Social Media Analysis: CGIAR Climate Security Observatory
| dc.creator | Carneiro, Bia | |
| dc.creator | Resce, Giuliano | |
| dc.creator | Ruscica, Giosuè | |
| dc.creator | Simone, Daniele di | |
| dc.date | 2023-03 | |
| dc.date | 2023-07-25T11:53:52Z | |
| dc.date | 2023-07-25T11:53:52Z | |
| dc.date.accessioned | 2026-06-27T13:21:39Z | |
| dc.description | The Climate Security Observatory (CSO) is an online platform for stakeholder decision-making that provides access to a range of global analyses related to climate and security. The CSO is based on an integrated climate security framework that helps understand the complexity of the climate-security interface. As part of the CSO Methods Paper Series, this report details the method used for the social media analysis. | |
| dc.format | application/pdf | |
| dc.identifier | https://hdl.handle.net/10568/131275 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/56926 | |
| dc.language | en | |
| dc.rights | Open Access | |
| dc.source | Carneiro, B.; Resce, G.; Ruscica, G.; Di Simone, D. (2023) Social Media Analysis: CGIAR Climate Security Observatory. Methods Papers Series 03/2023. 5 p. | |
| dc.subject | social media | |
| dc.subject | text mining | |
| dc.subject | big data | |
| dc.subject | policies | |
| dc.subject | climate | |
| dc.subject | conflicts | |
| dc.subject | machine learning | |
| dc.subject | natural language processing | |
| dc.subject | digital methods | |
| dc.subject | sentiment analysis | |
| dc.subject | climate security | |
| dc.title | Social Media Analysis: CGIAR Climate Security Observatory | |
| dc.type | Brief |
