Online Social Networks Can Be Tipped By Less Than 1% of Their Population
An anonymous reader writes "A new algorithm developed by researchers at West Point seems to break new ground for viral marketing practices in online social networks. Assuming a trend or behavior that spreads in an online social network based on the classic 'tipping' model from sociology (based on the work of Thomas Schelling and Mark Granovetter), the new West Point algorithm can find a set of individuals in the network that can initiate a social cascade – a progressive series of 'tipping' incidents — which leads to everyone in the social network adopting the new behavior. The good news for viral marketers is that this set of individuals is often very small – a sample of the Friendster social network can be influenced when only 0.8% of the initial population is seeded. The trick is finding the seed set. The algorithm is described in a paper to be presented later this summer at the prestigious IEEE ASONAM conference."
a sample of the Friendster social network can be influenced when only 0.8% of the initial population is seeded.
Friendster? Wow, you could influence, like, 300 people!
Any chance they're just witnessing C&C nodes transmitting spam orders or pagerank gaming links to the remaining 99.2% of Friendster accounts (all of which are hacked and forgotten)?
My work here is dung.
Is this what Occupy means when they say 1% of the country controls everything?
sudo make me a sandwich
Look at, well... anything. In any human social activity, there are a few people who drive all the activity, and the rest are happy to follow along.
Even leadership personalities are followers much of the time. It's not like everyone can be leaders in everything. You can only ever lead in a few small areas. (Though of course, some people lead more than others; while some people lead in nothing at all, I suppose.)
Trying to be noticed among a million other offerings, this is good news. After doing my best job writing, I can then try to figure out how to reach my own 1% to tip them toward my work, rather than trying to brute-force popularity.
Does this remind anyone of Locke and Demosthenes from Ender's Game? Seeding a few carefully worded articles to change the discourse of the network?
Friendster? Wow, you could influence, like, 300 people
American-centrist much, you insensitive clod?
From http://en.wikipedia.org/wiki/Friendster
Since the relaunch of Friendster as a social gaming platform in June 2011, the number of registered users has reached over 115 million. Over 90% of Friendster's traffic came from Asia. The top 10 countries accessing Friendster, according to Alexa, as of May 7, 2009 are the Philippines, Indonesia, Malaysia, Singapore, Thailand, Pakistan, United Arab Emirates, Sudan, South Korea, Bangladesh and India
A much more interesting conclusion of this study is that 99.2% of social network users will do anything their friends would tell them to do.
Let's say this model predicts that I can end terrorism by converting 100 radical muslims to buddhism. How does that help me? (Simply sending in drones to remove these nodes from the graph, so to speak, will not have the same effect).
Second example, let's say my novel is almost guaranteed to be successful if it gets a glowing review in the New York Times. Well, how hard can that be? Usually trusted nodes are trusted for some reason - because they're reliable. That means they're hard to influence.
This brings to mind the Connie Willis novel Bellwether
The main character, Dr. Sandra Foster, studies fads in Boulder, Colorado. Her employer, Hi-Tek, wants to know how to predict fads, in order to take advantage of this knowledge and thus to possibly create one.
A good read, quite enjoyable and funny.
-- I have a private email server in my basement.
"The trick is finding the seed set." No, it's not. The real trick is finding the seed set of the seed set. On Facebook, you have 900 million users. 1% of that is 9 million, which is too large to influence. But 1% of that 1% is just 90,000, something that a targeted advertising campaign might be able to influence.
Any chance they're just witnessing C&C nodes transmitting spam orders or pagerank gaming links to the remaining 99.2% of Friendster accounts (all of which are hacked and forgotten)?
It's a comp sci paper that is looking for connected nodes in a network, and they're using copies of data sets of social networks as their starting point. They aren't monitoring networks looking for "who is exerting influence over them", they're looking for nodes that are well connected to other nodes, presuming those represent the most valuable people to convince.
Now, could those "friends and families" in the network data actually be there as part of a botnet controller and its zombie minions? Sure, why not? But each one of those would be a single node in the set of nodes as having the right connections. Doesn't mean that marketing to the botherder or the botnet is going to get you much business, but if you were looking for someone who has influence, it would identify the botherder and not the bots themselves.
John
I may have the title of this wrong, but it is a well known rule of thumb in social media tech circles that of 100% of users, 90% pretty much just read, 9% post regularly, and only 1% are really active. So they have simply come up with the algorithm to determine that 1%.
I don't see things in black and white; I see the gray. Heck, I actually see in color, which makes things more difficult
I remember reading about a US study during the Cold War which found that if three specific people in the military and government colluded together they could start an unauthorised nuclear war. Fortunately the government ensured that it couldn't 'work' by monitoring those three people to ensure they couldn't collude.
Online Social Media Networks Inflate Their Numbers by 5000%.
When only 2% of the registered accounts are active, it's not hard to see that the right 1% can make a big change.
I looked at it, and it looks like this
. . .all anyone needs to know is what it will take to get Kevin Bacon to change from on social network to another.
How are you defining a "major religion"? Christianity has around 2 billion adherents, Islam around 1.5 billion, Hinduism around a billion, Buddhism around half a billion ... other than Judaism, what major religions can count less than 115 million people?
I guess they've never heard of George Takei... he tips The Facebook everyday.
I said no... but I missed and it came out yes.
Look you can't take claims like this seriously, by which i mean as immutable laws of nature or even as normative of online communities in a longitudinal sense, that is, as an enduring property of online communities.
From the paper:
In this problem we have a social network in the form of a directed graph and thresholds for each individual. Based on this data, the desired output is the smallest possible set of individuals such that, if initially activated, the entire population will adopt the new behavior (a seed set)
What the study shows in not that will happen in real social networks, but rather in their "tipping model" which is a directed graph whose nodes "activate" when they reach a certain threshold.of input given to them by surrounding nodes.
So what they demonstrated was a property of directed graphs and nodes with a certain made-up (ad hoc) set of characteristics. To assume that those characteristics are descriptive of human beings in a real social network is to extrapolate beyond the results of paper.
The authors obviously think that such extrapolation may be possible since they cite two other papers that they characterize as showing that real social networks have exhibited such behavior, but actually, those papers show something much more hypothetical and specific which I won't go into here.
When they say they applied their theory to social networks, (Buzznet Douban Flickr Flixster FourSquare Frienster Last.Fm LiveJournal Livemocha WikiTalk ) they mean they borrowed the physical topology - the interconnectedness of the nodes- of those networks, (which is available to researchers) NOT that they either found examples of nor instigated the real world behaviour of the people in those networks.
Back to reality, that such things CAN happen is not surprising . I am pretty sure Jennifer Aniston represented less than 1% of the group of American females in the mid 90s, and she wielded the power to tip hairstyles ("The Rachel" hairstyle!!! ) enormously in that time.
Similarly in Roman times, the hairstyles of prominent individual women would appear on coins, for instance, the Emperor's wife. This would lead to a frenzy of copycat hairstyles because hairstyle was one way the rich signaled their status.
There's a danger here that graph theory being applied to social networks will play the role of the mythical "perfectly rational actor" has played in economics. That is, a clean model which produces complex results whose ultimate referent is ONLY itself and in many decisive ways emits behaviour which is OPPOSITE of the behaviour of the real world entity which the theory sought to model.
People are irrational in ways that until recently, with the advent of behavioural economics, were not accounted for in economic models. IMO behavioural economics might as well have taken the name "real economics" . The same thing is going on here. How real people really behave in social networking sites is a wide open question. What we know is people hate to be manipulated and will act against their own seeming best interests in a wide variety of circumstances. See Dan Ariely's "Predictably Irrational" for some examples. Also here's the page on irrationality in Wikipedia. http://en.wikipedia.org/wiki/Irrationality
The point here is
1) this is not a study of people's behaviour, it's a study of the behaviour of nodes which have just those properties the researchers elected to give them transferred to a network topologies which were taken from a variety of real social networks.
2) The behaviour of real social networks is not determined by the assumptions of the researchers
3) nor did those assumptions model the actual behavior of real people in those networks.
Real behaviour is vastly more complex than emitting behavior when a threshold "input" from surrounding people is reached.
Finally, it should be noted that p
like this: christianity is not a religion, it's a classification of religions. catholics are not methodists are not baptists are not 7th day adventists are not episcopalians are not jehovah witnesses etc...
insensitive clod overlords obligatory xkcd car analogy russian reversals whoosh pedant fanbois ftfy in 3...2...1..PROFIT
You forgot to mention - when he didn't capitalize Like, he insulted half a dozen Grammar Nazis.
That's not completely true. While they all have their roots in the same book, the actual religions can be very different.
Roman Catholics, for example, include the worship of demigods (they call them Saints) and obeisance to the Church hierarchy, as well as the rite of confession. Some Protestant religions base their religion on personal understanding of the New and Old Testaments, and the Good Book is the only set of rules to live by. Some Protestant religions include the rite of confession, some don't. Some have clergy, some don't.
To say that all Christian religions are the same except for trappings would be the same as saying that all Abrahamic faiths are the same except for trappings. I mean, sure, Christians have a set of extra books to follow (compared to Jews),and Muslims have another book on top of that. But really, it's the same God they worship, so they're all the same religion, right?
"Trolls they were, but filled with the evil will of their master: a fell race..." -- J.R.R. Tolkien on Olog-hai