A graph-based algorithm for interpersonal ties clustering in signed networks - Sangamuang, Sumalee (Array, 2019)
Social ties are formed as a result of interactions and individual preferences of the people in a social network. There are two opposite types which are interpreted as friendship vs. enmity or trust vs. distrust between people. The aforementioned social network structure can be represented by a signed graph, where people are the graph’s vertices and their interactions are graph’s edges. The edges can be positive and negative signs. To determine trustworthiness, this paper considers the problem of a signed graph partitioning with minimizing the sum of the negative edge's weight and balanced size of its clusters. An efficient algorithm to solve such a problem is proposed. The experimental results show that the proposed algorithm outperforms in terms of the execution times and the accuracy within the given bounds.