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Optimizing the Effectiveness of Incentivized Social Sharing

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ASONAM '17: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017

Pages 119 - 122

https://doi.org/10.1145/3110025.3110147

Published: 31 July 2017 Publication History

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Abstract

Social media has become an important tool for companies interested in increasing the reach of their products and services. Some companies even offer monetary incentives to customers for recommending products to their social circles. However, the effectiveness of such incentives is often hard to optimize due to the large space of incentive parameters and the inherent tradeoff between the incentive attractiveness for the customer and the return on investment for the company. To address this problem, we propose a novel graph evolution model, Me+N model, which provides flexibility in exploring the effect of different incentive parameters on company's profits by capturing the probabilistic nature of customer behavior over time. We look at a specific family of incentives in which customers get a reward if they convince a certain number of friends to purchase a given product. Our analysis shows that simple monetary incentives can be surprisingly effective in social media strategies.

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Optimizing the Effectiveness of Incentivized Social Sharing
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms

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ASONAM '17: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017

July 2017

698 pages

ISBN:9781450349932

DOI:10.1145/3110025

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Association for Computing Machinery

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Published: 31 July 2017

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ASONAM '17: Advances in Social Networks Analysis and Mining 2017

July 31 - August 3, 2017

Sydney, Australia

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Revenue maximization in incentivized social advertising

Effectiveness of Trade Promotions: Analyzing the Determinants of Retail Pass Through

Social Sharing, Public Perception, and Brand Competition in a Horizontally Differentiated Market

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