Abstract:
This qualitative descriptive study aims to map the interactions and structures among Shopee consumers on Twitter, utilizing the Social Network Analysis (SNA) method. Secondary data from Twitter were collected, and data analysis was facilitated using various tools, including Google Colab, Dictionary, Wordij, and Gephi. The network properties, such as nodes, edges, average degree, diameter, and average path length, were calculated for different promotional content keywords. The findings revealed that the flash sale keyword in 2020 exhibited a significant number of nodes and interactions, indicating extensive discussions on social media. This research offers valuable insights for digital marketing strategies within the Shopee marketplace, based on the observed patterns and implications derived from the SNA results.
Highlights:
In-depth analysis: This research provides an in-depth analysis of consumer interactions on Twitter within the context of Shopee, shedding light on the dynamics and structures of these interactions.
Valuable insights: The study offers valuable insights into digital marketing strategies for the Shopee marketplace by examining the patterns and trends identified through social network analysis.
Implications for promotion: By mapping the interactions and structures among Shopee consumers on Twitter, this research helps identify effective promotional strategies, such as utilizing flash sales, to engage with users on social media platforms.
Keywords: Shopee, Twitter, Consumer Interactions, Digital Marketing Strategies, Social Network Analysis.
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