A fuzzy logic approach for tie strength assessment in relationship management: Design and performance comparison of two implemented fuzzy-based models
In an increasingly digitalised and interconnected world, assessing the strength of interpersonal ties in social networks is crucial for fields such as business, marketing and sociology. Traditional methods for evaluating Tie Strength (TS), which often classify relationships as either ”strong” or ”we...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2025-01-01
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| Series: | International Journal of Engineering Business Management |
| Online Access: | https://doi.org/10.1177/18479790251314990 |
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| Summary: | In an increasingly digitalised and interconnected world, assessing the strength of interpersonal ties in social networks is crucial for fields such as business, marketing and sociology. Traditional methods for evaluating Tie Strength (TS), which often classify relationships as either ”strong” or ”weak”, fail to capture the uncertainty and ambiguity of human interactions. This study proposes a Fuzzy-based System for Assessment of Tie Strength (FSATS). We develop and evaluate two models: FSATSM1, which utilises three input parameters Interaction Time (IT), Level of Intimacy (LoI) and Emotional Intensity (EI); and FSATSM2, where we introduce Reciprocity (Rc) as an additional parameter. Through simulations, we compare the performance of both models for the assessment of TS. The simulation results show that for FSATSM1, when IT is 0.9 and EI is 0.7 for all values of LoI, the TS values are more than 0.5. While, for FSATSM2, when IT is 0.9, for EI 0.1 (Rc more than 0.8), EI 0.5 (Rc more than 0.5) and EI 0.9 (Rc more than 0.2), all values of TS are more than 0.5, indicating a strong relationship. The results suggest that FSATSM2 provides a more accurate reflection of real-world relationships, which can be applied in contexts such as Social Customer Relationship Management (SCRM), enabling businesses to enhance customer engagement strategies. |
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| ISSN: | 1847-9790 |