Details

Autor(en) / Beteiligte

• Hu, Xiaojing
• Liu, Shixi
• Zhang, Yudong
• Zhao, Guozhu
• Jiang, Cuiqing

Titel

Identifying top persuaders in mixed trust networks for electronic marketing based on word-of-mouth

Ist Teil von

• Knowledge-based systems, 2019-10, Vol.182, p.104803, Article 104803

Ort / Verlag

Amsterdam: Elsevier B.V

Erscheinungsjahr

2019

Quelle

Elsevier ScienceDirect Journals

Beschreibungen/Notizen

• The identification of top persuaders from social networking websites is increasingly attracting attention because they can significantly affect consumers’ purchasing decisions in electronic word-of-mouth (eWOM) marketing. Existing studies on the identification of top persuaders have mainly focused on the idea of trust and have not considered distrust. However, this omission may lead to a high negative impact of the top persuaders identified from trust networks. To address this issue in the context of mixed trust networks, this study formulates the top persuader identification problem and develops a novel approach to identifying top persuaders. The structural properties of mixed trust networks are investigated through four measures: the degree of distribution, the correlation coefficient of trust and distrust, the cumulative distribution of the ratio between the degree of distrust and the degree of trust, and the mix pattern. To adapt to the context of mixed trust networks, a mixed trust PageRank (MTPR) index is conceived to evaluate the influential power of a top persuader. Reinforced by the dimensions of trust and distrust, the MTPR-based approach is proposed to identify top persuaders in mixed trust networks. The experimental results using real-world data collected from Epinions show that the proposed approach outperforms the degree centrality approach and the PageRank approach.