Mining text for causality: a new perspective on food safety crisis management
The aim of the present study was to quantitatively analyze the importance of each risk factor in a food safety event, so as to fully elucidate the correlation between different risk factors and provide a reference for food safety governance. Text mining and complex network analysis methods were util...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-11-01
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| Series: | Frontiers in Sustainable Food Systems |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fsufs.2024.1491255/full |
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| author | Jinyi Song Jiayin Pei |
| author_facet | Jinyi Song Jiayin Pei |
| author_sort | Jinyi Song |
| collection | DOAJ |
| description | The aim of the present study was to quantitatively analyze the importance of each risk factor in a food safety event, so as to fully elucidate the correlation between different risk factors and provide a reference for food safety governance. Text mining and complex network analysis methods were utilized to explore the causal mechanism of food safety incidents. By performing text mining on food safety event news reports, 15 major risk factors were identified based on high-frequency words. A causal network for food safety accidents was then constructed using strong association rules among these factors. Through network centrality analysis, the five core factors of food safety incidents and their associated sets were clarified. Based on text mining of 6,282 cases of food safety incidents reported by online media, 168 keywords related to food risk factors were extracted and further categorized into 15 types of food safety risk factors. Network analysis results revealed that microbial infection emerged as the most critical risk factor, with its associated sets including biotoxins and parasites, counterfeiting or fraud, processing process issues, and non-compliance with quality indicators. |
| format | Article |
| id | doaj-art-15ec0e7c641343f3bcd7cb0f113487e9 |
| institution | Kabale University |
| issn | 2571-581X |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Sustainable Food Systems |
| spelling | doaj-art-15ec0e7c641343f3bcd7cb0f113487e92024-11-12T04:40:55ZengFrontiers Media S.A.Frontiers in Sustainable Food Systems2571-581X2024-11-01810.3389/fsufs.2024.14912551491255Mining text for causality: a new perspective on food safety crisis managementJinyi SongJiayin PeiThe aim of the present study was to quantitatively analyze the importance of each risk factor in a food safety event, so as to fully elucidate the correlation between different risk factors and provide a reference for food safety governance. Text mining and complex network analysis methods were utilized to explore the causal mechanism of food safety incidents. By performing text mining on food safety event news reports, 15 major risk factors were identified based on high-frequency words. A causal network for food safety accidents was then constructed using strong association rules among these factors. Through network centrality analysis, the five core factors of food safety incidents and their associated sets were clarified. Based on text mining of 6,282 cases of food safety incidents reported by online media, 168 keywords related to food risk factors were extracted and further categorized into 15 types of food safety risk factors. Network analysis results revealed that microbial infection emerged as the most critical risk factor, with its associated sets including biotoxins and parasites, counterfeiting or fraud, processing process issues, and non-compliance with quality indicators.https://www.frontiersin.org/articles/10.3389/fsufs.2024.1491255/fullfood safetyrisk factorsbig datatext miningcomplex networks |
| spellingShingle | Jinyi Song Jiayin Pei Mining text for causality: a new perspective on food safety crisis management Frontiers in Sustainable Food Systems food safety risk factors big data text mining complex networks |
| title | Mining text for causality: a new perspective on food safety crisis management |
| title_full | Mining text for causality: a new perspective on food safety crisis management |
| title_fullStr | Mining text for causality: a new perspective on food safety crisis management |
| title_full_unstemmed | Mining text for causality: a new perspective on food safety crisis management |
| title_short | Mining text for causality: a new perspective on food safety crisis management |
| title_sort | mining text for causality a new perspective on food safety crisis management |
| topic | food safety risk factors big data text mining complex networks |
| url | https://www.frontiersin.org/articles/10.3389/fsufs.2024.1491255/full |
| work_keys_str_mv | AT jinyisong miningtextforcausalityanewperspectiveonfoodsafetycrisismanagement AT jiayinpei miningtextforcausalityanewperspectiveonfoodsafetycrisismanagement |