GSNESR: A Global Social Network Embedding Approach for Social Recommendation

2021 ◽  
pp. 215-226
Author(s):  
Bing-biao Xiao ◽  
Jian-wei Liu
Keyword(s):  
Social Network ◽  
Network Embedding ◽  
Social Recommendation

Consumers’ redemption behavior of recommended mobile coupons in social network sites

2019 ◽  
Vol 57 (9) ◽  
pp. 2477-2500 ◽  
Author(s):  
Qing Tang ◽  
Fen Liu ◽  
Shan Liu ◽  
Yunfeng Ma
Keyword(s):  
Social Network ◽  
Perceived Risk ◽  
Social Network Sites ◽  
Economic Benefits ◽  
Social Recommendation ◽  
Content Type ◽  
Coupon Redemption ◽  
Mobile Coupons ◽  
Key Drivers ◽  
Trust Propensity

Purpose The purpose of this paper is to explore the key factors that affect consumer redemption intention toward mobile coupons recommended in social network sites (SNS). Design/methodology/approach A research model that integrates recommendation trust, positive utilities, and negative utilities of coupon redemption is developed. With the important role of trust in social recommendation taken into consideration, the key drivers of recommendation trust were analyzed in the model. Data were collected from 210 users with mobile coupon recommendation experience in one of the largest SNS (i.e. WeChat) in China. The authors used partial least squares technique to analyze the model. Findings Recommendation trust and positive utilities (economic benefits and perceived enjoyment) positively affect the intention of mobile coupon redemption. Perceived risk, as a negative utility, negatively influences coupon redemption intention. In addition, swift trust (structure assurance, perceived similarity, trust propensity, and expertise of the recommender), knowledge-based trust (familiarity with the retailers), and emotion-based trust (social tie strength) are key drivers that promote recommendation trust. Originality/value While prior research investigated mobile coupon redemption behavior in which coupons were issued by merchants, limited research analyzed consumer responses toward mobile coupons in social recommendation. This study examines the effects of recommendation trust, positive utilities, and negative utilities on mobile coupon redemption in the context of social recommendation and recognizes the key drivers of recommendation trust.

Joint Personalized Markov Chains with social network embedding for cold-start recommendation

2020 ◽  
Vol 386 ◽  
pp. 208-220 ◽  
Author(s):  
Yijia Zhang ◽  
Zhenkun Shi ◽  
Wanli Zuo ◽  
Lin Yue ◽  
Shining Liang ◽  
...  
Keyword(s):  
Social Network ◽  
Markov Chains ◽  
Cold Start ◽  
Network Embedding

scholarly journals Heterogeneous Social Recommendation Model With Network Embedding

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 209483-209494
Author(s):  
Chang Su ◽  
Zongchao Hu ◽  
Xianzhong Xie
Keyword(s):  
Network Embedding ◽  
Social Recommendation

scholarly journals DeepAttr: Inferring Demographic Attributes via Social Network Embedding

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 130270-130282 ◽  
Author(s):  
Xucheng Luo ◽  
Minrui Xie ◽  
Kunpeng Zhang ◽  
Fan Zhou ◽  
Ting Zhong
Keyword(s):  
Social Network ◽  
Network Embedding ◽  
Demographic Attributes

Unsupervised Large-Scale Social Network Alignment via Cross Network Embedding

2021 ◽  
Author(s):  
Zhehan Liang ◽  
Yu Rong ◽  
Chenxin Li ◽  
Yunlong Zhang ◽  
Yue Huang ◽  
...  
Keyword(s):  
Social Network ◽  
Large Scale ◽  
Network Alignment ◽  
Network Embedding
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