A multi-platform framework for nowcasting social phenomena: A case study for food insecurity
Given the growing significance of internet-based information flows, this research proposes a conceptual framework that integrates digital platforms to nowcast social phenomena, applied to the context of food security monitoring in the Global South. Building on the foundations of Digital Methods and...
| Main Authors: | , , , , , , , |
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| Format: | Conference Paper |
| Language: | Inglés |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/149325 |
| _version_ | 1855517739148378112 |
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| author | Carneiro, Bia Resce, Giuliano Tucci, Giulia Ruscica, Giosue Caravaggio, Nicola Fanelli, Laura Santangelo, Agapito Emanuele Cruciata, Pietro |
| author_browse | Caravaggio, Nicola Carneiro, Bia Cruciata, Pietro Fanelli, Laura Resce, Giuliano Ruscica, Giosue Santangelo, Agapito Emanuele Tucci, Giulia |
| author_facet | Carneiro, Bia Resce, Giuliano Tucci, Giulia Ruscica, Giosue Caravaggio, Nicola Fanelli, Laura Santangelo, Agapito Emanuele Cruciata, Pietro |
| author_sort | Carneiro, Bia |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Given the growing significance of internet-based information flows, this research proposes a conceptual framework that integrates digital platforms to nowcast social phenomena, applied to the context of food security monitoring in the Global South. Building on the foundations of Digital Methods and online issue mapping, our research objective is to establish a multi-modal, multi-media model that monitors events from different perspectives to identify potential early warning signals arising from the data, ultimately informing policy actors and supporting early action. We apply three analytical processes: social listening, media monitoring and search interest analysis. Exploratory analysis on data from Zimbabwe point to the feasibility of the models applied to identify food security dimensions in text and search engine data. Further analysis is needed to interpret converging and diverging trends across the data streams, and their implications to food insecurity early warning. |
| format | Conference Paper |
| id | CGSpace149325 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| record_format | dspace |
| spelling | CGSpace1493252025-11-05T11:05:44Z A multi-platform framework for nowcasting social phenomena: A case study for food insecurity Carneiro, Bia Resce, Giuliano Tucci, Giulia Ruscica, Giosue Caravaggio, Nicola Fanelli, Laura Santangelo, Agapito Emanuele Cruciata, Pietro machine learning food security early warning systems text mining social media digital methods monitoring systems newspapers telegram digital platforms nowcasting google trends Given the growing significance of internet-based information flows, this research proposes a conceptual framework that integrates digital platforms to nowcast social phenomena, applied to the context of food security monitoring in the Global South. Building on the foundations of Digital Methods and online issue mapping, our research objective is to establish a multi-modal, multi-media model that monitors events from different perspectives to identify potential early warning signals arising from the data, ultimately informing policy actors and supporting early action. We apply three analytical processes: social listening, media monitoring and search interest analysis. Exploratory analysis on data from Zimbabwe point to the feasibility of the models applied to identify food security dimensions in text and search engine data. Further analysis is needed to interpret converging and diverging trends across the data streams, and their implications to food insecurity early warning. 2024-07 2024-07-31T07:11:01Z 2024-07-31T07:11:01Z Conference Paper https://hdl.handle.net/10568/149325 en Open Access application/pdf Carneiro, B.; Resce, G.; Tucci, G.; Ruscica, G.; Caravaggio, N.; Fanelli, L.; Santangelo, A.E.; Cruciata, P. (2024) A multi-platform framework for nowcasting social phenomena: A case study for food insecurity. 6th International Conference on Advanced Research Methods and Analytics (CARMA 2024). Valencia, 26-28 June 2024. 8 p. |
| spellingShingle | machine learning food security early warning systems text mining social media digital methods monitoring systems newspapers telegram digital platforms nowcasting google trends Carneiro, Bia Resce, Giuliano Tucci, Giulia Ruscica, Giosue Caravaggio, Nicola Fanelli, Laura Santangelo, Agapito Emanuele Cruciata, Pietro A multi-platform framework for nowcasting social phenomena: A case study for food insecurity |
| title | A multi-platform framework for nowcasting social phenomena: A case study for food insecurity |
| title_full | A multi-platform framework for nowcasting social phenomena: A case study for food insecurity |
| title_fullStr | A multi-platform framework for nowcasting social phenomena: A case study for food insecurity |
| title_full_unstemmed | A multi-platform framework for nowcasting social phenomena: A case study for food insecurity |
| title_short | A multi-platform framework for nowcasting social phenomena: A case study for food insecurity |
| title_sort | multi platform framework for nowcasting social phenomena a case study for food insecurity |
| topic | machine learning food security early warning systems text mining social media digital methods monitoring systems newspapers telegram digital platforms nowcasting google trends |
| url | https://hdl.handle.net/10568/149325 |
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