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A social experiment!
We want to discover how viral a tweet would be!
#spreadrhizomes
Aras BOZKURT
MA and PhD canditate in Distance Education
Freelance scholar & leisure learner,
Netizen, connectivist, hard-core gamer and clubber…
Overall Graph Metrics:
The graph is directed.
The graph's vertices were grouped by cluster using theClauset-
Newman-Moore cluster algorithm.
The graph was laid out using the Harel-Koren Fast Multiscale layout
algorithm.
The edge colors are based on edge weight values. The edge widths
are based on edge weight values. The edge opacities are based on
edge weight values.
The vertex sizes are based on betweenness centrality values.
Vertices: 100
Unique Edges: 122
Edges With Duplicates: 41
Total Edges: 163
Self-Loops: 17
Reciprocated Vertex Pair Ratio: 0,0245901639344262
Reciprocated Edge Ratio: 0,048
Connected Components: 3
Single-Vertex Connected Components: 1
Maximum Vertices in a Connected Component: 97
Maximum Edges in a Connected Component: 160
Maximum Geodesic Distance (Diameter): 4
Average Geodesic Distance: 2,117485
Graph Density: 0,0126262626262626
Modularity: 0,36791
Betweennes Centrality
@arasbozkurt
@vcvaile
@vanessavaile
@plugusin
@ısilboy
@wentale
@sfxsourcesounds
Eigenvector Centrality
@arasbozkurt
@vcvaile
@plugusin
@ısilboy
@wentale
@jaapsoft
@chaydin
@vanessavaile
@xb7r
@Jeffreykeefer
PageRank
@arasbozkurt
@vcvaile
@plugusin
@vanessavaile
@ısilboy
@wentale
@nickkearney
@xb7r
@jaapsoft
@chaydin
Top 10 who has most followers
@exposure4all 662641
@shwood 458246
@seanbeeson 227654
@sfxsourcesounds 171604
@alpmimar 150911
@courosa 81537
@quigleyp 39548
@elearngraphic 32577
@timbuckteeth 28995
@juandoming 21577
Top 10 who has tweeted most
@juandoming 351987
@exposure4all 225508
@courosa 107306
@daverage 79921
@timbuckteeth 66883
@dmace8 63696
@bonstewart 58334
@kathielarsyn 57649
@shwood 53171
@jeffreykeefer 47717
Features of #spreadrhizomes
• Broadcast Network
• In-hub & Spoke
Twitter commentary around breaking news stories and the output of well-known media outlets and pundits has a distinctive hub
and spoke structure in which many people repeat what prominent news and media organizations tweet. The members of the
Broadcast Network audience are often connected only to the hub news source, without connecting to one another. In some cases
there are smaller subgroups of densely connected people— think of them as subject groupies—who do discuss the news with
one another.
A Broadcast Network often has one or two large hubs with many spokes while the other groups are relatively small and internally
densely connected.
There are still powerful in the new social media world. Enterprises and personalities with loyal followings can still agenda setters
and conversation starters have a large impact on the conversation.
1-The Broadcast Network structure is dominated by a hub and spoke structure, with the hub often being a media outlet or
prominent social media figure, surrounded by spokes of people who repeat the messages generated by the news organization or
personality.
2-Isolates indicate the broadcaster’s message has visibility beyond the “regulars” who regularly repeat the broadcaster’s
messages.
3-More densely interconnected groups are composed of small communities of interconnected people interested in discussing the
hub of the Broadcast Network with one another.
http://www.pewinternet.org/2014/02/20/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters/
THE JOURNEY OF EGG AND SPERM- WEIRD, WE HAVE SIMILAR STORIES 
http://yourselfseries.com/teens/topic/reproduction/the-journey-of-egg-and-sperm/
The journey of egg and sperm is similar to journey of an idea within a community or network. There are a lot of
casualties (deaths) among the sperm as they swim toward the egg (just like the attempts to disseminate an idea by
retweeting and having nothing)
First, many get lost in the maze of a woman’s uterus (networks) where they also have to contend with acidic vaginal
secretions (content). Only about 10,000 of the sperm overall will manage to reach the fallopian tube where the egg is
hiding (a ha moment). This can take up to two hours since the sperm are so tiny. They have to guess which fallopian
tube contains the egg (there is no map, use subjectives) (which way do I go now, door number one or door number
two? Come out, come out, where ever you are—well, you can imagine the games they play in there.) (they try to find
a way to go out out of chamber)
Soon fluids in the reproductive tract excite the sperm (node) so their tails become more powerful and a woman’s
tract will also contract enough to push the sperm in the right direction (Some ties becomes stronger).
Meanwhile, the egg is making its way down the fallopian tube to meet up with the sperm. When the egg and sperm
meet the sperm cells actually release an enzyme that causes the breakdown of the protective layers of the egg.
About 100 sperm sacrifice themselves during this process in order to forge a path for the one sperm that will make
his way to the egg (This is what we did to go out of chamber while we were retweeting).
After that lucky sperm penetrates the egg, a chemical reaction occurs within the egg (it’s seriously like winning the
lottery). (when a hub [strategic node] disseminate [retweet] an idea).
When the egg and sperm meet they make a zygote that continues to divide until it has about 100 cells formed and
becomes known as a blastocyst. During this process it is also making its way to the uterus where it will adhere to the
endometrium (lining of the uterus) and begin growing in the warm, nutrient-rich fluid of the woman’s uterus. Nine
months later, if all goes well, a baby is born (this is nesting period of the tweet on an another network).
What! What about changing «Rhizomatic
learning» to something else ;)
• In 48 hours…
A single tweet first echoed (mutured to be able to reach out of chamber) and then spread to
invade other spaces!
Some rhizomes resisted while some tried to go out of chamber (each retweet is an attempt
to find the weakest point of the chamber)
The rhizomes that extended out of the chamber are creators of the content who shape the
network, lead a notion to find its way.
Ideas use hubs as a bridge to be viral, to plague other networks.
It is clear that some action verbs such as «engaging» is important to disseminate it.
This experiment also confirms «the long tail» theory…
This experiement also confirms «90-90-1 rule» (in terms of nodes)
This experiement also confirms «80%-20% rule» (in terms of consuming content)
ECHO
CHAMBER
ECHO
CHAMBER
INVASIVE
SPECIES
arasbozkurt@gmail.com
@arasbozkurt

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#Spreadrhizomes

  • 1. A social experiment! We want to discover how viral a tweet would be! #spreadrhizomes Aras BOZKURT MA and PhD canditate in Distance Education Freelance scholar & leisure learner, Netizen, connectivist, hard-core gamer and clubber…
  • 2. Overall Graph Metrics: The graph is directed. The graph's vertices were grouped by cluster using theClauset- Newman-Moore cluster algorithm. The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm. The edge colors are based on edge weight values. The edge widths are based on edge weight values. The edge opacities are based on edge weight values. The vertex sizes are based on betweenness centrality values. Vertices: 100 Unique Edges: 122 Edges With Duplicates: 41 Total Edges: 163 Self-Loops: 17 Reciprocated Vertex Pair Ratio: 0,0245901639344262 Reciprocated Edge Ratio: 0,048 Connected Components: 3 Single-Vertex Connected Components: 1 Maximum Vertices in a Connected Component: 97 Maximum Edges in a Connected Component: 160 Maximum Geodesic Distance (Diameter): 4 Average Geodesic Distance: 2,117485 Graph Density: 0,0126262626262626 Modularity: 0,36791 Betweennes Centrality @arasbozkurt @vcvaile @vanessavaile @plugusin @ısilboy @wentale @sfxsourcesounds Eigenvector Centrality @arasbozkurt @vcvaile @plugusin @ısilboy @wentale @jaapsoft @chaydin @vanessavaile @xb7r @Jeffreykeefer PageRank @arasbozkurt @vcvaile @plugusin @vanessavaile @ısilboy @wentale @nickkearney @xb7r @jaapsoft @chaydin Top 10 who has most followers @exposure4all 662641 @shwood 458246 @seanbeeson 227654 @sfxsourcesounds 171604 @alpmimar 150911 @courosa 81537 @quigleyp 39548 @elearngraphic 32577 @timbuckteeth 28995 @juandoming 21577 Top 10 who has tweeted most @juandoming 351987 @exposure4all 225508 @courosa 107306 @daverage 79921 @timbuckteeth 66883 @dmace8 63696 @bonstewart 58334 @kathielarsyn 57649 @shwood 53171 @jeffreykeefer 47717
  • 3. Features of #spreadrhizomes • Broadcast Network • In-hub & Spoke Twitter commentary around breaking news stories and the output of well-known media outlets and pundits has a distinctive hub and spoke structure in which many people repeat what prominent news and media organizations tweet. The members of the Broadcast Network audience are often connected only to the hub news source, without connecting to one another. In some cases there are smaller subgroups of densely connected people— think of them as subject groupies—who do discuss the news with one another. A Broadcast Network often has one or two large hubs with many spokes while the other groups are relatively small and internally densely connected. There are still powerful in the new social media world. Enterprises and personalities with loyal followings can still agenda setters and conversation starters have a large impact on the conversation. 1-The Broadcast Network structure is dominated by a hub and spoke structure, with the hub often being a media outlet or prominent social media figure, surrounded by spokes of people who repeat the messages generated by the news organization or personality. 2-Isolates indicate the broadcaster’s message has visibility beyond the “regulars” who regularly repeat the broadcaster’s messages. 3-More densely interconnected groups are composed of small communities of interconnected people interested in discussing the hub of the Broadcast Network with one another. http://www.pewinternet.org/2014/02/20/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters/
  • 4. THE JOURNEY OF EGG AND SPERM- WEIRD, WE HAVE SIMILAR STORIES  http://yourselfseries.com/teens/topic/reproduction/the-journey-of-egg-and-sperm/ The journey of egg and sperm is similar to journey of an idea within a community or network. There are a lot of casualties (deaths) among the sperm as they swim toward the egg (just like the attempts to disseminate an idea by retweeting and having nothing) First, many get lost in the maze of a woman’s uterus (networks) where they also have to contend with acidic vaginal secretions (content). Only about 10,000 of the sperm overall will manage to reach the fallopian tube where the egg is hiding (a ha moment). This can take up to two hours since the sperm are so tiny. They have to guess which fallopian tube contains the egg (there is no map, use subjectives) (which way do I go now, door number one or door number two? Come out, come out, where ever you are—well, you can imagine the games they play in there.) (they try to find a way to go out out of chamber) Soon fluids in the reproductive tract excite the sperm (node) so their tails become more powerful and a woman’s tract will also contract enough to push the sperm in the right direction (Some ties becomes stronger). Meanwhile, the egg is making its way down the fallopian tube to meet up with the sperm. When the egg and sperm meet the sperm cells actually release an enzyme that causes the breakdown of the protective layers of the egg. About 100 sperm sacrifice themselves during this process in order to forge a path for the one sperm that will make his way to the egg (This is what we did to go out of chamber while we were retweeting). After that lucky sperm penetrates the egg, a chemical reaction occurs within the egg (it’s seriously like winning the lottery). (when a hub [strategic node] disseminate [retweet] an idea). When the egg and sperm meet they make a zygote that continues to divide until it has about 100 cells formed and becomes known as a blastocyst. During this process it is also making its way to the uterus where it will adhere to the endometrium (lining of the uterus) and begin growing in the warm, nutrient-rich fluid of the woman’s uterus. Nine months later, if all goes well, a baby is born (this is nesting period of the tweet on an another network).
  • 5. What! What about changing «Rhizomatic learning» to something else ;)
  • 6. • In 48 hours… A single tweet first echoed (mutured to be able to reach out of chamber) and then spread to invade other spaces! Some rhizomes resisted while some tried to go out of chamber (each retweet is an attempt to find the weakest point of the chamber) The rhizomes that extended out of the chamber are creators of the content who shape the network, lead a notion to find its way. Ideas use hubs as a bridge to be viral, to plague other networks. It is clear that some action verbs such as «engaging» is important to disseminate it. This experiment also confirms «the long tail» theory… This experiement also confirms «90-90-1 rule» (in terms of nodes) This experiement also confirms «80%-20% rule» (in terms of consuming content)
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