Multi-criteria decision support for planning and evaluation of performance of viral marketing campaigns in social networks

Abstract

The current marketing landscape, apart from conventional approaches, consists of campaigns designed especially for launching information diffusion processes within online networks. Associated research is focused on information propagation models, campaign initialization strategies and factors affecting campaign dynamics. In terms of algorithms and performance evaluation, the final coverage represented by the fraction of activated nodes within a target network is usually used. It is not necessarily consistent with the real marketing campaigns using various characteristics and parameters related to coverage, costs, behavioral patterns and time factors for overall evaluation. This paper presents assumptions for a decision support system for multi-criteria campaign planning and evaluation with inputs from agent-based simulations. The results, which are delivered from a simulation model based on synthetic networks in a form of decision scenarios, are verified within a real network. Last, but not least, the study proposes a multi-objective campaign evaluation framework with several campaign evaluation metrics integrated. The results showed that the recommendations generated with the use of synthetic networks applied to real networks delivered results according to the decision makers’ expectation in terms of the used evaluation criteria. Apart from practical applications, the proposed multi-objective approach creates new evaluation possibilities for theoretical studies focused on information spreading processes within complex networks.

Green Supplier Selection Criteria: From a Literature Review to a Comprehensive Knowledge Base

“…Single models encompass mathematics approaches (e.g., AHP, linear programming, multi-objective programming, goal programming and also simulations and heuristics), single models such as cluster analysis, multiple regression or discriminant analysis, and artificial intelligence approaches including as an example neural networks, fuzzy set theory and software agents. Recently, because of high flexibility in combined models, they are developed more [80]. They refer to conjunctions of various single models, for example AHP with goal programming or AHP with fuzzy set theory [64].…”

Towards Strong Sustainability Management—A Generalized PROSA Method

“…From among the MCDA methods used in the context of sustainability, the PROMETHEE II method is worthy of particular attention. This method (including fuzzy versions) is widely used in decision-making problems related to sustainable development [42,43] and digital sustainability [44], and some of its unique features are useful for sustainability assessment. Thanks its use of six different preference functions, PROMETHEE II makes it possible to solve a decision problem taking into account both weaker sustainability and stronger one (higher and lower compensation degrees).…”

Multi-criteria approach to viral marketing campaign planning in social networks, based on real networks, network samples and synthetic networks

“…The earlier studies focused mainly on influence maximization to increase coverage within the network. Campaign evaluation was was also discussed as a multi-criteria problem [12]. Campaigns performed within agent based simulation environment were evaluated with the use of set of criteria related to budgets, campaign costs and the number of target nodes.…”

“…Additional budgets can be used to increase campaign dynamics or lifespan. To take into account various goals multi-criteria campaign evaluation can be used to select campaign parameters and goals according to preferences and priorities [12]. Earlier research has shown that in order to reduce computational complexity, campaigns can be planned with the use of simulations within smaller synthetic networks based on theoretical model.…”