Analysis of a continuous-time model of structural balance

It is not uncommon for certain social networks to divide into two opposing camps in response to stress. This happens, for example, in networks of political parties during winner-takes-all elections, in networks of companies competing to establish technical standards, and in networks of nations faced with mounting threats of war. A simple model for these two-sided separations is the dynamical system dX/dt = X^2 where X is a matrix of the friendliness or unfriendliness between pairs of nodes in the network. Previous simulations suggested that only two types of behavior were possible for this system: either all relationships become friendly, or two hostile factions emerge. Here we prove that for generic initial conditions, these are indeed the only possible outcomes. Our analysis yields a closed-form expression for faction membership as a function of the initial conditions, and implies that the initial amount of friendliness in large social networks (started from random initial conditions) determines whether they will end up in intractable conflict or global harmony.Comment: 12 pages, 2 figure

Simple and Near-Optimal Mechanisms For Market Intermediation

A prevalent market structure in the Internet economy consists of buyers and sellers connected by a platform (such as Amazon or eBay) that acts as an intermediary and keeps a share of the revenue of each transaction. While the optimal mechanism that maximizes the intermediary's profit in such a setting may be quite complicated, the mechanisms observed in reality are generally much simpler, e.g., applying an affine function to the price of the transaction as the intermediary's fee. Loertscher and Niedermayer [2007] initiated the study of such fee-setting mechanisms in two-sided markets, and we continue this investigation by addressing the question of when an affine fee schedule is approximately optimal for worst-case seller distribution. On one hand our work supplies non-trivial sufficient conditions on the buyer side (i.e. linearity of marginal revenue function, or MHR property of value and value minus cost distributions) under which an affine fee schedule can obtain a constant fraction of the intermediary's optimal profit for all seller distributions. On the other hand we complement our result by showing that proper affine fee-setting mechanisms (e.g. those used in eBay and Amazon selling plans) are unable to extract a constant fraction of optimal profit in the worst-case seller distribution. As subsidiary results we also show there exists a constant gap between maximum surplus and maximum revenue under the aforementioned conditions. Most of the mechanisms that we propose are also prior-independent with respect to the seller, which signifies the practical implications of our result.Comment: To appear in WINE'14, the 10th conference on Web and Internet Economic

Prophet Inequalities with Limited Information

In the classical prophet inequality, a gambler observes a sequence of stochastic rewards $V_1,...,V_n$ and must decide, for each reward $V_i$, whether to keep it and stop the game or to forfeit the reward forever and reveal the next value $V_i$. The gambler's goal is to obtain a constant fraction of the expected reward that the optimal offline algorithm would get. Recently, prophet inequalities have been generalized to settings where the gambler can choose $k$ items, and, more generally, where he can choose any independent set in a matroid. However, all the existing algorithms require the gambler to know the distribution from which the rewards $V_1,...,V_n$ are drawn. The assumption that the gambler knows the distribution from which $V_1,...,V_n$ are drawn is very strong. Instead, we work with the much simpler assumption that the gambler only knows a few samples from this distribution. We construct the first single-sample prophet inequalities for many settings of interest, whose guarantees all match the best possible asymptotically, \emph{even with full knowledge of the distribution}. Specifically, we provide a novel single-sample algorithm when the gambler can choose any $k$ elements whose analysis is based on random walks with limited correlation. In addition, we provide a black-box method for converting specific types of solutions to the related \emph{secretary problem} to single-sample prophet inequalities, and apply it to several existing algorithms. Finally, we provide a constant-sample prophet inequality for constant-degree bipartite matchings. We apply these results to design the first posted-price and multi-dimensional auction mechanisms with limited information in settings with asymmetric bidders

The Influence of Early Respondents: Information Cascade Effects in Online Event Scheduling

Sequential group decision-making processes, such as online event scheduling, can be subject to social influence if the decisions involve individuals’ subjective preferences and values. Indeed, prior work has shown that scheduling polls that allow respondents to see others’ answers are more likely to succeed than polls that hide other responses, suggesting the impact of social influence and coordination. In this paper, we investigate whether this difference is due to information cascade effects in which later respondents adopt the decisions of earlier respondents. Analyzing more than 1.3 million Doodle polls, we found evidence that cascading effects take place during event scheduling, and in particular, that early respondents have a larger influence on the outcome of a poll than people who come late. Drawing on simulations of an event scheduling model, we compare possible interventions to mitigate this bias and show that we can optimize the success of polls by hiding the responses of a small percentage of low availability respondents.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134703/1/Romero et al 2017 (WSDM).pd

Ferromagnetic Moment and Spin Rotation Transitions in Tetragonal Antiferromagnetic Sr\u3csub\u3e2\u3c/sub\u3eCu\u3csub\u3e3\u3c/sub\u3eO\u3csub\u3e4\u3c/sub\u3eCl\u3csub\u3e2\u3c/sub\u3e

Sr2Cu3O4Cl2 is a variant of the lamellar copper oxides, containing an extra Cu2+ ion in the center of every second plaquette of the square CuO2 lattice. The two types of Cu form interpenetrating Heisenberg antiferromagnets, which order at 380 and 40 K. Magnetization measurements yield a small spontaneous ferromagnetic moment below 380 K and two spin rotation transitions. The results are explained in detail by a pseudodipolar coupling between the two Cu lattices. A quantitative analysis of the data yields several previously unknown microscopic coupling constants, relevant to other lamellar, chain, and ladder copper oxides

What Do Computer Scientists Tweet? Analyzing the Link-Sharing Practice on Twitter

Twitter communication has permeated every sphere of society. To highlight and share small pieces of information with possibly vast audiences or small circles of the interested has some value in almost any aspect of social life. But what is the value exactly for a scientific field? We perform a comprehensive study of computer scientists using Twitter and their tweeting behavior concerning the sharing of web links. Discerning the domains, hosts and individual web pages being tweeted and the differences between computer scientists and a Twitter sample enables us to look in depth at the Twitter-based information sharing practices of a scientific community. Additionally, we aim at providing a deeper understanding of the role and impact of altmetrics in computer science and give a glance at the publications mentioned on Twitter that are most relevant for the computer science community. Our results show a link sharing culture that concentrates more heavily on public and professional quality information than the Twitter sample does. The results also show a broad variety in linked sources and especially in linked publications with some publications clearly related to community-specific interests of computer scientists, while others with a strong relation to attention mechanisms in social media. This refers to the observation that Twitter is a hybrid form of social media between an information service and a social network service. Overall the computer scientists’ style of usage seems to be more on the information-oriented side and to some degree also on professional usage. Therefore, altmetrics are of considerable use in analyzing computer science