- Sneak Peek at Content Sharing Survey Report
05/08/08
I did a sneak peak of my Link Attraction Factors report, and Alanisgood asked for a peak at my data from the upcoming content sharing survey report, so here it is:
This first graph shows the differences between the types of content non-Twitter users share individually and what Twitter-addicts share.
And this graph shows the difference in individual content sharing frequency between frequent blog readers and those people who don’t read blogs (yes, there are still some of those around).I’m hard at work on the report, and hope to have it out very soon, in the meantime let me know what you think of the data so far and anything you’d especially like to see.
- Working on Content Sharing Survey Results
04/28/08
My survey on web content sharing collected around 450 responses and now I’m working on the task of decoding the type-in answers and calculating the results.
I asked the question on twitter, but I’d also like to ask it here, what formats would everyone like to see the results in? I’ve already had suggestions of: spreadsheet and slideshare in addition to the normal graphs-in-a-blog-post format. Any other awesome ideas?
Update: Its also been suggested that I do a downloadable PDF version of the report, like I did with the Link Attraction Factors report.
- How to Make and Spread Rumors
04/17/08
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In 1940, the British military formed an organization as a part of the Special Operations Executive, or SOE, called the “Underground Propaganda Committee” or UPC whose mission was to create and disseminate rumors as defensive weapons against the expected Nazi invasion of the the English mainland. They code-named the rumor weapons “sibs,” short for siblare, latin word “to hiss.” During the war they developed the craft and science of designing rumors and developed international networks of agents to spread the sibs. (Psywar.org has a great history of the UPC.)
During World War II the Americans, under the Office of Strategic Services (OSS), which eventually became the CIA, began cultivating their own rumor-weapon technologies with the help of the UPC and scientist Robert Knapp, who also wrote about rumors in an academic context. Knapp’s work was adapted by the OSS in 1943 to create a sort of manual for rumor engineers during the war. This document was de-classified in 2004.Criteria for a Successful Rumor
- » The successful rumor is easy to remember.
- » The successful rumor follows a stereotyped plot.
- » The successful rumor is a function of the momentary interests and circumstances of the group.
- » The successful rumor exploits the emotions and sentiments of the group.
The manual says rumors are made memorable by being simple, making concrete references, using stereotypical phrases and utilizing humor, many of the same characteristics possessed by the Homeric poems and the rest of the oral tradition.
A stereotyped plot, according to the manual is “the oldest story in the newest clothes.” Old structure, typically derived from local myths, stories or legends, filled in with new content makes the best rumors.Academic work on rumors suggests that they are “collective sense making,” they are a society’s attempt to understand something that is happening where official or formal information is scarce or non-existent. The OSS paper says that good rumors are “provoked by” and provide interpretation or elaboration on a current event, filling a “knowledge gap.” If the locals heard a big boom earlier in the day, a rumor could easily be constructed to explain it if the authorities did not.
If a group is known to have a pre-disposition to mistrusting a certain other group, like Diggers disliking Microsoft, rumors about the evils of Microsoft are easy to spread. The manual says that successful rumors justify or articulate an emotion (such as hatred, fear or desire) widely held by the target population.
Targeting Rumors
The OSS/Knapp report sketches those people or “targets” that make good vectors for rumor spreading and what sorts of rumors will spread most virally amongst them.1. Those people who are most eager for information about events which affect them are the best targets for rumors supplying such information.
2. People with fears, hopes and hostilities stemming from their involvement in the war are most affected by rumors that feed on those feelings.The report also detailed certain kinds of information that should be gathered prior to designing a rumor for a specific group, including:
- » What kinds of information the group is eager for.
- » What information the group already has and what it lacks.
- » The current fears, hopes and hostilities the group already has.
- » The customary and traditional ways the group deals with those fears, hopes and hostilities.
Obviously, the information about the knowledge and emotions of the group should be gather in respect to what the rumor will be about. To use the Digger example again, if you wish to start a rumor about Microsoft, you should find out what Diggers want to know about Microsoft, what they already know and what they don’t know, how they feel about the group, and the traditional ways they express themselves about Microsoft.
Spreading Rumors
The British UPC developed specially designed networks around the world through which they could seed rumors for maximum effectiveness. Each individual rumor was not seeded into every active network, as that would have appeared too obvious; rather, the networks were chosen for their appropriateness to the specific sib.
From psywar.org:
SOE’s whispering network in Turkey was a typical example of how the machinery for spreading rumours worked. A Chief Whisperer was appointed who then recruited ten Sub-whisperers, each of whom was chosen because they had specially good contact with certain classes of people from politicians and Army officers to waiters and barbers, for example. Each Sub-whisperer was conscious of the fact that he, or she, was working for SOE, but although they knew the Chief Whisperer, they did not know the identities of any of the other Sub-whisperers. Each Sub-whisperer then recruited ten to twenty unconscious agents to whom they passed on rumours.
The OSS manual also gave a little detail into how rumors should be spread:
- » Design different rumors that reveal the same “information.”
- » Plant such rumors in different suitable places.
- » Design them so as to appear as of independent origin.
The OSS and the UPC both used a tactic where several rumors were constructed and seeded in such a way that they appeared to come from different sources and took different “routes” to expose the same information to the targets. This way when a person heard more than one source tell complimentary rumors, they were more likely to believe them.
Have you ever tried to start a rumor? I’d love to hear some stories.
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- Why People Forward Chain Letters
04/08/08
Chris Garrett asked a question on twitter this morning:
Anyone know why people forward chain letters?
And since I’ve been doing some research on exactly that question recently, I thought I’d write a post detailing some of what I’ve found.
Probably the most important point is the idea that email chain letters are “virtual urban legends” and as such many of the motivations that cause people to spread urban legends are the same that make people forward those emails.
Many urban legends function as warnings, if you break with social rules and roles you will be punished. Go to lover’s lane with your boyfriend and a crazy serial killer will come and kill you or him (or both of you). Disregard your parents’ dislike of unhealthy fast food and you may end up eating a rat.
As I mentioned briefly in a post last week humans evolved with strong rewards to develop imitation and social learning skills. Evolutionarily, people have a motivation to be susceptible to social warnings and pass them on to their family and community.
In 1998 Edmund Chattoe published a paper for IRISS titled “Virtual Urban Legends: Investigating the Ecology of the World Wide Web” in it he studies traditional chain letters and virus warnings, and in it he cites an earlier paper by Woolgar and Russell (called “The Social Basis of Computer Viruses” I can’t find it on the web) when he says users are rather inclined to believe in computer viruses as just ‘punishment’ for electronic promiscuity
Here the urban legend similarity is clear, if you disregard careful computer-based chastity and network with unsavory types (like downloading pirated music or programs) you’ll be punished with a computer virus.
Before email existed, chain letters propagated via snail mail and while they were still very virulent then, with the advent of the internet several factors changed which accelerated their spread. Obviously the speed of transmission and the ease at which someone can create and pass on an email is a lot greater than for traditional paper mail, and the anonymity of email reduces the risk to those who craft and continue the chains online.
Two of the key criterias of a successful meme are copying fidelity and fecundity, that is the less a message changes each time it is transmitted the greater the chance it has to retain the effective parts and continue spreading, and the more people it can be transmitted to the more successful it will be. Online emails are copied verbatim and all the sender has to do is click “forward” and it an exact copy is sent to all of their friends.
In the paper mail chain letter world, most people had become immune to the over-the-top promises and demands so their effectiveness started to drop. With the ease of spread and the high copying fielding available to mental email viruses, they’ve been able to evolve into more subtle and unfalsifiable variations. The chances of a person passing the email on is great online, so the messages themselves need to require less instructions about their own replication, making them less obvious and more trustworthy. Chattoe says:
More generally, chain letters have increasingly stressed intangibles like ‘good luck’ rather than more concrete rewards. They thus render themselves immune from obvious falsification and tap into a human tendency to ’superstition’, spotting patterns where none exist. If I fail to pass on a chain letter and shortly afterwards something bad happens, I may connect the two events and be more susceptible in future.
And while many (if not most) of these emails are debunked on sites like snopes, preliminary data from my survey shows that those who typically forward chain letters are typically less savvy users and may not know about snopes.
Perhaps the most subtle and powerful viral element of chain letters in email is the social proof that comes with many of them. Every time someone forwards one to his or her address book, another list of recipients and senders is attached to it, creating essentially a list of people who implicitly give authority to the message. If one person sends an email to another, the source may or may not be cited, and the sender’s reputation is the only real social authority the email carries, with a huge list of hundreds of others attached it, it suddenly appears that the message is common knowledge and the receiver is perhaps the only person left on the internet who wasn’t warned of the danger. The social proof factor goes back to information cascades and the understanding that humans base many of their decisions on the choices of others, it just makes good evolutionary and survival sense to do so. Even if you may think an email is a hoax, who are you to think that you know better than hundreds of your peers? And on the off-chance the email was true, and you didn’t pass it on you didn’t do your best to protect and enrich your friends and family.
- Survey on Web Content Sharing and Online Meme Transmission
04/06/08
I’ve had this idea rolling around in my head for a little while now, and I just got around to doing it.
I’m conducting a survey on what types of content people share online, where and how they share it, who they share it with, and the all important question, why they share it.
Please spread this as widely as possible, I’ll publish the results as soon as I get a decent number of responses.
- Informational Cascades Prove Tipping Points Exist
04/04/08
Mediapost reported recently on the results of a survey done by research firm Pollara, and Marshall Kirkpatrick over at ReadWriteWeb commented on it in a post titled “There is No Tipping Point”.A number of thinkers… and now the Pollara study have been arguing that large numbers of people do not make decisions based on the advice of a small number of powerful influencers…
The marketing world was really hoping they could just win over some existing social media power users and have everyone else fall like dominoes. This study says that’s not how it works.
The study says that while 80% of respondents were “very or somewhat more likely to consider buying products recommended by real-world friends and family” only 23% were similarly influenced by “well-known bloggers”. I do not disagree with this data, what I disagree with is the understanding of the mechanisms of social influence. A concept from economics called “Informational Cascades” shows us why the domino-effect/tipping point idea is valid, even in light of this study.
To understand this mechanism an example is helpful. Suppose there are two restaurants and a group of people on the street outside deciding which one to eat at. The most well-informed individuals (those with higher precision in making these types of decisions) will decide first and everyone will see some people start to line up outside of one restaurant. If the others know this person is of higher precision (and even if they don’t) a few people will follow their lead and join the line. Each new person who lines up outside of the restaurant sends a signal to the rest of the group (and in particular their friends and family) that this is the restaurant to pick. The more people who follow the signal, the stronger it gets and you have an Informational Cascade.The idea is presented in rigorous detail in a paper called “Theory of Fads, Fashion, Custom and Cultural Change as Informational Cascades” written by Sushil Bikhchandani, David Hirshleifer and Ivo Welch and published in 1992. To paraphrase:
An informational cascade occurs when it is optimal for an individual, having observed the actions of those ahead of him to follow the behavior of the preceding individual without regard to his own information…
The prediction that a low-precision individual imitates a higher-precision predecessor is consistent with the evidence of numerous psychological experiments demonstrating that a subject’s previous failure in a task raises the probability that in further trials he will imitate a model performing the task (see Thelen, Dollinger, and Kirkland 1979, p. 146)…
an individual who wishes to bring about a social change, for example, introduce a desirable innovation such as an improved sanitary method in a peasant community, must focus his efforts on persuading early community leaders.
This phenomenon will happen even if the early deciders are not experts (although it is certainly enhanced if they are), or influential people normally, by the act of making a choice before others, they become influential to the rest of the group. Real-world examples of Informational Cascades can be found everywhere, from the stock market and voting patterns to the fashion industry, but we may ask the question, why do humans put so much stock into choices made by others before them? For an answer to this we look to evolution.
For ancient (and modern) humans, learning by trial and error is energy and time expensive (not to mention dangerous), it is safer and more efficient to let someone else figure out what plants are safe to eat and then just imitate them. A 1980 paper by John Conlisk titled “Costly Optimizers and Cheap Imitators” showed that “imitators may have as high a long-run ‘fitness’ as optimizers“, and in 1992 Peter J. Richerson and Robert Boyd published a report called “Cultural Inheritance and Evolutionary Ecology” where they showed that in many instances social learning (like imitating your peers) is preferred by natural selection.
If we can agree that the choices and actions of others influence our own decisions then the mathematics of Information Cascades prove that as the size of the participating population increases, “Tipping Points” become inevitable.
- Introduction to Memetics: What is a Meme?
03/31/08
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Enki, Keeper of MeIn ancient Sumerian mythology the god Enlil organized a list of divine laws or Me which eventually found their way into human hands. The Me were a set of rules and regulations detailing every part of the Sumerian culture. The author of the poem “Inanna and Enki” broke his entire civilization down to one hundred instructions, covering ideas like politics, religion, social instruments, arts and crafts, music, intellectual, emotional and social behavior patterns. Not all of the Me were beneficial to the people they ruled, since the Sumerians had good and bad gods and they had good and bad commands. In the poem the Me were described as having physical forms that were stolen from the god Enki by his granddaughter Inanna and brought to man.
In the book Snow Crash Neal Stephenson popularize the story of Sumerian Mes by describing a malicious industrialist with a world-domination plan involving Nam-Shubs, ancient mind viruses that caused their victims to experience glossolalia or speaking in toungues.
Tibetan mysticism contains an idea called a Tulpa, which is the physical manifestation of a thought, idea or prayer. Whereas a Me is a blueprint for constructing something, that “thing” that is created may be called a Tulpa.
Richard Dawkins defined “meme” as a “unit of cultural inheritance“. These are ideas that spread from person to person, ideas like jokes, fashion trends, urban legends, folk sayings and gossip. When the first person discovered how to make fire the idea spread from person to person until the entirety of human civilization was “infected” with the meme and knew how to make fire. Dawkins based the word meme on the Greek word “mimeme” but its similarity to Sumerian Me is unmistakeable.
Dawkins’ 1976 book, The Selfish Gene coined the term “meme” and sparked modern interest in an evolutionary reincarnation of a concept similar to the Sumerian Me, the field of memetics. The field is perhaps best explored in the book Meme Machine by Susan Blackmore, in it she asserts that memes replicate and spread by way of imitation, but she made an important distinction between replication where the final product or behavior is imitated, and where the instructions are copied. To use the Sumerian example, if you have a Me that tells you how to weave a basket, in the later it is the Me itself, that is replicated and spreads between people, not the Tulpa basket, and in the former you see the basket and you decide to make your own just like it. Dawkins and Blackmore both postulate that humans are the only animal that learns by imitation and that this is the primary mechanism by which memes spread, explaining why humans seem to be the only animal vulnerable to mind viruses. Later research has cast this theory in a dubious light, as other animals including birds and primates also learn by imitation and may also be memetic vectors.
In the marketing world we speak of ideas “going viral” and our key metaphor for memes are viruses, infecting a host and then being transmitted to others. From this concept research (pdf) has been done into the reproduction rates of various memes, that is the average number of new people infected by each person who “catches” the virus. If a Meme has a reproduction rate under one, the growth of the virus will eventually stop, if it is over or equal to one it will continue to spread indefinitely (or at least until some outside factor reduces it’s reproduction rate).A key point with memes (and indeed biological viruses) is that they are “motivated” like genes are. Those memes that survive and grow do not do so because of the value they provide to their hosts, but because they are good at replicating and spreading. This is the “selfish meme” concept, just like the Sumerians had good and bad Me, we have good and bad memes. History is replete with examples of bad ideas, detrimental to those who internalized them, that spread like wildfire, so when we are looking to judge an idea’s potential virality we should largely ignore the value the idea bestows upon its host organisms.
Earworm Discussion
I asked the question “What is your worst/best earworm?” on twitter and got some great responses, check out my favorites to see.To be successful a meme must posses two traits, longevity and fecundity. Longevity is the ability of the meme to force it’s host brain to retain it for a period of time, ideas that are easily forgotten do not spread very far. Earworms are simple musical tunes that get stuck in your head because they become trapped in your phonological loop, an auditory memory bank. Fecundity is the ability of a meme to reproduce, there must be some element of the idea that commands it’s host to express it in a contagious fashion. When you start humming that song you have stuck in your head the earworm is being given a chance to lodge itself in the mind of everyone within earshot. I’ve written before, in more depth, about the criteria needed for memetic success, and about the way memes force retention in the human brain.
Online memes come in many forms, from viral videos like the Starwars kid and email chain letters to entire content “genres” like lolcats. Rickrolling is an example of a meme that is not only a piece of content, but a behavioral pattern, here the idea is not just to spread the video, but to trick people into watching it when they thought they were clicking on a relevant link. The instructions replicate, not just the final product. Typically online, we see mostly memes where the Me is copied, you see a page and you send the link to your friends, but in cases like Lolcats and Rickrolling, is often the other type of “Tulpa” replication, where you see the behavior and imitate that.In the blogosphere the word meme has taken on a sort of sub-meaning, where it is a list of questions that one blogger answers and then asks other’s to answer in posts as well. Often each blogger will “tag” more people to participate and the meme will spread from blog to blog. The viral roots of this meaning are clear to see.
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- The Science, History and How to of Contagious Laughter
03/24/08
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Laughter is that involuntary response humans of all cultures share, and while we may think of it as a reaction to humor (the funnier we find something, the more we laugh at it, goes the common wisdom), devoid of any other qualification it is a complex (and virulently contagious) social phenomenon. In this post I study the science of social laughter, the history of epidemics of contagious laughter and I’ll detail how to get started creating your own outbreaks.
A small observational study done by Robert Provine in 2000 showed that humor has little to do with laughter, rather it is our social setting that influences our giggles:Only 10% to 20% of the laughter episodes we witnessed followed anything joke-like. Even the most humorous of the 1,200 comments that preceded laughter weren’t necessarily howlers: “You don’t have to drink, just buy us drinks!” and “Was that before or after I took my clothes off?.” being two of my favorites. This suggests that the critical stimulus for laughter is another person, not a joke…
After excluding the vicarious social effects of media (television, radio, books, etc.), its social nature was striking: Laughter was 30 times more frequent in social than solitary situations. The students were much more likely to talk to themselves or even smile when alone than to laugh. However happy we may feel, laughter is a signal we send to others and it virtually disappears when we lack an audience.
Notice that Provine had to specifically exclude “the vicarious social effects of media“. The only time people laugh alone normally is when they are reading, watching TV or listening to the radio, these are simulated social situations. The effect is more pronounced with the internet because it is actual social interaction rather than one way communication. We laugh to communicate with others.
The Tanganyika Laughter Epidemic
Another curious feature of the social nature of laughter is its contagiousness. In 1962 a small town in what is now Tanzania fell victim to a spate of contagious laughing called the “Tanganyika Laughter Epidemic“. A few weeks after the nation gained its independence three teenage girls in a boarding school in the isolated village began laughing and it spread to the whole town. According to a 1963 report, a total of 10,000 adult men and women and teens of both sexes caught the “disease” after coming in contact with an infected person. The event is known as case of mass psychogenic illness and the modern explanations revolve around intense religious and cultural changes that were happening to the town at the time due to its new-found independence and the replacement of old spiritual beliefs with western religion. The laughter acted as a collective catharsis.
Holy Laughter
Another example of mass epidemics of laughter is the “holy laughter” phenomenon in the Charismatic Christian movement. An article adapted from an 1995 report by Albert James Dager, describes it such:Many churches are reporting spontaneous, uncontrollable laughter erupting from their congregations, even during times of solemn ceremony or messages from the pulpit.
The article traces the beginning of the modern outbreak to April of 1989 when Rodney Morgan Howard-Browne was preaching near Albany. Word of the laughing epidemics spread and he became well known as his services were broadcast on the radio. Another preacher, Randy Clark, experienced Howard-Browne’s holy laughter and brought it to a small church in Toronto where talk of the almost daily meetings turned it into a “mecca of sorts” by 1994. Holy laughter spread like a textbook meme, or idea virus.
The article also mentions Jonathan Edwards from the 1730’s thoughts on an earlier version of the outbreaks at his revivals:
One who is convicted of sin might well laugh or cry after he has felt release from the condemnation and control of sin, which comes with confession and repentance.
Contagious Laughter
Laughter can be a perfectly symmetrical meme in that the mere sound of laughter is capable of infecting and inducing others to laugh themselves, creating the snowball effect of the most successful viral ideas, here’s a video demonstrating this:
The power of contagious laughter is well-known by TV sitcom producers who have included recorded “laugh tracks” in most shows since 1950, the sound of other people laughing makes you laugh.
This, perhaps, then is the reason things that make us laugh “go viral” so often. By its very nature laughing is a cathartic social action, and it spreads virulently through communities, both online and off. Evidence has shown that chimpanzees laugh (and maybe even rats) so we known that the behavior is hard-wired into our brains by millions of years of evolution. Laughter is one of the most primal and powerful social contagions.
How to Engineer your own Outbreak of Contagious Laughter
As we’ve seen from the above examples, contagious laughter is usually a social catharsis from a stressful situation, so given any such setting we should be able to create our own epidemic of laughing. The Tanzanians were undergoing intense and rapid cultural and social changes, holy laughter happens when people feel relief from what they perceive as their own sinful nature and the three guys on stage with the comedian looked pretty nervous. Laughter is the release of social tension.
So the next time you find yourself in a tense meeting at work, a test or quiz in class, or a particularly technical or boring session at a conference give it a try. Start laughing, maybe quiet at first or even mimic that southern dude’s laugh in the video above. Remember it doesn’t have to be in response to a joke or anything funny, you just need tension and a group of people. Make sure that the other people can see (or at least hear you) laughing. In the video example the epidemic really took off when the comedian put the mic in front of the laughing guy and let the audience hear it for themselves.The less people want to laugh, the more they try to fight it, the more tension they’ll be creating and the more contagious the laughter will become. Also remember some people (and especially the presenter or the teacher) won’t appreciate the outbreak of giggling and they definitely won’t like it if they know you’re doing it on purpose so try this at your own risk.
The science of engineering contagious laughter is a new field, so experiment with it. Try different types of laughs, giggles, and chuckles. Try different situations and types of tensions. Make sure you report back the results of your tests, and maybe even try to get audio and video to share with the rest of us.
Update:
Someone in the comments just reminded me about Laughter Yoga, so I would remiss not to include this video example:If you like this post follow me on twitter
- Link Attraction Factors: Report, Tools, API and Plugin
02/29/08
A few weeks ago I published my Link Attraction Factors report over on Read/WriteWeb and the response was awesome. I also made two tools: a keyword checking tool and a title checking tool.
The keyword checking tool
Enter a keyword and the tool will return data on popular stories on Digg that mentioned that keyword. The average story in my database got 299 links and this tool displays the difference between that average and the average number of links accumulated by stories using the word.The title checking tool
Enter a title and the tool will breakdown the words and display the effect they had on the link accumulation of popular Digg stories. This tool is good for copywriters looking to find “words that word”. The scores are displayed in an easy to learn from way.There have been a bunch of great blog posts about them, and some people have said some nice things:
I love it! Dan has developed a fascinating resource and I am sure it will only improve with time and tweaks.
-Chris GarrettI love to see people passionate about their craft who work hard to develop tools and products that help the community. Many people have created Digg tools and Dan has worked hard to create a new, unique tool of his own like his LAF tool. Simply plug-in your future Digg submission title, hit Calculate, and it will return the potential effectiveness of each word contained within your title. The keyword effectiveness is crosschecked with titles of past successful submissions. A fun tool that I’m sure many people will get a lot of use out of.
-Brendan PichaGreat job, Dan! You’ve helped the industry take a huge leap towards quantifying the value of social media optimization.
-Hugo GuzmanDan summarizes a large amount of Digg front page data to show us what categories typically get the greatest number of links. Interesting read, and I look forward to seeing other great studies from him in the future.
-NowsourcingThis is an amazing tool.
-Troy DeckThis tool is great! Will try to write better titles using this tool in the future. Thanks for your great effort.
-Robert de BockNever one to get complacent I’ve also developed an XML API version of the title checking tool and a Wordpress Plugin version of the same tool.
LAF XML API
You can access the LAF (Link Attraction Factors) database via a new XML API by sending your title through a URL (GET) variable like this:http://www.linkattraction.com/api.php?title=this+is+a+test+title
The API will return an XML document of your results that looks like this:
<titleresults> <title>this is a test title</title> <score>-6.96%</score> <word> <name>this</name> <score>-5.26%</score> </word> <word> <name>is</name> <score>-0.87%</score> </word> <word> <name>a</name> <score>-0.16%</score> </word> <word> <name>test</name> <score>2.29%</score> </word> <word> <name>title</name> <score>-30.79%</score> </word> </titleresults>
The average number of links is ~299, and the scores are calculated by comparing the average number of links accumulated by stories using each keyword in their titles against the average. They’re displayed in percentage format.
WP-LAF
This is a plugin for the wordpress that checks a title against the LAF (Link Attraction Factors) database. The plugin will breakdown the words in your post title and display the effect they have on link accumulation.A plugin version of the LAF Title Check tool, it uses the XML API LAF database interface. For more information about the LAF database, read the report.
How to install WP-LAF
- 1. Extract the WP-LAF folder from the zip file
- 2. Upload the WP-LAF folder to your the plugins directory on your server
- 3. Click the ‘Activate’ link for WP-LAF on your Plugins page (in the WordPress admin interface)
So go, check them out and let me know what you think.
- Sneak Peak of Digg Link Acquisition Report
02/11/08
Above is a little sneak preview of data from a report I’m finishing up now and has been the reason my blog has been so quiet recently. (Click for a larger view).I’ve compiled a database of over 32,000 links that made Digg’s homepage in 2007 (a little over 37,000 total went popular last year) and the number of incoming links each page has. Then I dug into the data and discovered which factors (like time and day of submission, popularity of submission, topic, and the occurrence of certain words in the title and description) lead to higher or lower average incoming links.
The graph above shows the containers stories can be listed in on Digg and how many more (or less) links the average story submitted into those containers gets compared to the average story overall.
I will be selling the report as a PDF once I’m done with it, and it will include access to a tool that allows you to enter any keyword or phrase and it will return information about that word or phrase’s effect on the average number of incoming links a story gets.
If you’d like to pre-order the report, email me with a price you think is fair, if you have a fairly popular social media/internet marketing blog and you’d like to get a free review copy when its published, email me too.
If you think of any additional factors that may influence link accumulation comment them on this post and I’ll make sure I include them in the final report.
