A Fuzzy System for Evaluating Trustworthiness of Users in a Social Network

Authors

DOI:

https://doi.org/10.31436/iiumej.v23i2.1697

Keywords:

Social Network, Web-Based Social Network, Fuzzy logic, Trust

Abstract

In recent years, the emergence of various web-based social networks has led to the growth of social network users. These networks have become popular as a medium for disseminating information and communication. Governments and organizations also use social networks as a platform for better services. However, acting in such networks depends on the level of trust that members have with each other. The combination of personality attributes of a person can create a mental impression of the amount of trust that a person has. This amount of trust can affect the person's future interactions. Therefore, trust is an essential and important matter in these networks, especially when someone interacts with someone else on a web-based social network. We discuss this issue in this paper and provide a method for evaluating it. Measuring the accuracy is not easy for the users who are interacting with the social network. Here, the interactions are virtual. In this paper, we have used fuzzy logic to apply ambiguous data and to evaluate trustworthiness by taking into account the various personality attributes of users such as reliability, availability, interest, patience, and adaptability. As we used these attributes as input to the fuzzy system and based on the relevant fuzzy rules, we evaluated the trustworthiness of users in social networks. The proposed fuzzy system is extendable, because in this system, trust can be defined as a set of one or more personality attributes. Epinions social network dataset is also used to simulate and validate the proposed approach. In the proposed method, the MAE value is less than 0.015 and F-Score value more than 0.86. Based on the results, the presented fuzzy system shows an acceptable accuracy for evaluating the trustworthiness of users.

ABSTRAK: Sejak beberapa tahun kebelakangan ini, kemunculan pelbagai rangkaian web sosial telah menyebabkan pertumbuhan pengguna rangkaian sosial. Rangkaian ini telah menjadi popular sebagai medium penularan informasi dan komunikasi. Kerajaan dan organisasi juga menggunakan rangkaian sosial sebagai platfom bagi menyediakan servis perkhidmatan terbaik. Namun, pemakaian rangkaian ini bergantung kepada kepercayaan pengguna antara sesama pengguna. Gabungan ciri-ciri personaliti terhadap seseorang menyebabkan terciptanya persepsi secara mental pada kepercayaan ke atas seseorang. Jumlah kepercayaan ini akan memberi kesan terhadap interaksi yang akan berlaku pada masa depan ke atas individu tersebut. Oleh itu, kepercayaan sangat penting dalam rangkaian ini, terutama apabila seseorang berinteraksi dengan mereka di jaringan sosial web. Isu ini dibincangkan dalam kajian ini dan kaedah evaluasi turut dihuraikan. Mengukur ketepatan pengguna dalam jaringan sosial tidak mudah. Di sini, interaksi berlaku secara maya. Kajian ini menggunakan logik kabur pada data tidak jelas dan bagi mengukur tahap kepercayaan, pelbagai ciri personaliti individu diukur, seperti kebolehpercayaan, kebolehdapatan, minat, kesabaran dan kebolehsesuian. Ciri-ciri tersebut digunakan sebagai input kepada sistem rawak dan berdasarkan peraturan rawak, tahap kebolehpercayaan pengguna diukur dalam rangkaian sosial. Sistem rawak yang dicadangkan ini boleh dilanjutkan, kerana dalam sistem ini kepercayaan boleh dimaksudkan sebagai satu set atau lebih ciri-ciri personaliti. Anggapan pada set data rangkaian sosial turut digunakan bagi simulasi dan pengesahan kaedah yang dicadangkan. Bagi kaedah yang dicadangkan ini, nilai MAE adalah kurang daripada 0.015 dan nilai skor-F lebih daripada 0.86. Berdasarkan dapatan kajian ini, sistem rawak yang dikaji ini menunjukkan ketepatan yang boleh diterima bagi mengukur tahap kebolehpercayaan pengguna.

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Published

2022-07-04

How to Cite

SHAFIEI, M. M. ., SHIRGAHI, H., MOTAMENI, H., & BARZEGAR, B. . (2022). A Fuzzy System for Evaluating Trustworthiness of Users in a Social Network. IIUM Engineering Journal, 23(2), 154–170. https://doi.org/10.31436/iiumej.v23i2.1697

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Section

Engineering Mathematics and Applied Science