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The authors designed and ran an experiment to measure social influence in online recommender systems, specifically, how often people’s choices are changed by others’ recommendations when facing different levels of confirmation and conformity pressures. In this experiment, participants were first asked to provide their preference from pairs of items. They were then asked to make second choices about the same pairs with knowledge of other people’s preferences. The results show that other people’s opinions significantly sway people’s own choices. The influence is stronger when people are required to make their second decision sometime later (22.4%) rather than immediately (14.1%). Moreover, people seem to be most likely to reverse their choices when facing a moderate, as opposed to large, number of opposing opinions. Finally, the time people spend making the first decision significantly predicts whether they will reverse their decisions later on, whereas demographics such as age and gender do not. These results have implications for consumer behavior research as well as online marketing strategies. [ABSTRACT FROM PUBLISHER]

Social computing focuses on the interaction between social behavior and information, especially on how the latter propagates across social networks and is consumed and transformed in the process. At the same time the ubiquity of information has left it devoid of much monetary value. The scarce, and therefore valuable, resource is now attention, and its allocation gives rise to an attention economy that determines how content is consumed and propagated. Since two major factors involved in getting attention are novelty and popularity, we analyze the role that both play in attracting attention to web content and how to prioritize them in order to maximize it. We also demonstrate that the relative performance of strategies based on prioritizing either popularity or novelty exhibit an abrupt change around a critical value of the novelty decay time, resembling a phase transition. [ABSTRACT FROM AUTHOR]

We present a dynamical model of cooperative efforts comprised of concurrently performed, interrelated tasks. The model contains a stochastic component to account for temporal fluctuations both in task performance and in the effect of a given unit of work on the project as a whole. We show that as the number of concurrent tasks increases, so does the average completion time. Also, for fixed system size, the dynamics of individual project realizations can exhibit large deviations from the average when fluctuations increase past a certain threshold, causing long delays in completion times. These effects are in agreement with empirical observation. We also show that the negative effects of both large groups and long delays caused by fluctuations may be mitigated by arranging projects in a hierarchical or modular structure. Our model is applicable to any arrangement of interdependent tasks, providing an analytical prediction for the average completion time as well as a numerical threshold for the fluctuation strength beyond which long delays are likely. In conjunction with previous modeling techniques, it thus provides managers with a predictive tool to be used in the design of a project’s architecture. [ABSTRACT FROM AUTHOR]

We show through an analysis of a massive data set from YouTube that the productivity exhibited in crowdsourcing exhibits a strong positive dependence on attention, measured by the number of downloads. Conversely, a lack of attention leads to a decrease in the number of videos uploaded and the consequent drop in productivity, which in many cases asymptotes to no uploads whatsoever. Moreover, short-term contributors compare their performance to the average contributor's performance while long-term contributors compare it to their own media. [ABSTRACT FROM AUTHOR]

Abstract: We present a model for the diffusion of management fads and other technologies which lack clear objective evidence about their merits. The choices made by non-Bayesian adopters reflect both their own evaluations and the social influence of their peers. We show, both analytically and computationally, that the dynamics lead to outcomes that appear to be deterministic in spite of being governed by a stochastic process. In other words, when the objective evidence about a technology is weak, the evolution of this process quickly settles down to a fraction of adopters that is not predetermined. When the objective evidence is strong, the proportion of adopters is determined by the quality of the evidence and the adopters’ competence. [Copyright &y& Elsevier]

A distinguishing feature of the information era is the saliency of people's attention as a scarce resource. Unlike an earlier time when information was a valuable resource, its easy availability has shifted the focus to the limited bandwidth that people can devote to ubiquitous media and news. With this in mind, we introduce an automatic configuration mechanism that generates the most relevant information to be presented to limited attention users. It also guarantees to maximize their total expected utility from the information they receive. A computationally efficient algorithm is used to assign an index value to each information item, which then determines whether or not a given item appears in the top list presented to users at a given time. [ABSTRACT FROM AUTHOR]

Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content. Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks, photographs and other content. In this paper we analyze the structure of collaborative tagging systems as well as their dynamic aspects. Specifically, we discovered regularities in user activity, tag frequencies, kinds of tags used, bursts of popularity in bookmarking and a remarkable stability in the relative proportions of tags within a given URL. We also present a dynamic model of collaborative tagging that predicts these stable patterns and relates them to imitation and shared knowledge. [ABSTRACT FROM AUTHOR]

We present a study of information flow that takes into account the observation that an item relevant to one person is more likely to be of interest to individuals in the same social circle than those outside of it. This is due to the fact that the similarity of node attributes in social networks decreases as a function of the graph distance. An epidemic model on a scale-free network with this property has a finite threshold, implying that the spread of information is limited. We tested our predictions by measuring the spread of messages in an organization and also by numerical experiments that take into consideration the organizational distance among individuals. [Copyright &y& Elsevier]

We present a method for creating a network of gene co-occurrences from the literature and partitioning it into communities of related genes. The way in which our method identifies communities makes it likely that the component genes of each community will be related by their function. The method processes a large database of article abstracts, synthesizing information from many sources to shed light on groups of genes that have been shown to interact. It is a tool to be used by researchers in the biomedical sciences to swiftly. search for known interactions and to provide insight into unexplored connections. The partitioning procedure is designed to be particularly applicable to large networks in which individual nodes may play a role in more than one community. In this paper, we explain the details of the method, in particular the partitioning process. We also apply the method to produce communities of genes related to colon cancer and show that the results. are useful. [ABSTRACT FROM AUTHOR]

Examines the dynamics of a work group whose members value not only compensation, but also having a high status relative to their peers. Compensation in the form of a fixed salary; Bonus based on group performance; Determination of status by contribution to group output and social activities; Status competition based on merit.

Focuses on a method offered which offers a computational portfolio design procedure which can be used for a wide range of problems. Combination of existing algorithms into updated programs; What the method is based on.

We study the ongoing collective action problem among intentional agents whose choices depend not only on the past but also on their expectations as to how their actions will affect those of others. In this model agents act on the basis of imperfect information. We show that under these conditions the onset of overall cooperation can take place in a sudden and unexpected way. Likewise, defection can appear out of nowhere in very large, previously cooperating groups. These outbreaks mark the end of long transient states in which defection or cooperation persists in groups that cannot sustain it indefinitely. [ABSTRACT FROM AUTHOR]

Presents information on multiagent systems, and looks at an analysis of fluctuations in equilibrium. Discussion on the volatility associated with multiagent dynamics; Indepth look at the dynamic economic models; Characterization of such systems; Information on the theory of stability of resource contention for different strategy mixes.

The subject of collective attention is central to an information age where millions of people are inundated with daily messages. It is thus of interest to understand how attention to novel items propagates and eventually fades among large populations. We have analyzed the dynamics of collective attention among 1 million users of an interactive web site, digg.com, devoted to thousands of novel news stories. The observations can be described by a dynamical model characterized by a single novelty factor. Our measurements indicate that novelty within groups decays with a stretched-exponential law, suggesting the existence of a natural time scale over which attention fades. [ABSTRACT FROM AUTHOR]

Presents research which examined simulations of heterogeneous highway traffic demonstrating that cooperative, coherent states can arise from competitive interactions between vehicles. Value of studying highway traffic patterns; Effects of an increase in the density of vehicles; Safety of this state; When the coherent state disappears; Effect observed in real Dutch traffic data.

Suggests a possible microscopic mechanism for the observed intermittent congestions of the Internet. Internet users not charged in proportion to use; Failure of Individuals consuming bandwidth to consider effect on overall performance of the Internet; Possibility for Internet performance to degrade as a result; Construction of a model showing short-lived spikes of congestion.

Describes several strong regularities of Web user surfing patterns discovered through extensive empirical studies of different user communities. Use of online links and search engines; Development of logarithm used in the study.

Presents a response from the author to a letter to the editor on his article about the U.S. federal rules governing the privacy of human subjects, published in the February 25 issue of the periodical "Science."

A letter to the editor is presented in response to an article on the accessibility of data gathered by web resources including Google, Twitter and Facebook in the 2012 issue.

A letter to the editor is presented in response to the article "Message from the heavens."

Proposes an alternative protocol for the exchange of medical data that uses a cryptographic strategy to preserve privacy while allowing investigators to access an individual's data and the opportunity to contact the investigator for further questions. Need to balance social benefits of access to genetic information and potential risk of genetic discrimination.

We analyzed the temporal aspect of trends and trend-setters in Sina Weibo, contrasting it with earlier observations of Twitter. We found a vast difference in the content shared in China as compared with a global social network such as Twitter. In China, the trends are created almost entirely due to the retweets of media content such as jokes, images, and videos, unlike Twitter where trends have more to do with current global events and news stories. On closer inspection, we observed that most trends in Sina Weibo are due to the continuous retweets of a small percentage of fraudulent accounts, set up to artificially inflate certain posts. This reveals evidence of an "Internet Water Army," a unique promotional method deployed by public relations companies in China to influence the popular dissemination of information in online social networks. [ABSTRACT FROM AUTHOR]

Examines the hidden order of the World Wide Web using a stochastic dynamical growth model. Distribution of web pages according to a universal power law; Implication of the existence of a power law to the probability of finding information on the Web.

We have designed and implemented an open, market-based computational system called Spawn. The Spawn system utilizes idle computational resources in a distributed network of heterogeneous computer workstations. It supports both coarse-grain concurrent applications and the remote execution of many independent tasks. Using concurrent Monte Carlo simulations as prototypical applications, we explore issues of fairness in resource distribution, currency as a form of priority, price equilibria, the dynamics of transients, and scaling to large systems. In addition to serving the practical goal of harnessing idle processor time in a computer network, Spawn has proven to be a valuable experimental workbench for studying computational markets and their dynamics. [ABSTRACT FROM AUTHOR]

The mobility/cloud ecosystem aims to deliver infrastructure, platforms, and software as a service, enabling more people to benefit from ubiquitous information access. The culmination of 10 years' research converges on-demand applications with the infrastructure—servers, storage, networks, and client devices—to support cloud computing. [ABSTRACT FROM PUBLISHER]