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February 5, 2026Electronic Commerce Research and Applications

Stance detection for customer advocacy identification in online customer engagement: A deep learning approach

Bilal Abu-Salih Ruba Abukhurma Ahmad K. Al Hwaitat Malak Al-Hassan Abeer F. Alkhwaldi Muder Almiani

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Key Points

Stance detection effectively identifies customer advocacy in online engagements, leading to better strategic insights.
The model's accuracy reached 85% in categorizing advocacy stance among various online interactions.
Using deep learning algorithms, the analysis evaluates customer sentiments and advocacy in digital platforms.
This approach highlights the potential for enhancing customer engagement practices, fostering brand loyalty.

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Implication

Analysis demonstrates stance detection for identifying customer advocacy in online engagement, suggesting improved marketing strategies.

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Cite This Study

Abu-Salih et al. (2026) studied this question.

synapsesocial.com/papers/69a767e4badf0bb9e87e2c72 https://doi.org/10.1016/j.elerap.2026.101583

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