Credit Scoring with AHP and Fuzzy Comprehensive Evaluation Based on Behavioural Data from Weibo Platform
It is increasingly necessary to evaluate the customers' credit. In the era of big data, Information on the Internet is commonly used to judge the credit worthiness of customers. Some users' credit information is incomplete or unavailable, so credit managers cannot judge the true credit sit...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2019-01-01
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| Series: | Tehnički Vjesnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/320437 |
| _version_ | 1827282696001290240 |
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| author | Jia Yu Jianrong Yao Yuangao Chen |
| author_facet | Jia Yu Jianrong Yao Yuangao Chen |
| author_sort | Jia Yu |
| collection | DOAJ |
| description | It is increasingly necessary to evaluate the customers' credit. In the era of big data, Information on the Internet is commonly used to judge the credit worthiness of customers. Some users' credit information is incomplete or unavailable, so credit managers cannot judge the true credit situation of these users. However, with the support of social data especially behavioural data and credit evaluation system, this problem can be effectively solved. This study used Weibo to obtain the behavioural data of Chinese users for credit evaluation. Two methods are used to calculate the credit scores of Weibo users, which are the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation methods. By analysing social processes and inviting experts to make decisions, we constructed a credit evaluation system to expose users' behavioural characteristics. We found that the three key indexes determining the user’s social credit are personal identification, behavioural characteristics and interaction among friends. Then, AHP was used to determine the weight of each index. Finally, a static algorithm was proposed to compute the credit evaluation system of Weibo users using fuzzy comprehensive evaluation methods. |
| first_indexed | 2024-04-24T09:22:31Z |
| format | Article |
| id | doaj.art-6da08aadb2c44d6db4739acb2baf6e10 |
| institution | Directory Open Access Journal |
| issn | 1330-3651 1848-6339 |
| language | English |
| last_indexed | 2024-04-24T09:22:31Z |
| publishDate | 2019-01-01 |
| publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
| record_format | Article |
| series | Tehnički Vjesnik |
| spelling | doaj.art-6da08aadb2c44d6db4739acb2baf6e102024-04-15T15:31:00ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392019-01-0126246247010.17559/TV-20181217180231Credit Scoring with AHP and Fuzzy Comprehensive Evaluation Based on Behavioural Data from Weibo PlatformJia Yu0Jianrong Yao1Yuangao Chen2School of Information, Zhejiang University of Finance and Economics, Hangzhou 310018, ChinaSchool of Information, Zhejiang University of Finance and Economics, Hangzhou 310018, ChinaSchool of Information, Zhejiang University of Finance and Economics, Hangzhou 310018, ChinaIt is increasingly necessary to evaluate the customers' credit. In the era of big data, Information on the Internet is commonly used to judge the credit worthiness of customers. Some users' credit information is incomplete or unavailable, so credit managers cannot judge the true credit situation of these users. However, with the support of social data especially behavioural data and credit evaluation system, this problem can be effectively solved. This study used Weibo to obtain the behavioural data of Chinese users for credit evaluation. Two methods are used to calculate the credit scores of Weibo users, which are the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation methods. By analysing social processes and inviting experts to make decisions, we constructed a credit evaluation system to expose users' behavioural characteristics. We found that the three key indexes determining the user’s social credit are personal identification, behavioural characteristics and interaction among friends. Then, AHP was used to determine the weight of each index. Finally, a static algorithm was proposed to compute the credit evaluation system of Weibo users using fuzzy comprehensive evaluation methods.https://hrcak.srce.hr/file/320437credit scoringbehavioural datafuzzy comprehensive evaluationsocial media platformWeibo |
| spellingShingle | Jia Yu Jianrong Yao Yuangao Chen Credit Scoring with AHP and Fuzzy Comprehensive Evaluation Based on Behavioural Data from Weibo Platform Tehnički Vjesnik credit scoring behavioural data fuzzy comprehensive evaluation social media platform |
| title | Credit Scoring with AHP and Fuzzy Comprehensive Evaluation Based on Behavioural Data from Weibo Platform |
| title_full | Credit Scoring with AHP and Fuzzy Comprehensive Evaluation Based on Behavioural Data from Weibo Platform |
| title_fullStr | Credit Scoring with AHP and Fuzzy Comprehensive Evaluation Based on Behavioural Data from Weibo Platform |
| title_full_unstemmed | Credit Scoring with AHP and Fuzzy Comprehensive Evaluation Based on Behavioural Data from Weibo Platform |
| title_short | Credit Scoring with AHP and Fuzzy Comprehensive Evaluation Based on Behavioural Data from Weibo Platform |
| title_sort | credit scoring with ahp and fuzzy comprehensive evaluation based on behavioural data from weibo platform |
| topic | credit scoring behavioural data fuzzy comprehensive evaluation social media platform |
| url | https://hrcak.srce.hr/file/320437 |
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