Target Set Selection in Dense Graph Classes

In this paper we study the Target Set Selection problem, a fundamental problem in computational social choice, from a parameterized complexity perspective. Here for a given graph and a threshold for each vertex the task is to find a set of active vertices that activates whole graph. A vertex becomes active if the number of activated vertices in its neighborhood is at least its threshold. We give two parameterized algorithms for a special case where each vertex has threshold set to half of its neighbors (the so called Majority Target Set Selection problem) for parameterizations by neighborhood diversity and twin cover number of the input graph. From the opposite side we give hardness proof for the Majority Target Set Selection problem when parameterized by (restriction of) the modularwidth – a natural generalization of both previous structural parameters. Finally, we give hardness proof for the Target Set Selection problem parameterized by the neighborhood diversity when there is no restriction on the thresholds.