6. Publishing Openness
(who has access to the ‘publish’ button?)
Everyone Select Few
Social Media
Blogs Magazines
7. Viewing Content
Key Variables:
• Filtering
Tools and services for filtering,
viewing, sharing and providing
feedback on content. Includes
social media feeds, search
results pages, and aggregating
websites.
8. Filtering Content
(who or what filters the content we view?)
Machine Filtering Professional Filtering
Algorithms Using Social
and Topic Graphs
Magazine
Editors
Community & List
Moderators
9. Machine Filtering
(how do we filter the content we view?)
Topical Interest Social Interest
Topic Graph Social Graph
10. Attaching Topics to Content in Publishing
Publishing
Topic Graph
We attach topics to content with
categories, tags, keywords, groups,
communities and hashtags.
11. Attaching Topics to Content After Publishing
Topic Graph
Search Bot
Knowledge Graph
Google crawls our content to assess its relevance to various
topics. It also matches what it finds against its Knowledge
Graph for more accurate relevance assessment.
12. Identity: More than Just a Pretty Face
Identity
Like many things on the web, our identity is not unlike an
iceberg; only a small portion of it is visible to us as our profile.
The rest resides in massive data sets stored on the proprietary
servers of new media companies.
13. Attaching Topics to Identity: the Interest Graph
Identity Topic Graph
Interest Graph
Some of that data relates to our interests. We attach topics to
our identity every time we like, plus, tweet, share or search for
something online. The result is our own, individual interest
graph.
14. Viewing Filtered by Interests
Interest Graph Viewing
Our Interest Graph personalizes our search
results and social media streams to help us stay
on top of our interests.
15. Relationships and Identity: the Social Graph
Identity Social Graph
Some of our identity data relates to our relationships. We build
our social graph by harvesting our past through school and work
connections, crawling lists of friends of friends, and making new
connections through communities and other online interactions.
16. Viewing Filtered by Relationships
Social Graph Viewing
Our Social Graph personalizes our social media
streams to help us tend to our relationships.
17. Connecting the Topic and Social Graphs
+ =
Social Graph Interest Graph Shared Interest
Graph
Our Shared Interest Graph helps us find and
build relationships with people who share our
interests.
18. Revenue from New Media
Interest Graph > Social Graph
with Revenues,
Ads and subscriptions drive most media revenues. Ads work best
when tied to our interests, but are largely noise when we’re
socializing.
Subscription revenues are unlikely from the social graph, unless
paired with interests, as in certain shared interest graphs.
19. End User Engagement is the Super Power
Publishing Social
Graph
Interest
Graph
Revenues Shared
Interest
Graph
Topic
Graph
Viewing
The following is a simple attempt to apply this
pattern language to a handful of representative new
media organizations. Of course, others will have a
very different interpretation of these organizations.
20. Google Plus
Shared interest network with civil discussion and no revenues. 300
million users.
Google ID
main stream,
circle streams,
communities,
Google search
good search, communities,
circles, hashtags
posts and
comments
no revenues,
may help search
revenues
…shared
interest graph
strangers become
friends through a …
21. Google Search
Powerful media aggregator, topic graph and ad network.
1.17 billion users
Google ID
search results
pages
search bots, algorithms,
Knowledge Graph
SEO optimization,
Ad Sense
search
advertising
Search, plus
Your World
relevance algorithms,
personalized search
22. Facebook
Powerful social network with rich user information. 1.3 billion users.
Facebook ID
rich demographics
stream, groups
Open Graph
objects
posts & comments,
Open Graph for 3rd
party sites
on-site ads, mobile
app Audience
Network
friends
interests
groups
23. LinkedIn
Powerful professional network and interest graph. 300 million users.
LinkedIn ID
rich professional
history
stream, groups
companies, schools
occupations, industries
updates, rich posts
& comments
ads to professional
audience,
premium services
professional
connections
interests
school &
organizational
alumni
24. Reddit
Scrappy, content-sharing network, broken out by interests. 114
million users.
weak identity
strong crowd filtering,
minimal algorithmic
filtering
categories,
ok search
Mostly
linking, lots of
comments
minimal ads,
freemium
friends, but
not prominent
25. Huffington Post
News and opinion, powered by staff-coordinated, unpaid writers.
84 million users.
3rd-party logins
mix of editorial and
popularity filtering
60 vertical
sites
unpaid
bloggers
ads $100 million
relies on 3rd-party
social graphs
26. WordPress
Blogging / Content Management tool. 77 million websites (22%
of worldwide total).
WordPress
login
WordPress
Reader
categories,
tags,
keywords
rich editing,
commenting
freemium, ad-on
services
relies on 3rd-party
social graphs
27. End User Engagement as Super Power
The real difference with new media is that it is a two-way channel,
capable of engaging people in a new collaborative partnership.
New media success depends on building business models to
engage end users in publishing and viewing media, and building
social, topical, interest and shared interest graphs.
This is the goose that lays the golden eggs of new media.
28. For more:
A Pattern Language
for New Media
http://www.the-vital-edge.com/new-media/
