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• W4283263265 abstract "Purpose Social media data from financial websites contain information related to enterprise credit risk. Mining valuable new features in social media data helps to improve prediction performance. This paper proposes a credit risk prediction framework that integrates social media information to improve listed enterprise credit risk prediction in the supply chain. Design/methodology/approach The prediction framework includes four stages. First, social media information is obtained through web crawler technology. Second, text sentiment in social media information is mined through natural language processing. Third, text sentiment features are constructed. Finally, the new features are integrated with traditional features as input for models for credit risk prediction. This paper takes Chinese pharmaceutical enterprises as an example to test the prediction framework and obtain relevant management enlightenment. Findings The prediction framework can improve enterprise credit risk prediction performance. The prediction performance of text sentiment features in social media data is better than that of most traditional features. The time-weighted text sentiment feature has the best prediction performance in mining social media information. Practical implications The prediction framework is helpful for the credit decision-making of credit departments and the policy regulation of regulatory departments and is conducive to the sustainable development of enterprises. Originality/value The prediction framework can effectively mine social media information and obtain an excellent prediction effect of listed enterprise credit risk in the supply chain." @default.
• W4283263265 created "2022-06-23" @default.
• W4283263265 creator A5008810320 @default.
• W4283263265 creator A5058795894 @default.
• W4283263265 creator A5061570010 @default.
• W4283263265 creator A5088644141 @default.
• W4283263265 date "2022-06-22" @default.
• W4283263265 modified "2023-09-27" @default.
• W4283263265 title "Using social media information to predict the credit risk of listed enterprises in the supply chain" @default.
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• W4283263265 cites W1994824189 @default.
• W4283263265 cites W2004076523 @default.
• W4283263265 cites W2004473119 @default.
• W4283263265 cites W2013285825 @default.
• W4283263265 cites W2018209163 @default.
• W4283263265 cites W2026572648 @default.
• W4283263265 cites W2048658075 @default.
• W4283263265 cites W2048945213 @default.
• W4283263265 cites W2058307797 @default.
• W4283263265 cites W2075219207 @default.
• W4283263265 cites W2083291852 @default.
• W4283263265 cites W2087936817 @default.
• W4283263265 cites W2090668243 @default.
• W4283263265 cites W2092747527 @default.
• W4283263265 cites W2093064636 @default.
• W4283263265 cites W2098738227 @default.
• W4283263265 cites W2103780778 @default.
• W4283263265 cites W2137334813 @default.
• W4283263265 cites W2139120543 @default.
• W4283263265 cites W2171468534 @default.
• W4283263265 cites W2259814617 @default.
• W4283263265 cites W2334959554 @default.
• W4283263265 cites W2400568945 @default.
• W4283263265 cites W2403788329 @default.
• W4283263265 cites W2408383986 @default.
• W4283263265 cites W2425956735 @default.
• W4283263265 cites W2523224585 @default.
• W4283263265 cites W2587091557 @default.
• W4283263265 cites W2588176548 @default.
• W4283263265 cites W2622765476 @default.
• W4283263265 cites W2624239644 @default.
• W4283263265 cites W2758688634 @default.
• W4283263265 cites W2761075141 @default.
• W4283263265 cites W2780508324 @default.
• W4283263265 cites W2782609450 @default.
• W4283263265 cites W2793298921 @default.
• W4283263265 cites W2797682158 @default.
• W4283263265 cites W2897596136 @default.
• W4283263265 cites W2898153843 @default.
• W4283263265 cites W2901657898 @default.
• W4283263265 cites W2911450871 @default.
• W4283263265 cites W2918825256 @default.
• W4283263265 cites W2940658499 @default.
• W4283263265 cites W2944580602 @default.
• W4283263265 cites W2949985842 @default.
• W4283263265 cites W2959466452 @default.
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• W4283263265 cites W3122283149 @default.
• W4283263265 cites W3122628491 @default.
• W4283263265 cites W3123399111 @default.
• W4283263265 cites W3124197748 @default.
• W4283263265 cites W3124440722 @default.
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• W4283263265 doi "https://doi.org/10.1108/k-12-2021-1376" @default.
• W4283263265 hasPublicationYear "2022" @default.
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