3 The research was done while at HP Labs.

Twitter, a microblogging service less than three years old, commands more than 41 million users as of July 2009 and is growing fast. Twitter users tweet about any topic within the 140-character limit and follow others to receive their tweets. The goal of this paper is to study the topological characteristics of Twitter and its power as a new medium of information sharing. We have crawled the entire Twitter site and obtained 41.7 million user profiles, 1.47 billion social relations, 4, 262 trending topics, and 106 million tweets. In its follower-following topology analysis we have found a non-power-law follower distribution, a short effective diameter, and low reciprocity, which all mark a deviation from known characteristics of human social networks [28]. In order to identify influentials on Twitter, we have ranked users by the number of followers and by PageRank and found two rankings to be similar.

The flow of information or influence through a large social network can be thought of as unfolding with the dynamics of an epidemic: as individuals become aware of new ideas, tech-nologies, fads, rumors, or gossip, they have the potential to pass them on to their friends and colleagues, causing the resulting behavior to cascade through the network. We consider a collection of probabilistic and game-theoretic models for such phenomena proposed in the mathematical social sciences, as well as recent algorithmic work on the problem by computer scientists. Building on this, we discuss the implications of cascading behavior in a number of on-line settings, including word-of-mouth effects (also known as “viral marketing”) in the success of new products, and the influence of social networks in the growth of on-line communities. 1

There is a widespread intuitive sense that different kinds of information spread differently on-line, but it has been difficult to evaluate this question quantitatively since it requires a setting where many different kinds of information spread in a shared environment. Here we study this issue on Twitter, analyzing the ways in which tokens known as hashtags spread on a network defined by the interactions among Twitter users. We find significant variation in the ways that widely-used hashtags on different topics spread. Our results show that this variation is not attributable simply to differences in “stickiness, ” the probability of adoption based on one or more exposures, but also to a quantity that could be viewed as a kind of “persistence ” — the relative extent to which repeated exposures to a hashtag continue to have significant marginal effects. We find that hashtags on politically controversial topics are particularly persistent, with repeated exposures continuing to have unusually large marginal effects on adoption; this provides, to our knowledge, the first large-scale validation of the “complex contagion” principle from sociology, which posits that repeated exposures to an idea are particularly crucial when the idea is in some way controversial or contentious. Among other findings, we discover that hashtags representing the natural analogues of Twitter idioms and neologisms are particularly non-persistent, with the effect of multiple exposures decaying rapidly relative to the first exposure. We also study the subgraph structure of the initial adopters for different widely-adopted hashtags, again finding structural differences across topics. We develop simulation-based and generative models to analyze how the adoption dynamics interact with the network structure of the early adopters on which a hashtag spreads.

A basic premise behind the study of large networks is that interaction leads to complex collective behavior. In our work we found very interesting and counterintuitive patterns for time evolving networks, which change some of the basic assumptions that were made in the past. We then develop models that explain processes which govern the network evolution, fit such models to real networks, and use them to generate realistic graphs or give formal explanations about their properties. In addition, our work has a wide range of applications: it can help us spot anomalous graphs and outliers, forecast future graph structure and run simulations of network evolution. Another important aspect of our research is the study of “local ” patterns and structures of propagation in networks. We aim to identify building blocks of the networks and find the patterns of influence that these blocks have on information or virus propagation over the network. Our recent work included the study of the spread of influence in a large person-to-person

National Institute on Aging PO1-AG19783. In his classic 1957 study of hybrid corn diffusion, Griliches emphasized the importance of economic incentives and profitability in the adoption of new technology, and this focus has been continued in the economics literature. But there is a distinct literature with roots in sociology emphasizing the structure of organizations, informal networks, and “change agents. ” We return to a forty-year-old debate between Griliches and the sociologists by considering state-level factors associated with the adoption of a variety of technological innovations: hybrid corn and tractors in the first half of the 20 th century, computers, and the treatment of heart attacks during the last decade. First, we find that some states consistently adopted new effective technology, whether hybrid corn, tractors, or effective treatments for heart attacks such as Blockers. Second, the adoption of these new highly effective technologies was closely associated with measures of statelevel social capital (and education), but not per capita income, density, or (in the case of Blockers) with expenditures on heart attack patients. Economic models are useful in identifying why some regions are more likely to adopt early, but sociological barriers – perhaps related to a lack of social capital or informational networks – can potentially explain why other regions lag far behind.

Because knowledge plays an important role in the creation of wealth, economic actors often wish to skew the flow of knowledge in their favor. Managers seek to spread knowledge widely within their organization but prevent its diffusion to rivals. Regional planners promote knowledge diffusion within a local economy but not beyond it. We ask, when will knowledge developed in one area of dense social connections – such as a firm, a geographic locale, or a technological community – tend to diffuse to the edge of that area but not beyond it? Marrying social network theory with a view of knowledge transfer as a search process, we argue that the degree of knowledge inequality across social boundaries depends crucially on the nature

Competition between organizational forms manifests itself in political contention over the law. The authors analyze the political strength and organization of the groups that supported and opposed state anti-chain-store laws. The enactment of these laws depended on intrastate political activity and the interstate diffusion of antichain-store legislation. The repeal process relied on suprastate activity, as nationally organized pro-chain-store forces shifted the arena of contention to the Supreme Court and forged national alliances with labor unions and agricultural cooperatives. In both enactment and repeal, the political resources and strategies of organziational forms interacted with existing institutions to determine the trajectory of institutional change. The selfishness of those who would control the money power of the nation, if their greed is allowed to develop unchecked... [would leave] masses of Americans wholly at the mercy of the despotic power of a monopolistic class.—National Association of Retail Druggists Journal If the people of the United States like our stores so little that they are willing to tax us out of business, that is their affair. We will shut up shop.—president of the Atlantic & Pacific

When is a social actor most strongly influenced by its peers? This article addresses this question by clarifying when computer firms were most strongly affected by the choices of their structurally equivalent rivals to adopt a well-known technology: Intel’s sixth-generation processor. The core hypothesis is that the effect of adoptions by structurally equivalent firms increases with the competitive pressure that a focal firm faces in its market position. The results show that a chosen firm is most strongly influenced by comparable others when it faces scale-based competition and is diversified. The implications of this study are twofold: a social actor’s sensitivity to the conduct of others may depend not only on its place in a hierarchy but also on the nature of its ties to an external audience; and a contingent theory of social influence may be necessary to characterize diffusion processes correctly, particularly when external and time-varying nonnetwork factors have significant effects.

informs ® doi 10.1287/orsc.1050.0137 © 2005 INFORMS This paper argues that research in organization theory has seen a shift in orientation from paradigm-driven work to problem-driven work since the late 1980s. A number of paradigms for the study of organizations were elaborated during the mid-1970s, including transaction cost economics, resource dependence theory, organizational ecology, new institutional theory, and agency theory in financial economics. These approaches reflected the dominant trends of the large corporations of their time: increasing concentration, diversification, and bureaucratization. However, subsequent shifts in organizational boundaries, the increased use of alliances and network forms, and the expanding role of financial markets in shaping organizational decision making all make normal science driven by the internally derived questions from these paradigms less fruitful. Instead, we argue that problem-driven work that uses mechanism-based theorizing and research that takes the field rather than the organization as the unit of analysis are the most appropriate styles of organizational research under conditions of major economic change—such as our own era. This sort of work is best exemplified by various studies under the rubric of institutional theory in the past 15 years, which are reviewed here. Key words: organization theory; social mechanisms; organizational fields; paradigms