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Book Description Cambridge University Press, New Book. Delivered from our UK warehouse in 4 to 14 business days. Established seller since Seller Inventory LQ Shipped from UKs. Book Description Thus Pagerank mines and aggregates the results of human judgments as expressed through link creation, and uses it to assess the importance of pages and determine the order in which to display them. This is an early, and very notable, example of the recognition that the digital actions of a large number of people can be tapped to provide a valuable service.
Social activity is a fundamental aspect of human life. Not surprisingly, digital systems have accommodated such activity for decades, initially serving as platforms that supported online conversation and other collaborative activity. This is abstract, so let us look at a common example, that of the online retailer Amazon. As most readers will be aware, Amazon is an online department store that sells a wide variety of goods, as well as providing an online storefront for other retailers. Amazon enables its users to create online product reviews.
Each review consists of a textual essay, a rating of 1 to 5 stars, and the name of its author. Products may garner many reviews — for example, the best-selling book, The Girl with the Dragon Tattoo , has amassed over reviews. And readers, in fact, do this. Using this information, Amazon provides two user interface components that significantly increase the utility of the user-entered information Figure 1. Copyright terms and licence: Unknown pending investigation. See section "Exceptions" in the copyright terms below.
Figure 4. These components — which rely on computations carried out on user input — make it easier for viewers to deal with large amounts of user-generated content. The first integrates the results of all reviews of a book, providing not only the average rating but also the more informative distribution of ratings.
All in all, these mechanisms produce virtuous circles: positive feedback loops that promote desirable results. This aptly illustrates the phase shift that began around the year Amazon takes this approach as well, when it uses the purchase history of a user to identify those with similar histories, and then provides users-like-you-also-bought recommendations. However it occurs, this ability for the information produced via social interaction to be processed and re-used by the system supporting that interaction is the hallmark of present day social computing.
Why does social computing matter? Besides the fact that the social interaction supported by social computing systems is intrinsically rewarding, there are a number of ways in which social computing systems can provide value over and above that offered by purely digital systems. First, social computing systems may be able to produce results more efficiently. Because Amazon can draw on its entire customer base for book reviews, it can provide far more reviews far more quickly than relying on the comparative trickle of reviews produced by Publishers Weekly and other trade outlets.
The Girl with the Dragon Tattoo received five reviews within a month of its publication in English, long before it emerged from obscurity in the English language market. Similarly, Wikipedia, the online encyclopedia, offers over three and a half million articles in the English edition, and can generate articles on current events literally overnight. As of this writing, nearly ten weeks after the event, the article has been edited over 5, times by over 1, users, and has references; in the last 30 days it has received nearly , views.
A second way in which social computing can be of value is by increasing the quality of results. MatLab is a commercial software package for doing mathematical analysis that uses its own scripting language, and one way its developers promote it is by running a programming contest. Each contest poses a problem, and the challenge is to produce a program that solves it as quickly and completely as possible. Contestants submit the MatLab source code of their programs, and the programs are immediately evaluated, scored, and listed in order of their scores.
The new tweaked program can be submitted, and it and its author will thereby vault ahead of the originator into first place until another contestant tweaks that entry. As this tweaking process is repeated dozens of times e. Following the introduction of a new algorithm variants shown in red , contestants refine it, gradually and noisily optimizing the algorithm adapted from MatLab Central A third way in which social computing systems can provide value is by producing results that are seen as fairer or more legitimate.
Another example is the online auction, where multiple people bid for an item — those who lose out may not like the result, but few will argue that it is not legitimate. Stepping out of the digital realm for a moment, note that the rationale for the plebiscites on which democracies are based is not that they produce more rapid decisions, nor that the decisions are necessarily of higher quality, but rather that they are representative and reflect the popular consensus.
It is notable that the value of plebiscites and auctions and even the Amazon review process can be invalidated by failures in their processes — ballot box stuffing, vote buying and other forms of fraud in elections; shills in auctions; and collusion among bidders and reviewers. In cases like this, it is the legitimacy of the result that has been undermined; demonstrating that the decision was arrived at more quickly or is of higher quality is immaterial. In this case the value of the product is contingent upon the process through which it was derived. A fourth way in which social computing provides value is by tapping into abilities that are uniquely human.
For example, the ESP Game Ahn and Dabbish , which we will discuss in more detail shortly, is an online game in which a user and an anonymous partner look at an image and try to guess the words that occur to the other person. Other examples are Galaxy Zoo Galaxy Zoo , Priedhorsky et al , which asks people to classify galaxies in astronomical photographs by their shapes, and Investigate Your MP Guardian - guardian.
To sum up, there are different ways in which social computing systems may produce value: they may produce results more quickly by multiplying effort; they may produce higher quality results by integrating knowledge from multiple participants; they may produce results that are more legitimate by virtue of representing a community; and they may carry out tasks that are beyond the capacity of current digital systems by drawing on uniquely human abilities. But while this value is of great practical import, it should not obscure the most important aspect of social computing: the social interaction itself.
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Greater efficiency, quality and legitimacy are important benefits, but the reason most people engage with social computing systems lies in the give and take of the interaction itself, the meaning and insight we derive from it, and the connections with others that may be created and strengthened as its result. The shift to social computing is, at the heart, driven by the ability of digital systems to process the products of the social interaction they support.
The products of social interaction have been made digitally tractable, either by dint of digital computation e. Up to this point our principal example of social computing has been Amazon. However, while Amazon has been enormously successful at making use of social computing mechanisms, if one removed all elements of social computing from Amazon, it would still be able to carry out its basic aim of selling goods online.
The art of designing this type of social computing system lies in finding a domain with a difficult problem that can be solved by the massive repetition of a simple for humans task, and in figuring out how to motivate the human participants to carry out a simple task many times.
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The ESP Game is notable both for its practical success and for the subtleties of design that underlie its apparent simplicity. At a high level the ESP Game sets out accomplish the task of assigning textual labels to images on the web. This is a task that is difficult for computers to perform, but easy for humans.
However, while easy for humans, it is not a task that is very interesting to perform, which given that there are billions of images in existence constitutes a problem. What the ESP Game does is to reframe the image labeling process as a game, and by making it fun it succeeds in recruiting large numbers of people to label images. In fact, in its first 5 years of existence, , people used it to produce more than 50 million image labels Ahn and Dabbish The ESP Game works as follows.
A user goes to the web site, where, after a brief wait, he or she is paired with an anonymous partner and the game begins Figure 3. Each game lasts three minutes, and both participants receive points each time they match on a word. If the other player enters one of the same words, there is d a match, and both players get points.
If it seems too difficult to come up with good guesses, either player can e pass. After a game ends the players go their separate ways, each seeing a screen Figure 4 that recaps how well they did, both in the individual game, and in a cumulative score for all games played. At the end of the game, players are shown a their points, b their level, c points needed to achieve the next level and d to beat the best player of the day d. Players can also earn points by e referring friends. The ESP Game has a number of design features that illustrate issues that social computing systems, in general, must address.
As we shall see later, different systems may address these issues differently, but the ESP Game provides a good starting point for grounding this discussion. Social computing systems carry out various forms of work to produce value, often by applying algorithms to the results of user-generated content. The ESP Game performs computations by incenting individuals to use their perceptual and cognitive abilities to generate possible labels for an image, and aggregating results across many games to produce a valuable outcome.
This is a result that cannot be achieved by purely digital systems.
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The ability of a social computing system to produce value relies on user-generated content, and that means that the system must take measures to ensure that it has a sufficient number of users who are motivated to participate. This was not an issue for Amazon, because the Amazon review mechanism is embedded in the larger Amazon ecosystem, and it happens that some of those attracted to Amazon by its function as an online retailer are interested in reviewing products. This is not the case with the ESP Game — it must do all the work of attracting people.
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It does this via its use of game-like incentive mechanisms to recruit and motivate its players. Once potential players arrive at the site the problem shifts to engaging them in the game. To that end the ESP Game is nicely designed with bright colors, snappy interaction and appropriate sounds.
Many of its features — the limited time, the awarding of points for right answers, a graphical scale showing cumulative points, and the sound of a clock ticking during the final moments of the game — work to motivate the users during game play. Participants in a social computing system generally require identities through which to engage in interaction with others, and identity — especially identity that persists over time — is also bound up with motivation and reputation.
The ESP game is actually a relatively low-identity example of a social computing system, in that its participants are not allowed to talk with one another while playing the game, so as to deter cheating. Nevertheless, the ESP Game does take pains to support identity and reinforce the social aspects of the game. As noted, players can register, creating a screen name, an icon, and other elements of a profile. While communication between a pair of players during the game is prohibited, players can join a chat room for the site as a whole the ESP Game is part of a site called Games with a Purpose.
More generally, the design shows the presence of others.
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Like the incentive mechanism, these social features aim to increase the attraction and interest of the site. But suppose you show up for a game and there is no one to play with? This is a problem in that not only can the game not take place, but the player who has come to the site may now be less likely to return. The game that ensues will use images that have already been labeled by at least one pair of human players, and the bot will simply replay the responses and timings of one of the previous players, giving the human partner the experience of playing against someone else. This use of bots supports the experience of the game, and has another use that we will look at shortly.
Another issue that social computing systems need to deal with is how to focus or otherwise shape the activities of their users. In the ESP Game, this is done via taboo words. As already described, taboo words serve to increase the breadth of the set of labels generated for an image by ruling out those that many previous pairs of players have produced.
Taboo words also shape the set of labels produced in a more subtle way: they can prime players to pay attention to certain aspects of the image Ahn and Dabbish e. The ESP Game could use other approaches to focusing work such as selecting images from particular known sets e. Many social computing systems have mechanisms, of one sort or another, that try to focus or otherwise control the nature of the computation the system performs.
While humans can perform computations that are difficult or impossible for digital systems, it is also the case that human-generated results may be inaccurate — thus many social computing systems need to address the issues of monitoring and controlling the quality of results produced. Quality problems may result from ignorance, unnoticed bias, or intentional choice. In the case of the ESP Game, the primary threat to quality is cheating. That is, the game-like incentive mechanisms work so well that players may play with the goal of getting points, rather than accurately labeling images.
As the ESP Game has developed, various cheating strategies have been identified and circumvented. Solo cheating occurs when a person logs on twice and tries to play themselves — this can be detected and prevented by IP matching. Dyadic cheating occurs when two players devise a word entry strategy e. If there are not enough players waiting to ensure a good likelihood of a random match, the ESP Game can use bots as surrogate players, as previously described. Finally, cheating can occur en mass when someone posts a word entry strategy and starting times on a public web site.
This approach can be detected by a sudden spike in activity or a sudden increase in performance , and countered by, once again, pairing players with bots. These examples of cheating raise several points. First, with respect to designing social computing systems, cheating can be dealt with. It is simply necessary to identify cheating strategies and block them — or at least lower their probability of success to a point where it is easier to win by using the system as the designers intended. Second, note that cheating is an issue only in certain types of social computing systems.
Unlike the Amazon review mechanism, which was embedded in the larger Amazon ecology, the ESP Game needs to function as a complete system, solving the problems of recruiting participants, giving them an identity within the system, focusing their attention on tasks that need doing, incenting them to do the task, and monitoring and controlling the quality of the results. The ESP Game does this by drawing on game design thinking.
It is successful because the tasks on which it is focused are simple, well-formed and thus amenable to very rapid, very iterative interaction — and this, in turn, is well suited to game play. On the other hand, while von Ahn and his colleagues have proven to be quite ingenious in their ability to find domains amenable to this approach see Ahn and Dabbish , many problems do not break down so neatly into such simple well-formed tasks.
In this section we examine what is, in the view of many, the most successful example of a social computing system: Wikipedia. Whereas the ESP Game attracts a steady stream of anonymous users who perform a simple task embedded in a game, Wikipedia is more of a community, with a core of committed participants who interact with one another while performing a variety of complex tasks.
Wikipedia has also proved to be popular with researchers, making it a superbly studied example of a social computing system. Thus, our examination of Wikipedia will add breadth to our understanding of social computing. On the face of it, this is a bit of a paradox: how can one have an authoritative source of knowledge that anyone can change at any moment? And yet it works well enough. Regardless of how it compares to the quality of traditional encyclopedias, Wikipedia has been remarkably successful. With over three and a half million articles in the English edition alone, it is among the most visited sites on the web.
And, as we saw earlier, it can generate lengthy, well-researched articles very quickly — literally over night at times. As encyclopedias go, this puts Wikipedia in a class by itself. Most visitors come a to read, but they can also b edit the article, c view its history, or d read its discussion page. Those wishing more involvement in Wikipedia can visit e the Community portal.
While the aim is to create an encyclopedia article, clearly this is too large a task. Contributors do not author fully formed articles all at once. Instead, articles coalesce out of the accretion of smaller efforts. Some may add links to references, others may correct typos and grammatical errors, and still others may contribute images.
This is how the article on The Girl with the Dragon Tattoo developed. As of this writing, it has been viewed , times in the last 30 days.