Social Computing

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Paper Type

ERF

Paper Number

1235

Description

Various theoretical models are used in research into the dissemination of information in social networks. The assumed goals include selecting seeds in order to maximize the influence or reach the target subset of the network users (nodes). On the other hand, the multi-attribute nature of individual network nodes indicates the possibility of analyzing their multi-criteria nature, as well as the consequent use of MCDA methods in the process of seed selection. The state of art shows, however, that this contribution is still missing. This paper presents an attempt to use the multi-criteria decision analysis (MCDA) in the seed selection process and thus a methodological framework supporting reaching many varied sets of target nodes. As a result, a single viral marketing campaign in a social network can be performed to target multiple (often separate) sets of target nodes, thus fulfilling the objectives normally achieved with multiple campaigns.

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Aug 9th, 12:00 AM

Seeding for Complementary Campaign Objectives in Social Networks

Various theoretical models are used in research into the dissemination of information in social networks. The assumed goals include selecting seeds in order to maximize the influence or reach the target subset of the network users (nodes). On the other hand, the multi-attribute nature of individual network nodes indicates the possibility of analyzing their multi-criteria nature, as well as the consequent use of MCDA methods in the process of seed selection. The state of art shows, however, that this contribution is still missing. This paper presents an attempt to use the multi-criteria decision analysis (MCDA) in the seed selection process and thus a methodological framework supporting reaching many varied sets of target nodes. As a result, a single viral marketing campaign in a social network can be performed to target multiple (often separate) sets of target nodes, thus fulfilling the objectives normally achieved with multiple campaigns.

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