134,406 research outputs found

    Gossip at Work: Unsanctioned Evaluative Talk in Formal School Meetings

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    This article uses a form of linguistic ethnography to analyze videotaped recordings of gossip that took place during formal school meetings. By comparing this gossip data against existing models of gossip based on data collected in informal settings, we identify eleven new response classes, including four forms of indirectness that operate to cloak gossip under ambiguity, and seven forms of avoidance that change the trajectory of gossip. In doing so, this article makes three larger contributions. First, it opens a new front in research on organizational politics by providing an empirically grounded, conceptually rich vocabulary for analyzing gossip in formal contexts. Second, it contributes to knowledge about social interactions in organizations. By examining gossip talk embedded within a work context, this project highlights the nexus between structure, agency, and interaction. Third, it contributes to understandings of gossip in general. By examining gossip in a context previously unexamined, this project provides analytical leverage for theorizing conditions under which gossip is likely and when it will take various forms

    Gossip on Weighted Networks

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    We investigate how suitable a weighted network is for gossip spreading. The proposed model is based on the gossip spreading model introduced by Lind et.al. on unweighted networks. Weight represents "friendship." Potential spreader prefers not to spread if the victim of gossip is a "close friend". Gossip spreading is related to the triangles and cascades of triangles. It gives more insight about the structure of a network. We analyze gossip spreading on real weighted networks of human interactions. 6 co-occurrence and 7 social pattern networks are investigated. Gossip propagation is found to be a good parameter to distinguish co-occurrence and social pattern networks. As a comparison some miscellaneous networks and computer generated networks based on ER, BA, WS models are also investigated. They are found to be quite different than the human interaction networks.Comment: 8 pages, 4 figures, 1 tabl

    Gossip Codes for Fingerprinting: Construction, Erasure Analysis and Pirate Tracing

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    This work presents two new construction techniques for q-ary Gossip codes from tdesigns and Traceability schemes. These Gossip codes achieve the shortest code length specified in terms of code parameters and can withstand erasures in digital fingerprinting applications. This work presents the construction of embedded Gossip codes for extending an existing Gossip code into a bigger code. It discusses the construction of concatenated codes and realisation of erasure model through concatenated codes.Comment: 28 page

    Geographic Gossip: Efficient Averaging for Sensor Networks

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    Gossip algorithms for distributed computation are attractive due to their simplicity, distributed nature, and robustness in noisy and uncertain environments. However, using standard gossip algorithms can lead to a significant waste in energy by repeatedly recirculating redundant information. For realistic sensor network model topologies like grids and random geometric graphs, the inefficiency of gossip schemes is related to the slow mixing times of random walks on the communication graph. We propose and analyze an alternative gossiping scheme that exploits geographic information. By utilizing geographic routing combined with a simple resampling method, we demonstrate substantial gains over previously proposed gossip protocols. For regular graphs such as the ring or grid, our algorithm improves standard gossip by factors of nn and n\sqrt{n} respectively. For the more challenging case of random geometric graphs, our algorithm computes the true average to accuracy ϵ\epsilon using O(n1.5lognlogϵ1)O(\frac{n^{1.5}}{\sqrt{\log n}} \log \epsilon^{-1}) radio transmissions, which yields a nlogn\sqrt{\frac{n}{\log n}} factor improvement over standard gossip algorithms. We illustrate these theoretical results with experimental comparisons between our algorithm and standard methods as applied to various classes of random fields.Comment: To appear, IEEE Transactions on Signal Processin

    Equational Reasonings in Wireless Network Gossip Protocols

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    Gossip protocols have been proposed as a robust and efficient method for disseminating information throughout large-scale networks. In this paper, we propose a compositional analysis technique to study formal probabilistic models of gossip protocols expressed in a simple probabilistic timed process calculus for wireless sensor networks. We equip the calculus with a simulation theory to compare probabilistic protocols that have similar behaviour up to a certain tolerance. The theory is used to prove a number of algebraic laws which revealed to be very effective to estimate the performances of gossip networks, with and without communication collisions, and randomised gossip networks. Our simulation theory is an asymmetric variant of the weak bisimulation metric that maintains most of the properties of the original definition. However, our asymmetric version is particularly suitable to reason on protocols in which the systems under consideration are not approximately equivalent, as in the case of gossip protocols

    Greedy Gossip with Eavesdropping

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    This paper presents greedy gossip with eavesdropping (GGE), a novel randomized gossip algorithm for distributed computation of the average consensus problem. In gossip algorithms, nodes in the network randomly communicate with their neighbors and exchange information iteratively. The algorithms are simple and decentralized, making them attractive for wireless network applications. In general, gossip algorithms are robust to unreliable wireless conditions and time varying network topologies. In this paper we introduce GGE and demonstrate that greedy updates lead to rapid convergence. We do not require nodes to have any location information. Instead, greedy updates are made possible by exploiting the broadcast nature of wireless communications. During the operation of GGE, when a node decides to gossip, instead of choosing one of its neighbors at random, it makes a greedy selection, choosing the node which has the value most different from its own. In order to make this selection, nodes need to know their neighbors' values. Therefore, we assume that all transmissions are wireless broadcasts and nodes keep track of their neighbors' values by eavesdropping on their communications. We show that the convergence of GGE is guaranteed for connected network topologies. We also study the rates of convergence and illustrate, through theoretical bounds and numerical simulations, that GGE consistently outperforms randomized gossip and performs comparably to geographic gossip on moderate-sized random geometric graph topologies.Comment: 25 pages, 7 figure

    Gossip

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