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Table 3 Notation of myopic two-stage 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

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

Scenario

Parameters

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

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

\(\,d_{ki}\)

The node repost decision, that node i will repost message k in the network

\(\,w_k\)

The influence weight of message k

Decision variable

\(\,x_{ki}\)

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

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

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