Social Behavior Analysis in Exclusive Enterprise Social Networks by FastHAND
Authors: 
Yang Yang, Feifei Wang, Enqiang Zhu, Fei Jiang, Wen YaoAuthors Info & Claims
Article No.: 134, Pages 1 - 32
Abstract
There is an emerging trend in the Chinese automobile industries that automakers are introducing exclusive enterprise social networks (EESNs) to expand sales and provide after-sale services. The traditional online social networks (OSNs) and enterprise social networks (ESNs), such as X (formerly known as Twitter) and Yammer, are ingeniously designed to facilitate unregulated communications among equal individuals. However, users in EESNs are naturally social stratified, consisting of both enterprise staffs and customers. In addition, the motivation to operate EESNs can be quite complicated, including providing customer services and facilitating communication among enterprise staffs. As a result, the social behaviors in EESNs can be quite different from those in OSNs and ESNs. In this work, we aim to analyze the social behaviors in EESNs. We consider the Chinese car manufacturer NIO as a typical example of EESNs and provide the following contributions. First, we formulate the social behavior analysis in EESNs as a link prediction problem in heterogeneous social networks. Second, to analyze this link prediction problem, we derive plentiful user features and build multiple meta-path graphs for EESNs. Third, we develop a novel Fast (H)eterogeneous graph (A)ttention (N)etwork algorithm for (D)irected graphs (FastHAND) to predict directed social links among users in EESNs. This algorithm introduces feature group attention at the node-level and uses an edge sampling algorithm over directed meta-path graphs to reduce the computation cost. By conducting various experiments on the NIO community data, we demonstrate the predictive power of our proposed FastHAND method. The experimental results also verify our intuitions about social affinity propagation in EESNs.
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Index Terms
- Social Behavior Analysis in Exclusive Enterprise Social Networks by FastHAND
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Publication History
Published: 12 April 2024
Online AM: 12 February 2024
Accepted: 26 January 2024
Revised: 03 October 2023
Received: 05 January 2023
Published in TKDD Volume 18, Issue 6
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- National Natural Science Foundation of China
- Renmin University of China, Chinese National Statistical Science Research
- Foundation from Ministry of Education of China
- MOE Project of Key Research Institute of Humanities and Social Sciences
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