news publishers with similar political
leanings. Notice the closeness of Politico, Salon, The Atlantic,
and The Washington Post. Similarly, notice the proximity of
Breitbart, The Daily Caller, and BizPacReview. These
relationships hint at hidden biases and relationships in how these
publishers pick up each other’s stories.
A More Global Perspective
a fascinating project by Kalev Leetaru at Forbes looked at the
dynamics Google News publishers in the US and around the world. The
project leveraged GDelt’s massive news article dataset, and
visualized the network with Gephi, similarly to the above network
discussed in the previous paragraph.
This visualization differs in that the link network was built
looking only at in-context links, whereas the visualization
featured in the previous paragraph looked at all links. This is
perhaps an even more accurate view of news syndication networks
because it better parses out site-wide links, navigation links, and
other non-context links that impact the graph. Additionally, this
graph was generated using more than 121 million articles from
nearly every country in the world, containing almost three-quarters
of a billion individual links. It represents one of the
most accurate pictures of the dynamics of the global news landscape
Edge weights were determined by the total number of links from
each node to each other node. The more links, the stronger the
edge. Node sizes were calculated using Pagerank in this case
instead of Domain Authority, though they are similar metrics.
Using this visualization, Mr. Leetaru was able to infer some
incredibly interesting and potentially powerful relationships that
have implications for anyone who pitches mainstream publishers.
Some of the most important include:
- In the center of the graph, we see a very large cluster. This
cluster can be thought of as essentially the “Global Media
Core,” as Mr. Leetaru puts it. Green nodes represent American
outlets. This, as with the previous example, shows the
frequency with which these primary news outlets interlink and cover
each other’s stories, as well as how much less frequently they
cite sources from smaller publications or local and regional
- Interestingly, CNN seems to play a unique role in the
dissemination to local and regional news. Note the many links from
CNN to the blue cluster on the far right. Mr. Leetaru speculates
this could be the result of other major outlets like the NYTimes
and the Washington Post using paywalls. This point is important for
anyone who pitches content. Paywalls should be something taken into
consideration, as they could potentially significantly
reduce syndication elsewhere.
- The NPR cluster is another fascinating one, suggesting that
there is heavy interlinking between NPR-related stories and also
between NPR and the Washington Post and NYTimes. Getting a
pickup on NPR’s main site could result in syndication to many of
its affiliates. NYTimes or Washington Post pickups could
also have a similar effect due to this interlinking.
- For those looking for international syndication, there are some
other interesting standouts. Sites like NYYibada.com cover news in the US. They
are involved with Chinese language publications, but also have
versions in other languages, including English. Sites like
this might not seem to be good pitch targets, but could likely be
pitched successfully given their coverage of many of the same
stories as US-based English language publications.
- The blue and pink clusters at the bottom of the graph are
outlets from the Russian and Ukrainian press, respectively. You
will notice that while the vast majority of their linking is
self-contained, there seem to be three bridges to international
press, specifically via the BBC, Reuters, and AP. This suggests
getting pickups at these outlets could result in much
broader international syndication, at least in Eastern
Europe and Russia.
- Additionally, the overall lack of deep interlinking between
publications of different languages suggests that it is
quite difficult to get English stories picked up
- Sites like ZDnet.com have
foreign language counterparts, and often translate their stories
for their international properties. Sites like these offer
unique opportunities for link syndication into mostly isolated
islands of foreign publications that would be difficult to reach
I would encourage readers to explore this interactive more.
Isolating individual publications can give deep insight into what
syndication potential might be possible for any story covered. Of
course, many factors impact how a story spreads through these
networks. As a general rule, the broader the syndication network,
the more opportunities that exist.
Link Syndication in Practice
Over our 6 years in business, Fractl has executed more than
1,500 content marketing campaigns, promoted using high-touch,
one-to-one outreach to major publications. Below are two views of
content syndication we have seen as a result of our content
production and promotion work.
Let’s first look just at a single campaign.
Recently, Fractl scored a big win for our client Signs.com with
in Memory” campaign, which was a fun and visual look at how
well people remember brand logos. We had the crowd attempt to
recreate well-known brand logos from memory, and completed data
analysis to understand more deeply which brands seem to have the
best overall recall.
As a result of strategic pitching, the high public appeal, and
the overall “coolness” factor of the project, it was picked up
widely by many mainstream publications, and enjoyed extensive
Here is what that syndication looked like in network graph form
If you are interested in seeing and exploring the full graph,
you can access the interactive by clicking on the gif above, or
here. As with previous examples, node size is related to domain
A few important things to note:
- The orange cluster of nodes surrounding the central node are
links directly to the landing page on Signs.com.
- Several pickups resulted in nodes (publications) that
themselves generated many numbers of links pointing at the story
they wrote about the Signs.com project. The blue cluster at the 8PM
position is a great example. In this case it was a pickup from
- Nodes that do not link to Signs.com are secondary syndications.
They pass link value through the node that links to Signs.com, and
represent an opportunity for link reclamation. Fractl follows up on
all of these opportunities in an attempt to turn these secondary
syndications into do-follow links pointing directly at our
- An animated view gives an interesting insight into the pace of
link accumulation both to the primary story on Signs.com, but also
to the nodes that garnered their own secondary syndications. The
GIF represents a full year of pickups. As we found in my
previous Moz post examining link acquisition over time, roughly
50% of the links were acquired in the first month, and the other
50% over the next 11 months.
Now, let’s take a look at what syndication networks look like
when aggregated across roughly 3 months worth of Fractl client
campaigns (not fully comprehensive):
If you are interested in exploring this in more depth, click
here or the above image for the interactive. As with previous
examples, node size is related to domain authority.
A few important things to note:
- The brown cluster near the center labeled “placements” are
links pointing back directly to the landing pages on our clients’
sites. Many/most of these links were the result of pitches to
writers and editors at those publications, and not as a result of
- We can see many major hubs with their own attached orbits of
linking nodes. At 9PM, we see entrepreneur.com, at 12PM we see
CNBC.com, 10PM we see USAToday, etc.
- Publications with large numbers of linking nodes surrounding
them are examples of prime pitching targets, given how syndications
link back to stories on those publications appear in this aggregate
Putting it All Together
New data tools are enabling the ability to more deeply
understand how the universe of news publications and the larger
“blogosphere” operate dynamically. Network visualization tools in
particular can be put to use to yield otherwise impossible insights
about the relationships between publications and how content is
distributed and syndicated through these networks.
The best part is that creating visualizations with your own data
is very straightforward. For instance, the link graphs of Fractl
content examples, along with the first overarching view of news
networks, was built using backlink exports from SEMrush.
Additionally, third party resources such as Gdelt offer tools and
datasets that are virtually unexplored, providing opportunity for
deep understanding that can convey significant advantages for those
looking to optimize their content promotion and syndication
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