1,969 research outputs found

    On dynamic monopolies of graphs: the average and strict majority thresholds

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    Let GG be a graph and τ:V(G)N{0}{\mathcal{\tau}}: V(G)\rightarrow \Bbb{N}\cup \{0\} be an assignment of thresholds to the vertices of GG. A subset of vertices DD is said to be a dynamic monopoly corresponding to (G,τ)(G, \tau) if the vertices of GG can be partitioned into subsets D0,D1,...,DkD_0, D_1,..., D_k such that D0=DD_0=D and for any i0,...,k1i\in {0, ..., k-1}, each vertex vv in Di+1D_{i+1} has at least τ(v)\tau(v) neighbors in D0...DiD_0\cup ... \cup D_i. Dynamic monopolies are in fact modeling the irreversible spread of influence in social networks. In this paper we first obtain a lower bound for the smallest size of any dynamic monopoly in terms of the average threshold and the order of graph. Also we obtain an upper bound in terms of the minimum vertex cover of graphs. Then we derive the upper bound G/2|G|/2 for the smallest size of any dynamic monopoly when the graph GG contains at least one odd vertex, where the threshold of any vertex vv is set as (deg(v)+1)/2\lceil (deg(v)+1)/2 \rceil (i.e. strict majority threshold). This bound improves the best known bound for strict majority threshold. We show that the latter bound can be achieved by a polynomial time algorithm. We also show that α(G)+1\alpha'(G)+1 is an upper bound for the size of strict majority dynamic monopoly, where α(G)\alpha'(G) stands for the matching number of GG. Finally, we obtain a basic upper bound for the smallest size of any dynamic monopoly, in terms of the average threshold and vertex degrees. Using this bound we derive some other upper bounds

    On the Voting Time of the Deterministic Majority Process

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    In the deterministic binary majority process we are given a simple graph where each node has one out of two initial opinions. In every round, every node adopts the majority opinion among its neighbors. By using a potential argument first discovered by Goles and Olivos (1980), it is known that this process always converges in O(E)O(|E|) rounds to a two-periodic state in which every node either keeps its opinion or changes it in every round. It has been shown by Frischknecht, Keller, and Wattenhofer (2013) that the O(E)O(|E|) bound on the convergence time of the deterministic binary majority process is indeed tight even for dense graphs. However, in many graphs such as the complete graph, from any initial opinion assignment, the process converges in just a constant number of rounds. By carefully exploiting the structure of the potential function by Goles and Olivos (1980), we derive a new upper bound on the convergence time of the deterministic binary majority process that accounts for such exceptional cases. We show that it is possible to identify certain modules of a graph GG in order to obtain a new graph GΔG^\Delta with the property that the worst-case convergence time of GΔG^\Delta is an upper bound on that of GG. Moreover, even though our upper bound can be computed in linear time, we show that, given an integer kk, it is NP-hard to decide whether there exists an initial opinion assignment for which it takes more than kk rounds to converge to the two-periodic state.Comment: full version of brief announcement accepted at DISC'1

    Bidding Rings and the Winner's Curse: The Case of Federal Offshore Oil and Gas Lease Auctions

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    This paper extends the theory of legal cartels to affiliated private value and common value environments, and applies the theory to explain joint bidding patterns in U.S. federal government offshore oil and gas lease auctions. We show that efficient collusion is always possible in private value environments, but may not be in common value environments. In the latter case, fear of the winner's curse can cause bidders not to bid, which leads to inefficient trade. Buyers with high signals may be better off if no one colludes. The bid data is consistent with oil and gas leases being common value assets, and with the prediction that the winner's curse can prevent rings from forming on marginal tracts.

    Parameterized Inapproximability of Target Set Selection and Generalizations

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    In this paper, we consider the Target Set Selection problem: given a graph and a threshold value thr(v)thr(v) for any vertex vv of the graph, find a minimum size vertex-subset to "activate" s.t. all the vertices of the graph are activated at the end of the propagation process. A vertex vv is activated during the propagation process if at least thr(v)thr(v) of its neighbors are activated. This problem models several practical issues like faults in distributed networks or word-to-mouth recommendations in social networks. We show that for any functions ff and ρ\rho this problem cannot be approximated within a factor of ρ(k)\rho(k) in f(k)nO(1)f(k) \cdot n^{O(1)} time, unless FPT = W[P], even for restricted thresholds (namely constant and majority thresholds). We also study the cardinality constraint maximization and minimization versions of the problem for which we prove similar hardness results

    Searching for the Concentration-Price Effect in the German Movie Theater Industry

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    This paper investigates whether a price-concentration relationship can be found on local cinema markets in Germany. First, we test a model of monopolistic pricing using a new set of German micro data and find no significant difference in admission prices on monopoly and oligopoly markets. In a next step, we test whether this can be explained by the existence of local monopolies, but find no hint of that. Implicit or explicit collusion among cinema operators might explain our observations.price-concentration study; cinema pricing

    On the approximability and exact algorithms for vector domination and related problems in graphs

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    We consider two graph optimization problems called vector domination and total vector domination. In vector domination one seeks a small subset S of vertices of a graph such that any vertex outside S has a prescribed number of neighbors in S. In total vector domination, the requirement is extended to all vertices of the graph. We prove that these problems (and several variants thereof) cannot be approximated to within a factor of clnn, where c is a suitable constant and n is the number of the vertices, unless P = NP. We also show that two natural greedy strategies have approximation factors ln D+O(1), where D is the maximum degree of the input graph. We also provide exact polynomial time algorithms for several classes of graphs. Our results extend, improve, and unify several results previously known in the literature.Comment: In the version published in DAM, weaker lower bounds for vector domination and total vector domination were stated. Being these problems generalization of domination and total domination, the lower bounds of 0.2267 ln n and (1-epsilon) ln n clearly hold for both problems, unless P = NP or NP \subseteq DTIME(n^{O(log log n)}), respectively. The claims are corrected in the present versio

    The Power of Small Coalitions under Two-Tier Majority on Regular Graphs

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    In this paper, we study the following problem. Consider a setting where a proposal is offered to the vertices of a given network GG, and the vertices must conduct a vote and decide whether to accept the proposal or reject it. Each vertex vv has its own valuation of the proposal; we say that vv is ``happy'' if its valuation is positive (i.e., it expects to gain from adopting the proposal) and ``sad'' if its valuation is negative. However, vertices do not base their vote merely on their own valuation. Rather, a vertex vv is a \emph{proponent} of the proposal if the majority of its neighbors are happy with it and an \emph{opponent} in the opposite case. At the end of the vote, the network collectively accepts the proposal whenever the majority of its vertices are proponents. We study this problem for regular graphs with loops. Specifically, we consider the class Gndh\mathcal{G}_{n|d|h} of dd-regular graphs of odd order nn with all nn loops and hh happy vertices. We are interested in establishing necessary and sufficient conditions for the class Gndh\mathcal{G}_{n|d|h} to contain a labeled graph accepting the proposal, as well as conditions to contain a graph rejecting the proposal. We also discuss connections to the existing literature, including that on majority domination, and investigate the properties of the obtained conditions.Comment: 28 pages, 8 figures, accepted for publication in Discrete Applied Mathematic
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