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March 3, 2026
Stance detection for customer advocacy identification in online customer engagement: A deep learning approach
BA
Bilal Abu-Salih
University of Jordan
RA
Ruba Abukhurma
Al-Balqa Applied University
AH
Ahmad K. Al Hwaitat
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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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Abu-Salih et al. (Thu,) studied this question.
synapsesocial.com/papers/69a767e4badf0bb9e87e2c72
https://doi.org/https://doi.org/10.1016/j.elerap.2026.101583
Stance detection for customer advocacy identification in online customer engagement: A deep learning approach | Synapse