Segmenting consumers on social networks based on individual motivations for engagement in eWOM communication with self-organising maps

Manijeh Bahrainizad & Hamid Izadi

International Journal of Internet Marketing and Advertising2025https://doi.org/10.1504/ijima.2025.144182article
AJG 1ABDC C
Weight
0.50

What the paper says

Social networks allow consumers to share marketing content and advertise products for free through electronic word-of-mouth (eWOM) communication.Consumers regularly share eWOM regarding their motivations.Some of these motivations have been identified in previous studies.This study aimed to understand how consumers can be segmented on social networks according to the individual motivations for engagement in eWOM.A self-organising map was used for segmentation.Data were collected by sending questionnaire links to 385 Iranian users of Telegram, Facebook, and Instagram using a convenience sampling method.A total of three segments were identified: active users with low individual motivation, who spent a relatively long time on social networks, but had low individual motivations to participate in eWOM activities.Active users with high individual motivations were young users who devoted the most time to social networks and were highly motivated.Finally, inactive users with individual motivations who despite having sufficient individual motivations, spent very little time on social networks.This study, by applying a self-organising map for segmenting consumers on social networks, provides insights into how companies should make strategies to engage consumers in eWOM communication, taking into account individual motivations.

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https://doi.org/https://doi.org/10.1504/ijima.2025.144182

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@article{manijeh2025,
  title        = {{Segmenting consumers on social networks based on individual motivations for engagement in eWOM communication with self-organising maps}},
  author       = {Manijeh Bahrainizad & Hamid Izadi},
  journal      = {International Journal of Internet Marketing and Advertising},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijima.2025.144182},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.