Daniel M. Romero

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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(More)
Scholars, advertisers and political activists see massive online social networks as a representation of social interactions that can be used to study the propagation of ideas, social bond dynamics and viral marketing, among others. But the linked structures of social networks do not reveal actual interactions among people. Scarcity of attention and the(More)
The ever-increasing amount of information flowing through Social Media forces the members of these networks to compete for attention and influence by relying on other people to spread their message. A large study of information propagation within Twitter reveals that the majority of users act as passive information consumers and do not forward the content(More)
It has often been taken as a working assumption that directed links in information networks are frequently formed by “short-cutting” a two-step path between the source and the destination — a kind of implicit “link copying” analogous to the process of triadic closure in social networks. Despite the role of this assumption in theoretical models such as(More)
The tragedy of the digital commons does not prevent the copious voluntary production of content that one witnesses in the web. 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(More)
People’s interests and people’s social relationships are intuitively connected, but understanding their interplay and whether they can help predict each other has remained an open question. We examine the interface of two decisive structures forming the backbone of online social media: the graph structure of social networks — who connects with whom — and(More)
In social media settings where users send messages to one another, the issue of reciprocity naturally arises: does the communication between two users take place only in one direction, or is it reciprocated? In this paper we study the problem of reciprocity prediction: given the characteristics of two users, we wish to determine whether the communication(More)
A variety of social networks feature a directed attention or “follower” network. In this paper, we compare several methods of recommending new people for users to follow. We analyzed structural patterns in a directed social network to evaluate the likelihood that they will predict a future connection, and use these observations to inform an intervention(More)
Crowds are increasingly being adopted to solve complex problems. Size and diversity are two key characteristics of crowds; however their relationship to performance is often paradoxical. To better understand the effects of crowd size and diversity on crowd performance we conducted a study on the quality of 4,317 articles in the WikiProject Film community.(More)