Convergence of Opinion Diffusion is PSPACE-complete

We analyse opinion diffusion in social networks, where a finite set of individuals is connected in a directed graph and each simultaneously changes their opinion to that of the majority of their influencers. We study the algorithmic properties of the fixed-point behaviour of such networks, showing that the problem of establishing whether individuals converge to stable opinions is PSPACE-complete

Convergence of opinion diffusion is PSPACE-complete

We analyse opinion diffusion in social networks, where a finite set of individuals is connected in a directed graph and each simultaneously changes their opinion to that of the majority of their influencers. We study the algorithmic properties of the fixed-point behaviour of such networks, showing that the problem of establishing whether individuals converge to stable opinions is PSPACE-complet

A Structural Complexity Analysis of Synchronous Dynamical Systems

Synchronous dynamical systems are well-established models that have been used to capture a range of phenomena in networks, including opinion diffusion, spread of disease and product adoption. We study the three most notable problems in synchronous dynamical systems: whether the system will transition to a target configuration from a starting configuration, whether the system will reach convergence from a starting configuration, and whether the system is guaranteed to converge from every possible starting configuration. While all three problems were known to be intractable in the classical sense, we initiate the study of their exact boundaries of tractability from the perspective of structural parameters of the network by making use of the more fine-grained parameterized complexity paradigm. As our first result, we consider treewidth - as the most prominent and ubiquitous structural parameter - and show that all three problems remain intractable even on instances of constant treewidth. We complement this negative finding with fixed-parameter algorithms for the former two problems parameterized by treedepth, a well-studied restriction of treewidth. While it is possible to rule out a similar algorithm for convergence guarantee under treedepth, we conclude with a fixed-parameter algorithm for this last problem when parameterized by treedepth and the maximum in-degree

Opinion Dynamics in Networks: Convergence, Stability and Lack of Explosion

Inspired by the work of Kempe et al. [Kempe, Kleinberg, Oren, Slivkins, EC 2013], we introduce and analyze a model on opinion formation; the update rule of our dynamics is a simplified version of that of [Kempe, Kleinberg, Oren, Slivkins, EC 2013]. We assume that the population is partitioned into types whose interaction pattern is specified by a graph. Interaction leads to population mass moving from types of smaller mass to those of bigger mass. We show that starting uniformly at random over all population vectors on the simplex, our dynamics converges point-wise with probability one to an independent set. This settles an open problem of [Kempe, Kleinberg, Oren, Slivkins, EC 2013], as applicable to our dynamics. We believe that our techniques can be used to settle the open problem for the Kempe et al. dynamics as well. Next, we extend the model of Kempe et al. by introducing the notion of birth and death of types, with the interaction graph evolving appropriately. Birth of types is determined by a Bernoulli process and types die when their population mass is less than epsilon (a parameter). We show that if the births are infrequent, then there are long periods of "stability" in which there is no population mass that moves. Finally we show that even if births are frequent and "stability" is not attained, the total number of types does not explode: it remains logarithmic in 1/epsilon

An algorithmic analysis of deliberation and representation in collective behaviour

The selection of a nominee by a group of players in the process of selecting a winner is present in many contexts. In sports, it is a major strategic problem to select the best team members. Crucially, in politics, this problem is essential for the process of primaries. There, factions decide which of their candidates should take part in the elections. We study the strategic behaviour of coalitions from the game-theoretic perspective. More precisely, we analyse the existence of a pure Nash equilibrium in the games capturing the strategic nomination problem. First, we adapt the well-known Hotelling-Downs model, capturing the strategic behaviour of political parties in primaries. Subsequently, we explore this problem for tournament-based rules. There, winners are chosen based on the pairwise comparisons between candidates. First, we study the setting of knockout-tournaments. Next, we investigate tournaments, in which participants do not compete in rounds. For each of these mechanisms, we analyse the computational complexity of checking the existence of a pure Nash equilibrium. Nominee selection can also be influenced by the deliberation between the voters. To account for that, we investigate the complexity of checking the convergence of a synchronous, threshold-based protocol. There, in every time step all agents update their opinion if the strict majority of their influencers disagrees with them. Furthermore, we explore computational aspects of majority illusion. This phenomenon occurs when a large number of agents in a network perceives the opinion, which is a minority view, as the one which is held by the majority of agents. We study the problem of checking the possibility of assigning opinions to agents, so that it holds for a large fraction of them. We further address the complexity of checking the possibility of eliminating the majority illusion by changing a small number of edges in a social network

Random Majority Opinion Diffusion: Stabilization Time, Absorbing States, and Influential Nodes

Consider a graph G with n nodes and m edges, which represents a social network, and assume that initially each node is blue or white. In each round, all nodes simultaneously update their color to the most frequent color in their neighborhood. This is called the Majority Model (MM) if a node keeps its color in case of a tie and the Random Majority Model (RMM) if it chooses blue with probability 1/2 and white otherwise. We prove that there are graphs for which RMM needs exponentially many rounds to reach a stable configuration in expectation, and such a configuration can have exponentially many states (i.e., colorings). This is in contrast to MM, which is known to always reach a stable configuration with one or two states in $O(m)$ rounds. For the special case of a cycle graph C_n, we prove the stronger and tight bounds of $\lceil n/2\rceil-1$ and $O(n^2)$ in MM and RMM, respectively. Furthermore, we show that the number of stable colorings in MM on C_n is equal to $\Theta(\Phi^n)$, where $\Phi = (1+\sqrt{5})/2$ is the golden ratio, while it is equal to 2 for RMM. We also study the minimum size of a winning set, which is a set of nodes whose agreement on a color in the initial coloring enforces the process to end in a coloring where all nodes share that color. We present tight bounds on the minimum size of a winning set for both MM and RMM. Furthermore, we analyze our models for a random initial coloring, where each node is colored blue independently with some probability $p$ and white otherwise. Using some martingale analysis and counting arguments, we prove that the expected final number of blue nodes is respectively equal to $(2p^2-p^3)n/(1-p+p^2)$ and pn in MM and RMM on a cycle graph C_n. Finally, we conduct some experiments which complement our theoretical findings and also lead to the proposal of some intriguing open problems and conjectures to be tackled in future work.Comment: Accepted in AAMAS 2023 (The 22nd International Conference on Autonomous Agents and Multiagent Systems

Modal Logics and Group Polarization

Under embargo until: 2022-10-22This paper proposes different ways of modally defining properties related to the concept of balance in signed social networks where relations can be either positive or negative. The motivation is to be able to formally reason about the social phenomenon of group polarization based on balance theory. The starting point is a recently developed basic modal logic that axiomatizes the class of social networks that are balanced up to a certain degree. This property is not modally definable but can be captured using a deduction rule. In this work, we examine different possibilities for extending this basic language to define frame properties such as balance and related properties such as non-overlapping positive and negative relations and collective connectedness as axioms. Furthermore, we define the property of full balance rather than balanced-up-to-a-degree. We look into the complexity of the model checking problem and show a non-compactness result of the extended language. Along the way, we provide axioms for weak balance. We also look at a full hybrid extension and reason about network changes with dynamic modalities. Then, to explore the measures of how far a network is from polarization, we consider variations of measures in relation to balance.acceptedVersio

The hitchhiker's guide to decidability and complexity of equivalence properties in security protocols

International audiencePrivacy-preserving security properties in cryptographic protocols are typically modelled by observational equivalences in process calculi such as the applied pi-calulus. We survey decidability and complexity results for the automated verification of such equivalences, casting existing results in a common framework which allows for a precise comparison. This unified view, beyond providing a clearer insight on the current state of the art, allowed us to identify some variations in the statements of the decision problems-sometimes resulting in different complexity results. Additionally, we prove a couple of novel or strengthened results