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Table 2 Notation of multistage stochastic programming model

From: Influence maximization in social media networks concerning dynamic user behaviors via reinforcement learning

Symbol

Definition

Indices and sets

\(\,i \in {{\mathcal {I}}}\)

Node

\(\,k \in {{\mathcal {K}}}\)

Message

\(\,t \in {{\mathcal {T}}}\)

Time

\(\,s \in {{\mathcal {S}}}\)

Scenario

Parameters

\(\,a^{t,s}_{ij}\)

The directed arc from node i to node j

\(\,b_{ki}\)

The information preference of node i with respect to message k

\(\,c_{ki}\)

The pre-activation, that node i has known or has not known the message k before the seed selection

\(\,w_k\)

The influence weight of message k

Decision variable

\(\,x^t_{ki}\)

Binary variable, seed selection, whether the node i is selected as the seed node of message k at time t

\(\,y^{t,s}_{ki}\)

Binary variable, node activation, whether the node i is activated by message k at time t and scenario s

\(\,z^{t,s}_{ki}\)

Binary variable, message transmission, whether the node i decide to transmit message k to its neighbor at time t and scenario s

Other

\(\,Q(x)\)

The total cost of seed selection x

\(\,R(y)\)

The total reward of node activation y

\(\,P(a)\)

The network topology probability of all the arcs a