[Air-l] I'm researching virality in social networks - suggested papers?

[John Veitch]

George Floros wrote:
> John Veitch said
>> AC Nielsen report  "In most online communities, 90% of users are lurkers 
>> who never contribute, 9% of users contribute a little, and 1% of users 
>> account for almost all the action".

Hello George

First of all an apology, on checking I find the source is Jakob Nielsen 
not AC Nielsen.

It's one of his Allertbox Reports on useit.com
http://www.useit.com/alertbox/participation_inequality.html
Here is the full  text.

"Participation Inequality: Encouraging More Users to Contribute
     Summary:
     In most online communities, 90% of users are lurkers who never 
contribute, 9% of users contribute a little, and 1% of users account for 
almost all the action.

All large-scale, multi-user communities and online social networks that 
rely on users to contribute content or build services share one 
property: most users don't participate very much. Often, they simply 
lurk in the background.

In contrast, a tiny minority of users usually accounts for a 
disproportionately large amount of the content and other system 
activity. This phenomenon of participation inequality was first studied 
in depth by Will Hill in the early '90s, when he worked down the hall 
from me at Bell Communications Research (see references below).

When you plot the amount of activity for each user, the result is a Zipf 
curve, which shows as a straight line in a log-log diagram.

User participation often more or less follows a 90-9-1 rule:

     * 90% of users are lurkers (i.e., read or observe, but don't 
contribute).
     * 9% of users contribute from time to time, but other priorities 
dominate their time.
     * 1% of users participate a lot and account for most contributions: 
it can seem as if they don't have lives because they often post just 
minutes after whatever event they're commenting on occurs.

Early Inequality Research
Before the Web, researchers documented participation inequality in media 
such as Usenet newsgroups, CompuServe bulletin boards, Internet mailing 
lists, and internal discussion boards in big companies. A study of more 
than 2 million messages on Usenet found that 27% of the postings were 
from people who posted only a single message. Conversely, the most 
active 3% of posters contributed 25% of the messages.

In Whittaker et al.'s Usenet study, a randomly selected posting was 
equally likely to come from one of the 580,000 low-frequency 
contributors or one of the 19,000 high-frequency contributors. 
Obviously, if you want to assess the "feelings of the community" it's 
highly unfair if one subgroup's 19,000 members have the same 
representation as another subgroup's 580,000 members. More importantly, 
such inequities would give you a biased understanding of the community, 
because many differences almost certainly exist between people who post 
a lot and those who post a little. And you would never hear from the 
silent majority of lurkers.

Inequality on the Web
There are about 1.1 billion Internet users, yet only 55 million users 
(5%) have weblogs according to Technorati. Worse, there are only 1.6 
million postings per day; because some people post multiple times per 
day, only 0.1% of users post daily.

Blogs have even worse participation inequality than is evident in the 
90-9-1 rule that characterizes most online communities. With blogs, the 
rule is more like 95-5-0.1.

Inequalities are also found on Wikipedia, where more than 99% of users 
are lurkers. According to Wikipedia's "about" page, it has only 68,000 
active contributors, which is 0.2% of the 32 million unique visitors it 
has in the U.S. alone.

Wikipedia's most active 1,000 people -- 0.003% of its users -- 
contribute about two-thirds of the site's edits. Wikipedia is thus even 
more skewed than blogs, with a 99.8-0.2-0.003 rule.

Participation inequality exists in many places on the Web. A quick 
glance at Amazon.com, for example, showed that the site had sold 
thousands of copies of a book that had only 12 reviews, meaning that 
less than 1% of customers contribute reviews.

Furthermore, at the time I wrote this, 167,113 of Amazon’s book reviews 
were contributed by just a few "top-100" reviewers; the most prolific 
reviewer had written 12,423 reviews. How anybody can write that many 
reviews -- let alone read that many books -- is beyond me, but it's a 
classic example of participation inequality.

Downsides of Participation Inequality
Participation inequality is not necessarily unfair because "some users 
are more equal than others" to misquote Animal Farm. If lurkers want to 
contribute, they are usually allowed to do so.

The problem is that the overall system is not representative of Web 
users. On any given user-participation site, you almost always hear from 
the same 1% of users, who almost certainly differ from the 90% you never 
hear from. This can cause trouble for several reasons:

     * Customer feedback. If your company looks to Web postings for 
customer feedback on its products and services, you're getting an 
unrepresentative sample.
     * Reviews. Similarly, if you're a consumer trying to find out which 
restaurant to patronize or what books to buy, online reviews represent 
only a tiny minority of the people who have experiences with those 
products and services.
     * Politics. If a party nominates a candidate supported by the 
"netroots," it will almost certainly lose because such candidates' 
positions will be too extreme to appeal to mainstream voters. Postings 
on political blogs come from less than 0.1% of voters, most of whom are 
hardcore leftists (for Democrats) or rightists (for Republicans).
     * Search. Search engine results pages (SERP) are mainly sorted 
based on how many other sites link to each destination. When 0.1% of 
users do most of the linking, we risk having search relevance get ever 
more out of whack with what's useful for the remaining 99.9% of users. 
Search engines need to rely more on behavioral data gathered across 
samples that better represent users, which is why they are building 
Internet access services.
     * Signal-to-noise ratio. Discussion groups drown in flames and 
low-quality postings, making it hard to identify the gems. Many users 
stop reading comments because they don't have time to wade through the 
swamp of postings from people with little to say.

How to Overcome Participation Inequality
You can't.
The first step to dealing with participation inequality is to recognize 
that it will always be with us. It's existed in every online community 
and multi-user service that has ever been studied.

Your only real choice here is in how you shape the inequality curve's 
angle. Are you going to have the "usual" 90-9-1 distribution, or the 
more radical 99-1-0.1 distribution common in some social websites? Can 
you achieve a more equitable distribution of, say, 80-16-4? (That is, 
only 80% lurkers, with 16% contributing some and 4% contributing the most.)

Although participation will always be somewhat unequal, there are ways 
to better equalize it, including:

     * Make it easier to contribute. The lower the overhead, the more 
people will jump through the hoop. For example, Netflix lets users rate 
movies by clicking a star rating, which is much easier than writing a 
natural-language review.
     * Make participation a side effect. Even better, let users 
participate with zero effort by making their contributions a side effect 
of something else they're doing. For example, Amazon's "people who 
bought this book, bought these other books" recommendations are a side 
effect of people buying books. You don't have to do anything special to 
have your book preferences entered into the system. Will Hill coined the 
term read wear for this type of effect: the simple activity of reading 
(or using) something will "wear" it down and thus leave its marks -- 
just like a cookbook will automatically fall open to the recipe you 
prepare the most.
     * Edit, don't create. Let users build their contributions by 
modifying existing templates rather than creating complete entities from 
scratch. Editing a template is more enticing and has a gentler learning 
curve than facing the horror of a blank page. In avatar-based systems 
like Second Life, for example, most users modify standard-issue avatars 
rather than create their own.
     * Reward -- but don't over-reward -- participants. Rewarding people 
for contributing will help motivate users who have lives outside the 
Internet, and thus will broaden your participant base. Although money is 
always good, you can also give contributors preferential treatment (such 
as discounts or advance notice of new stuff), or even just put gold 
stars on their profiles. But don't give too much to the most active 
participants, or you'll simply encourage them to dominate the system 
even more.
     * Promote quality contributors. If you display all contributions 
equally, then people who post only when they have something important to 
say will be drowned out by the torrent of material from the hyperactive 
1%. Instead, give extra prominence to good contributions and to 
contributions from people who've proven their value, as indicated by 
their reputation ranking.

Your website's design undoubtedly influences participation inequality 
for better or worse. Being aware of the problem is the first step to 
alleviating it, and finding ways to broaden participation will become 
even more important as the Web's social networking services continue to 
grow.

Learn More
Full day tutorial on what designers can learn from social psychology at 
the User Experience 2006 conference in Seattle and London.

References
Laurence Brothers, Jim Hollan, Jakob Nielsen, Scott Stornetta, Steve 
Abney, George Furnas, and Michael Littman (1992): "Supporting informal 
communication via ephemeral interest groups," Proceedings of CSCW 92, 
the ACM Conference on Computer-Supported Cooperative Work (Toronto, 
Ontario, November 1-4, 1992), pp. 84-90.

William C. Hill, James D. Hollan, Dave Wroblewski, and Tim McCandless 
(1992): "Edit wear and read wear," Proceedings of CHI'92, the SIGCHI 
Conference on Human Factors in Computing Systems (Monterey, CA, May 3-7, 
1992), pp. 3-9.

Steve Whittaker, Loren Terveen, Will Hill, and Lynn Cherny (1998): "The 
dynamics of mass interaction," Proceedings of CSCW 98, the ACM 
Conference on Computer-Supported Cooperative Work (Seattle, WA, November 
14-18, 1998), pp. 257-264.


-- 
"John Stephen Veitch"
http://www.ate.co.nz
Should we be talking?
By all means Google me.