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Effective Estimation of Relationship Strength Among Facebook Users Applying Pearson Correlation and Jaccard’s Coefficient

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Intelligent Human Centered Computing (Human 2023)

Abstract

Numerous ways have been established till the present to identify tie strength among users on online social media. Although calculating relationship strength among interconnected users has been a burning research topic, it is not also easy to find out powerful interconnections in a dynamic network as the volatility of user connections over a period of time. Mainly, the highest frequency of sharing information between two users in a network indicates strong bonding in a social network. And possible mutual connections may be established based on the strong bonding between two users. In this paper, we have proposed a novel method to calculate relationship strength among Facebook users with Pearson Correlation and Jaccard’s Coefficient. We propose two factors Analogy Profile and Analogy Friendship to obtain the final relationship strength. The performance of our proposed model is compared with the popular existing model, namely Trust Propagation-User Relationship Strength (TP-URS) using the assessment matrices Precision, Recall, and Dice Similarity Coefficient (DSC). Our proposed method provides a precision value of 0.66, recall value of 0.74, and DSC value of 0.71 which are comparatively better than the existing algorithm.

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Correspondence to Deepjyoti Choudhury .

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Choudhury, D., Acharjee, T. (2023). Effective Estimation of Relationship Strength Among Facebook Users Applying Pearson Correlation and Jaccard’s Coefficient. In: Bhattacharyya, S., Banerjee, J.S., De, D., Mahmud, M. (eds) Intelligent Human Centered Computing. Human 2023. Springer Tracts in Human-Centered Computing. Springer, Singapore. https://doi.org/10.1007/978-981-99-3478-2_2

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