Learning Social Media Content Optimization: How Can SMEs Draw the Users' Attention on Official WeChat Accounts?

Xueyun Zeng, Xuening Xu, Yenchun Jim Wu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Application of artificial intelligence is accelerating the digital transformation of enterprises, and digital content optimization is crucial to take the users' attention in social media usage. The purpose of this work is to demonstrate how social media content reaches and impresses more users. Using a sample of 345 articles released by Chinese small and medium-sized enterprises (SMEs) on their official WeChat accounts, we employ the self-determination theory to analyze the effects of content optimization strategies on social media visibility. It is found that articles with enterprise-related information optimized for content related to users' psychological needs (heart-based content optimization, mind-based content optimization, and knowledge-based content optimization) achieved higher visibility than that of sheer enterprise-related information, whereas the enterprise-related information embedded with material incentive (benefits-based content optimization) brings lower visibility. The results confirm the positive effect of psychological needs on the diffusion of enterprise-related information, and provide guidance for SMEs to apply artificial intelligence technology to social media practice.

Original languageEnglish
Article number783151
JournalFrontiers in Psychology
Volume12
DOIs
Publication statusPublished - 2022 Jan 10

Keywords

  • SMEs
  • content optimization strategy
  • psychological need
  • self-determination theory
  • social media visibility

ASJC Scopus subject areas

  • General Psychology

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