Manifesto for the Reputation Society by Hassan Masum and Yi–Cheng Zhang

Information overload, challenges of evaluating quality, and the opportunity to benefit from experiences of others have spurred the development of reputation systems. Most Internet sites which mediate between large numbers of people use some form of reputation mechanism: Slashdot, eBay, ePinions, Amazon, and Google all make use of collaborative filtering, recommender systems, or shared judgements of quality.

But we suggest the potential utility of reputation services is far greater, touching nearly every aspect of society. By leveraging our limited and local human judgement power with collective networked filtering, it is possible to promote an interconnected ecology of socially beneficial reputation systems — to restrain the baser side of human nature, while unleashing positive social changes and enabling the realization of ever higher goals.

Contents

Introduction
Search
Communicating with peers
Filtering
Trade
Culture
Risks
Ideosphere
Conclusion

The emergence of reputation systems

How do we identify what is good? And how do we censure what is bad? We will argue that developing a humane reputation system ecology can provide better answers to these two general questions — restraining the baser side of human nature, while liberating the human spirit to reach for ever higher goals.

Most social interactions require matching human needs on the one hand, and quality or taste on the other hand: hunting for a reliable mechanic, looking for an interesting book, sifting through potential investments, judging the merits of proposed policies. Drawing from a distributed pool of reputations has the potential to ease the search for opportunities, ideas, friendships, cultural goods, and high–quality services; hand in hand, pressure will increase for honest behavior, competence, and fulfilling subtle human needs. At the same time, more efficient tagging of con artists, sources of spam, untrue claims, and dishonest actions can better sanction antisocial behavior, for the most part in a bottom–up "distributed court of opinion."

Sustained rapid advances in information technology have created unprecedented abilities, which come along with unprecedented dilemmas. Data has never been easier to create and move around, but to make decisions one also needs to understand its context and implications. Just as important is what lies behind its face value, in realms such as speculative bubbles (Chancellor, 2000), shady financial practices (Partnoy, 2004), and the political statements that are the topic of much of our public discourse.

Access has generally become easier, driven by falling production, communication, and search costs; however, there are consequently far more suggestions, demands, and events to consider, straining our individual information processing capacity. Leaving the computational milieu alone to evolve "naturally" is no guarantee that an ideal or even acceptable society–wide information infrastructure will emerge, as Brin (1999), Lessig (2001), Norman (1994), Schenk (1998), Stallman (2002), Walker (2003), and others have warned. To promote an interconnected ecology of socially beneficial reputation systems, conscious design, analytical modeling, and learning from past successes and failures is indispensable.

Filtering tools are still in their infancy — and having a better window to look out at the world can also imply that others can more easily peek in. Search engines speed up finding similar work done elsewhere; collaboration tools from humble mailing lists to community software to advanced groupware aid both individual and collective problem–solving. Yet it seems that for many important issues, all these tools are not keeping up with the increasing scale and number of decisions we must make, leading to what (Homer–Dixon, 2002) has referred to as an "ingenuity gap."

Sheer computation power is not enough — another factor of 1000 in speed, storage, or bandwidth translates to a more modest gain in making better decisions, and perhaps even a net loss in other forms of effectiveness. (Indeed, if the data or assumptions are noisy enough, the programming aphorism of "Garbage In, Garbage Out" applies.) Those who seek to use technology or the public space of ideas to advance their own agendas can also leverage increased computation power. There is indeed a technological revolution still in progress, reshaping commercial and social interactions — but its ultimate course will be affected by designers, activists, researchers and civil society at large. As (Fischer, 2002) said:

"Peter Drucker argued that "there is nothing so useless as doing efficiently that which should not be done at all." Adding new media and new technologies to existing practices will not change the consumer mindsets of learners and workers. We need to explore new computational media based on fundamental aspects of how we think, create, work, learn, and collaborate ... New tools should not only help people to do known cognitive tasks more easily, but they should lead to fundamental alterations in the way problems are solved."

In order for computational advances to translate to widespread social advances, the tools must confer the ability to "think smarter, not harder" — and use our collective evaluations of what is desirable to steer resources away from unproductive negative–sum games. Human brains provide an analogy: the difference between a moron and a genius lies primarily not in more or faster neurons, but in neurons that are wired together more effectively. In the same way, reputation systems are a generic tool that allow our observations, analysis, and actions to be "wired together" more efficiently.

What is special about the present time? A networked society that can easily share opinions and access reputations is making new applications possible, and new possibilities in turn generate interest in previously impractical solutions. Rising living standards have led to higher expectations. Increasing political, cultural, and personal freedom in many societies has encouraged the widespread ability to question customary choices, with the resulting ferment of millions discussing and seeking for better answers being a defining part of our zeitgeist.Finally, unprecedented challenges loom — global ecological issues, technologically–amplified terrorist threats, resource depletion, and the poverty of billions. Seeing that a better world is possible pushes us to solve challenges that we once might have resigned ourselves to.

The character of reputation

A vendor haggles with a prospective customer in the bazaar, shrewdly trying to estimate a closing price: the customer’s dress, mode of speech, degree of interest, and evident knowledge of the product all play a part. Simultaneously the customer tries to estimate how much the product is worth and what options the vendor has: the vendor’s location, store layout, knowledge, and guarantees can all modify the first impression of the product itself. In this age–old bargaining game, the image of both parties always looms in the background.

A press kit claiming development of a breakthrough cancer drug is received by a journalist. At first the temptation is strong to dump it straight in the waste basket; crackpots are a dime a dozen. But then a name jumps out from the page: one of the country’s most prominent investors has endorsed the science, along with a professor from a world famous university. The journalist’s skepticism turns quickly to interest.

Browsing through the new releases at the library, a grad student notes a book somewhat related to her thesis topic. Although it’s not directly relevant, the author has been widely quoted in newspapers — incentive enough to pick it up and read it.

All these examples share a dependence on reputation: of buyers and sellers, of investors and professors, of authors and ideas themselves. When in colloquial language we speak of a person’s "good reputation", we are implicitly claiming that the person fulfills many of his or her local society’s expectations of good social behavior — typically including qualities like honesty, reliability, "good moral character", and competence. (Note particularly the last — someone might be perfectly honest, sincere, and dedicated, yet still be mistaken or mediocre.)

Reputation is context–specific. A Ph.D. degree, medical license, or award of merit is meant to certify particular abilities. When a credit agency evaluates your financial history and generates a reputation, the context is your ability to repay loans; this ability may be correlated with but is quite distinct from more general character traits. And reputation could refer to any of these more general traits, like one’s sense of humor or ability to work in a team.

Since there is no absolute objective reputation quantity stamped on people’s foreheads, measurable proxies are necessary, such as book sales rankings, citations in academic papers, Web site visits, and readership of blogs. (Not coincidentally, they have similar highly asymmetric power–law distributions. Many distributions of wealth and of readership of non-electronic resources also follow power–law distributions, a fact noted in Zipf (1949) more than half a century ago.)

Reputation is a surrogate — a partial reflection representing our "best educated guess" of the underlying true state of affairs. Active evaluation by looking behind surface signals can corroborate or disprove reputations, while indiscriminate use degrades their reliability. The challenge is to encourage active evaluation, but also to use it efficiently since it will always be in limited supply.

Emerging information tools are making it possible for people to rate each other on a variety of traits, generating what is really a whole set of reputations for each person. (Information technology is also indirectly increasing the need for such reputations, as we have to sift through more and more possibilities.) You may mentally assign a friend a bad reputation for being on time or returning borrowed items promptly, while still thinking them reliable for helping out in case of real need. No person can be reduced to a single measure of "quality."

So people will have different reputations for different contexts. But even for the same context, people will often have different reputations as assessed by different judges. None of us is omniscient — we all bring our various weaknesses, tastes, bias, and lack of insight to bear when rating each other. And people and organizations often have hidden agendas, leading to consciously distorted opinions.

Reputations are rarely formed in isolation — we influence each others’ opinions. Studying the structure of social connectivity [1] promises to reveal insights about how we interact, and thinking about simple quantities like the average number of sources consulted before an opinion is formed will help us to better filter these opinions.

Are reputations only for people? No, their scope is far wider:

• They can be for groups of people: companies, media sources, non–governmental organizations, fraternities, political movements.
• They are often used for inanimate objects: books, movies, music, academic papers, consumer products. Typically, whenever we talk about the "quality" of an object with some degree of subjectivity, we can also speak of its reputation, usually as assessed by multiple users — bestseller lists are a simple example.
• Finally, ideas can have reputations. Belief systems, theories, political ideas, and policy proposals are the bedrock of public discussion. The waxing and waning of idea–reputations directly affects their likelihood of implementation, and thus the environment that we all share [2].

In the twentieth century, perhaps the two biggest changes in how reputations were formed came from the pervasive spread of mass media and from advances in information technology. For better and for worse, newspapers, radio, and television indisputably play a central role in forming reputations of people and ideas, through near ubiquitous broadcasting, advertising and branding. However, long–term effects of information technology are still very much in formation.

The Web lets us publish and actively access information — but if we wind up using the Web as just an alternative conduit for an expanded mass media, not much has changed. E–mail, chat, and future collaboration technologies are democratizing communication and discussion — but how many of our opinions on important issues are formed through discussion and how many from seemingly authoritative sources?

Reputation itself is changing. While feudal entitlements and class differences once had a fair chance of lasting for decades or even centuries, now a single major news story can make a star or break a career. And the sphere of interaction within which we need to have some reputational information is expanding, as trade, travel, and personal links go global. Computational tools — and the implicit "division of judgement" they enable — will help the same number of hours in the day go further. Just as we have greatly leveraged our natural human muscle power with mechanical energy, we will also leverage our limited and local human judgement power with collective networked filtering energy.

Why reputation systems matter

Each of us has limits: limited time, limited motivation, and limited ability to make sense of facts and observations. Brains adapted over millennia for hunter-gatherer roles are suddenly being forced to cope with the complex and frenetic rhythms of the information age. As the tasks we must solve in professional, private, and civic roles require more and more resources, we are less and less able to cope. Complex issues become oversimplified; opportunities are missed; hidden agendas and snake–oil salesmen become rampant. But most of the solutions required are not dependent on endlessly increasing the amount of data that each of us must process — such a world is a recipe for stress, general degradation of society, and progressive loss of control over our destiny.

And dealing with analytical issues is not the only problem. A whole class of difficulties arises from conflicts of interest between multiple parties — especially when distributions of power, influence, and information become overly asymmetric. Increasing social welfare has been a challenge for millennia, but now increases in scale, scope, and speed of interactions require compensating tools to keep parties honest and encourage accountability. There is as well a hierarchy of basic human needs (Maslow, 1998; Csikszentmihalyi, 1991) which could be addressed more effectively: finding friends and peers, seeking cultural and intellectual stimulation, challenging oneself.

We argue that all these issues and more could potentially benefit from the use of reputation systems, a process that is already underway and beginning to be researched; see Dellarocas and Resnick (2003); Perugini, et al. (2003); and, Terveen and Hill (2001) for surveys, and Masum (2002) for a previous general paper along similar lines. Reputation is a judgement of quality. It becomes more trusted to the extent it accounts for differing biases and abilities of reputation–formers, and differing tastes and needs of reputation–users. Each time we can use reputation instead of having to process and judge the underlying raw data, we save time and effort, and extend our reach and capabilities.

Reputation systems systematically combine many reputations, providing a point of access and enforcing "rules of the game." The information institutions that make these services available — formal and informal, for–profit and non–profit, private and public — will become pillars of the Reputation Society. The challenge is to first understand and then design, build and foster healthy reputation systems — to systematically benefit from the experience of others, and avoid stumbling through endless trial–and–error cycles. In a world where information institutions are often global (and can underpin critical infrastructure) the cost of avoidable failure is unacceptably high.

The process of filtering information to distill a smaller yet more refined set of usable, verified, trustworthy judgements is not easy. But it is doable. And it is both more feasible and more necessary now than ever before, due to information proliferation, technological advances, and pressing socio–economic problems. Indeed, we already see many types of reputation systems emerging, especially online:

• Slashdot has grown to be a prime tech news site largely because of its inspired combination of open contribution and bottom–up filtering, using a modest amount of effort distributed over a large number of people — ranking the thousands of daily comments so one can choose to read just a few gems or all contributions. Similar communities are arising with different focuses, and figuring out why some fail while others succeed will teach us valuable design lessons.
• Amazon, the online bookselling pioneer that has grown to be a juggernaut, early on made a decision to let users themselves rate each item, optionally accompanied by comments. Browsing through these ratings, suggestions, and warnings can be a gold mine of useful tips, one that is hard to replicate.
• eBay uses reputations at the heart of its online auction system, for ranking buyer and seller honesty. Without this feedback, weeding out the bad apples who renege on deals would be far more difficult.
• Google uses derived reputations from Web page interlinking to decide which search results are most relevant, which proved so effective that it has rapidly grown to become a global information utility. It has no "community boundaries," but extends use of reputation to the Web in its entirety.
• BizRate and ePinions provide ratings of businesses, seeking to identify those with better product quality and customer service. Both depend on feedback from many consumers, summarizing the experiences of many and in turn influencing future purchasing decisions of consumers in a virtuous feedback loop.

All these sites and more owe a big part of their usefulness to the large–scale use of reputation: to schemes for emphasizing what is perceived to be better, as measured by the explicit and implicit contributions of millions of users. If a reputation system is honest and well–designed, information filtering using a huge pool of individuals can be more stable, reliable, and insightful than the opinions of a small group of gatekeepers or pundits. In the early twenty–first century, lower costs for search, coordination, and evaluation are making previously unthought–of applications feasible — just as happened with the Internet in the 1990’s.

The goal, then, is to devise ways of reducing the gap between reputations and reality. A good reputation system will take account of real–world limitations — scarce ratings, differing tastes, people gaming the system — and still manage to create reputation signals that are close enough to reality to be useful.

Search

Popularity vs. obscurity

Information transport has developed steadily, from shipping books and brains around, to telecommunications, to the Internet and beyond. Network protocols and skyrocketing bandwidth have more or less solved the transport of raw data, but we continue to grapple with a far harder problem: finding which data is relevant. And there is a lot of data to sift through, most of which never even gets printed (Lyman and Varian, 2003). With growing interconnectedness and increasing scope of problems to solve, there is a pressing need for better tools than the occasional "best–of list" for finding high–quality resources.

Steam engines heralded the Industrial Revolution more than two centuries ago. A diversity of power devices took over most of their functionality, but all still obey the same thermodynamic laws. Today, search engines play a similar role as universal information–powering devices, and merit special attention. It took many decades of trial and error and incremental evolution before reliable engineering solutions developed for steam engines, and even longer for theoretical understanding of efficiency limits and thermodynamics. Search in particular and Reputation in general await a similar theoretical science. The future may find other institutions or mechanisms to handle information matching, but the challenges posed to search engines today will survive the specific engines themselves.

It must be possible to find reputational information on a category of interest easily — even slight increases in the transactional cost of effort required can reduce usage of reputations. In early 2004, an illustrative example was the antitrust probe of the European Commission into Microsoft. One key claim that led to the imposition of penalties was that Microsoft’s tying of Windows Media Player to its Windows operating system made it difficult for alternative programs to compete on merit (EU, 2004). The implication is that even the few minutes of extra search effort for users to find alternatives was in practice enough to dissuade many.

This suggests a fundamental dichotomy between searching for static, long–lasting objects like books and secure databases (which can safely remain in storage for decades, ready to be picked up again if someone becomes interested) and more ephemeral talents, ideas, or organizations which may wither away for lack of interest if no one seeks them out. Like flowers, many ventures need to bask in the light of human involvement to survive.

Similarly, there is a difference between predefined knowledge that comes in neatly labeled packages, and searching for more organic or abstract knowledge which may need to be pieced together from various sources. Finding a book with a known author or title is easy; much harder is finding works about an interdisciplinary or hard–to–define area, or judging quality and relevance. Those ideas which are hard to find naturally suffer a judgmental penalty; it is difficult to rate an item that is hard to find. Both ephemeral and abstract objects are also more at risk for being actively manipulated by interested parties, since they can more easily decay or be distorted.

It is instructive to start by looking at centuries of experience in information retrieval, which provide a rich base of time–tested tools for "finding out about" (Baeza–Yates and Ribeiro–Neto, 1999). The indices used to arrange books in libraries today are generally topical and hierarchical — for example, science books start with "Q" in the Library of Congress classification system, but "QA75" and "QA76" are reserved for "calculating machines," an archaic category which now includes computer science and software. When computer science first arose, defining it as a rather esoteric subfield of mathematics (which occupies the rest of the "QA" section) made sense. However, in the early twenty–first century, these two numbers are probably larger and more rapidly growing than anything else between QA1 and QA999. Once fixed and widely adopted, changing a cataloging system is a major undertaking — and the categories used affect an idea’s "default reputation."

The simple Boolean method, used in older library systems, considers a document as a list of keywords. It searches indexed documents with queries composed of keywords along with the operators AND, OR, and NOT — for example, "(climate AND change) NOT warming" could give climate change information other than global warming. While both simple and fast, this method often returns too few or too many documents, and doesn’t rank search results. This can amplify the popularity of a few well–known references, as searchers who are pressed for time settle for what is better–known or what comes up first with the most obvious keywords.

Adding consideration of keyword frequency — both the number of times each occurs within a document, and the relative frequency between different documents — gives the better-performing vector space model [3]. More sophisticated approaches can be built on these ideas, many of which are used in current search engines; for example, keywords occurring in titles or other prime locations are usually a sign of high relevance. Since queries like "information overload" and "data smog" probably refer to similar ideas, keywords can be mapped to more general categories, making it easier for once separate subdisciplines to recombine and share ideas on what is important.

Search engines and link–based reputation

Let us turn now to the emergence of search engines, and the radical decrease they bring in certain search costs. When the Web first arose, there were few roadmaps — each user decided what to put up and who else to link to in a vast bottom–up creative construction. But navigating through a land with no signposts was difficult.

The physical routing problem — going from a URL or IP address to the corresponding computer, located anywhere — had been solved so well that it operated behind the scenes most of the time. However, the separate pieces of the Web built on top of this physical layer lacked connective tissue — the paths, roads, and maps that would allow users to find what they were looking for, and to know what there was to be found. And this in turn meant that information on which resources were good could not spread easily.

Many search–assisting sites arose. Yahoo! and the Open Directory Project were human–edited directories of links with hierarchical topic directories. But like a spinning loom factory in the dawn of the Industrial Revolution, they required too much manual attention, covering an ever smaller percentage of sites as the Web grew. Altavista remedied this problem by trying to crawl all reachable sites to form a giant automated index; while useful for targeted search, the numerous results for more general queries rendered it difficult to use as an exploratory tool. An unmet demand for sorting search results by relevance and quality steadily built up — and when Google supplied an easy–to–use solution, it grew rapidly to become a global information utility.

Consider an arbitrary Web page — how can we estimate its quality? A breakthrough in increasing search result relevance came from the development and implementation of PageRank, as outlined in Brin and Page (1998). The basic idea behind PageRank is to estimate reputation of a page using both the number and quality of other pages it is linked to [4], building on insights from citation analysis and information science.

The crucial feature of all this link information is that it summarizes a huge number of independent choices. The creator of each Web page has a choice of which other Web pages to link to, and normally one would choose to link to higher–quality pages — so every incoming link to the page in question is an implicit vote of confidence. In a complementary way, suppose the page in question links to a lot of other high–quality pages — these are probably useful to a reader, and should hence also increase its score.

The beauty of this type of scheme is that it implicitly leverages the writers of all publicly accessible Web pages — their collective selecting (Park, 2002), sifting, and evaluating is observed via the resulting link information. The filtered opinions of millions create Web page reputations that have helped make Google a global icon — and that affect how the page popularity distribution and link structure of the Web itself evolves over time.

Do link–based heuristics always work? Certainly not. All such heuristics are just approximations — a page could be good, yet still not satisfy some or all of the criteria. For example, the basic algorithm above will assign a low rank to a page that is high–quality but too new to have gathered many links yet, or one that is thoughtful but too difficult to be appreciated by most Web users. Along with other popularity–based methods, it also suffers from the "preferential attachment" problem: since Web pages that become popular will be returned first in the list of search results, they will tend to become even more popular, independently of their underlying quality. More sophisticated search algorithms are continually under development (Roush, 2004).

Similar search dynamics play a part in many other information resources, from academic citations to searching for new music to the market for books. While library catalogs are still as useful as ever, in 2004 Amazon.com is one of the most often used resources for purposes of book search — to look up bibliographic information, to search for books that are related to a given book of interest, or to browse books in a new field. User rankings and the way that Amazon orders query results influence which items people are likelier to buy.

Search engines also use other heuristics to try to figure out which sites are better in quality, and which sites best match a user’s query. One can consider factors like where the search terms occur in the document, how long the resource has been available, what format the resource is in, where it’s from, and so on. In fact, it’s common to use many of these same heuristics when searching in a library or bookstore for information about a new subject — from a glance or quick flip through the book, we use the typeface, layout, size, tone, publishing company, and many other more subliminal factors to estimate quality.

Masquerading and coevolutionary search

While academics have used citation tricks like cross–referencing cliques for decades, the commercial Internet has triggered a larger shift from static information "sitting there waiting to be noticed" to a co–evolutionary race between ways of finding relevant information and ways of getting noticed by the finders. This is part of a general pattern: when others are seeking positive search results to reward, we naturally emphasize ourselves and discount others; conversely, when others seek negative search results like blacklisted businesses to stay away from, we naturally try to stay off their radar. Like a masquerade ball, we seek to present the best appearance, while trying to imagine what might lie behind the masks of others.

Frequently people modify their pages in a deliberate attempt to improve search engine rankings. (A number of "hacks" are possible, as discussed in Calishain and Dornfest (2003); though largely about ways of using Google more cleverly, the information can also be applied to try to skew one’s ranking.) The possibility of inflating rankings has led to an arms race where Google updates its algorithms to counter abuses, another weakness is found which Google again combats, and so forth. Yet despite all these flaws, search engines are empirically quite useful, and for many purposes work well enough to meet users’ needs.

Clearly, being a gateway to the Web provides an opportunity for influencing what gets found and what gets ignored. The most obvious temptation is to skew search results based on payment, so that those Web sites that pay more appear earlier than they otherwise would. (This has been tried by some search engines.) Making a site just modestly more difficult or easier to find can have a major impact on its popularity, since people usually stop looking after relatively few results. The challenge for Google and other top engines is thus to keep answering the question, "Who evaluates the evaluators?", with the same answer: "Everybody."

As Simon (1996) pointed out, we usually "satisfice" instead of optimizing difficult problems due to limited time and insight, settling for a solution that is good enough. The "findability" of information biases its perceived quality — studies such as Lawrence (2001) suggest that papers available online are several times more likely to be cited than those offline (though there may be a self–selection effect where authors publicize only their better papers).

The search applications we have seen so far are only the tip of the iceberg. Classical information retrieval and many Web search tools deal with finding exact matches to specified queries. The better search engines modestly generalize exact matching, by also considering limited forms of approximate matching and quality indicators. Personalizable search engines of the future will find items satisfying more general properties:

• A business partner, with liquidity, skills, and the right personality.
• A list of opportunities matching your interests and abilities — charitable, professional, or personal.
• An employee or graduate student, with talent, insight, and a strong work ethic.
• A game partner, with matching ability level and tastes.
• News items, whose topic is most important and interesting relative to your point of view, and whose author is most authoritative and clear.
• Representatives of opposing points of view (Gerhart, 2004).
• An expert advisor, with a history of solving tough problems and a list of satisfied clients.
• The most urgent and ignored problems in a given field.

A big part of transaction costs in personal, commercial, and civic life is finding the right challenge to tackle, or the right partners. Indeed, in Zhang (2001) we suggest that the first part of the Internet Age was about people connecting computers, while the second (still just beginning) is about computers connecting people — and the ever more powerful computing resources pouring into society can be productively harnessed toward matching people together to their mutual benefit. "Search" in the broader sense of the term eases a whole range of difficulties which collectively sow confusion in the world.

Finding high quality options requires active search. If we’re content to take whatever is given to us, the other party has no incentive to improve. If we’re content to stick with the status quo and not search for alternatives, new products and ways of doing business will have a difficult time getting started. And if we’re content to accept any explanation given without questioning too hard, those who have power will always be tempted to make reassuring noises instead of doing the hard work of living up to what they say.

Communicating with peers

Virtual connections

What were the public places where people once formed reputations? Taverns, town squares, bazaars, and places of worship. Now, the Internet "idea bazaar" is creating many oases of discussion, and a few of real community.

From our point of view as observers and developers of reputation mechanisms, a key connecting thread is the varied solutions developed to the problem of raising discourse quality. Another thread is motivation for contribution; common rewards include peer esteem, making social connections, and the natural pleasure of helping others. To the degree that a conversational community has stable and important reputations for individuals (e.g., a relatively intimate mailing list), or has a reputation for the community as a whole by helping to create a public good (e.g., Wikipedia), there is more flexibility as reputation and other motivations substitute for direct reciprocity.

Mailing lists and newsgroups formed some of the earliest online communities, and are still quite active; their history and social functions are described in Rheingold (2000). Those who organized such communities had to solve many problems which characteristically arose past a certain size. Flaming is the term given to rude, overly emotional, or excessively argumentative replies to a posting; flamers may be socially shunned, or each reader may individually choose to place them in a "bozo filter" so that the reader is automatically shielded from their future postings. Newcomers to the list may ask questions which have previously been discussed ad nauseum; for this, the FAQ (Frequently Asked Questions) was developed, and is frequently a repository of high–quality information about the group’s topic.

Choosing to make a list or newsgroup moderated is a general strategy that combats all these issues: if every post must be approved, then off–topic, flame, and spam posts are much less likely to appear. However, moderation introduces its own problems, such as time (a busy list may require a lot of supervision from moderators), and taste (moderators have their own preferences and agendas which may differ from the rest of the group). Another type of moderation is by restricting access to the community as a whole, perhaps by requiring a recommendation from an existing group member or by voting on new admissions.

In a pattern that recurs in most cohesive communities, local experts often arise in newsgroups — people who because of their knowledge, eloquence, or wisdom come to be respected for the value of their postings. Thus there arises an informal but nonetheless real degree of positive reputation for those who have the capability and energy to contribute high–quality material. Modern conversational software harkens back to hunter–gatherer days when tribal leaders could arise rapidly through wit, cunning, and brute strength — as in the earliest times, most of us come into online communities "naked", and prove ourselves in a relatively level playing field.

Chat provides a more real–time discussion format. Chatting with a small group of friends or co–workers can be a productive experience. At the other extreme is participation in a large, open chat room, where drivel seems to scroll unendingly on the monitor. Usually, taking part in a restricted access conversation increases the potential level of trust, especially if the identities of the participants are known.

The reputation of a chat venue depends partly on its stability; if identities are persistent, if it is difficult for outsiders to break up good conversations with inane or off–topic remarks, if there is quality control on those entering, then (just as with real–life communities) the chat venue will come to be seen as a place worthwhile. Of course, a chicken–and–egg problem exists — it’s hard to attract good people without a reputation for high–quality conversation, but such a reputation is difficult to form without good people. Worthwhile communities are emergent phenomena.

SMS and instant messaging services form an interesting special case of chatting, usually being terse yet accessible anywhere. Although it’s hard to see deep discussions taking place in this medium, the ubiquitous availability could alter reputations in real time of a person or event — or even government if the sparks catch fire, as discussed in the case of the Philippines and elsewhere in Rheingold (2003). One could speculate on the potential effectiveness of a large group of connected people, with strong motivations (such as in a conflict, celebration, or natural disaster), all of whom are using some collaborative protocol that enables rapid decision–making for a crowd. These tactics have been seen in protest movements, and are reminiscent of swarm models (Bonabeau, et al., 1999).

Blogs (an abbreviation of "Web log") are structured forms of Web pages, which usually feature some combination of links to other bloggers, links to stories or items with personal commentary, feedback from readers, and a diary–like format. This combination of features gives them a story–telling feel, and perhaps makes it easier for readers to assess the personality of the person behind the blog; in turn, the implicit reputation formed by one’s blog is a valuable tool for making new and talented acquaintances. (See Rodzvilla (2002) for a collection of blog perspectives.)

Tools have been developed to derive ratings, with a simple method inferring higher ratings for items referred to more often. Due to their relatively lightweight nature — many blog postings consist of just a paragraph and a link or two — blogs often operate at a faster time scale than Web pages, and so the derived ratings from who–links–to–whom information can provide near real–time rankings of breaking news. This in turn can feed back to the community and focus attention of other bloggers; a blog is only as powerful as its reader base. Those blogs that specialize in current events and analysis can be seen as complementary to mainstream media, with a smaller but more focused audience.

Enabling technologies for blogs allow easy syndication of articles, so that one can easily track new stories from a personally chosen selection of dozens or hundreds of other sites (Rittenbruch, et al., 2003) . This "self–amplifying Web of respect" may allow for more effective group discourse, though as Blood (2003) discusses, there is a danger of becoming trapped in "echo chambers" of like–minded discussion partners. In fact, if methods can be found to improve their filtering and to consolidate conversational threads across multiple blogs into contextualized narratives, the structure of blogs as public discourse scaffolds may well make them powerful building blocks for honing large–scale ideas.

Scaling up: Conversations among millions

No discussion of online discourse would be complete without looking at Slashdot. This bottom–up news site, self–described as "News for Nerds — Stuff that matters," showed how hundreds of thousands of users could contribute toward readable commentary on technological and science developments. The operation of the site is straightforward: anyone can suggest a news item to be featured on the front page, but only a small number of suggestions are chosen by the site administrators. Then, all users can comment on the news story, or on each other’s comments.

Due to the large number of visitors, stories routinely receive