The Role of Social Networks in Online Shopping: Information Passing, Price of Trust, and Consumer Choice

TL;DR

This paper investigates how social networks influence online consumer behavior on Taobao, analyzing information passing, trust, and decision-making processes through social graph analysis and transaction data.

Contribution

It provides a large-scale analysis of social and commerce network integration, introducing models for information passing, trust valuation, and consumer choice in online marketplaces.

Findings

Social interactions facilitate information passing among buyers and sellers.

Trust significantly impacts consumer willingness to pay and purchase decisions.

Network structure influences the formation of links and consumer behavior patterns.

Abstract

While social interactions are critical to understanding consumer behavior, the relationship between social and commerce networks has not been explored on a large scale. We analyze Taobao, a Chinese consumer marketplace that is the world's largest e-commerce website. What sets Taobao apart from its competitors is its integrated instant messaging tool, which buyers can use to ask sellers about products or ask other buyers for advice. In our study, we focus on how an individual's commercial transactions are embedded in their social graphs. By studying triads and the directed closure process, we quantify the presence of information passing and gain insights into when different types of links form in the network. Using seller ratings and review information, we then quantify a price of trust. How much will a consumer pay for transaction with a trusted seller? We conclude by modeling this consumer choice problem: if a buyer wishes to purchase a particular product, how does (s)he decide which store to purchase it from? By analyzing the performance of various feature sets in an information retrieval setting, we demonstrate how the social graph factors into understanding consumer behavior.