Publicação
Social media intelligence and wildlife crime: A quantitative analysis.
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | |
| datacite.subject.sdg | 15:Proteger a Vida Terrestre | |
| dc.contributor.author | Santos, Lara | |
| dc.contributor.author | Lopes, Luisa | |
| dc.contributor.author | Correia, Mariana | |
| dc.date.accessioned | 2026-02-23T12:13:06Z | |
| dc.date.available | 2026-02-23T12:13:06Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | This paper explores the role of social media intelligence (SMI) and digital marketing—particularly data-driven analytics, social media marketing, and social media platforms—as instruments for analysing and addressing wildlife crime in online spaces, focusing on illegal animal trafficking. This is a descriptive study based on a quantitative approach. A bibliometric analysis was conductedusing the Web of Science database, complemented by a quantitative analysis of data extracted from the European Union project ECO-SOLVE platform and the United Nations Office on Drugs and Crime (UNODC) platform, to identify the main patterns of action of traffickers on social networks. The results show a growing number of research studies interested in applying digital tools to track and prevent illegal animal trafficking, with a predominance of scientific publications in the areas of environmental sciences and criminology. The results also indicate the use of digital social networks by criminals, with Facebook standing out as the main platform for disseminating ads. By leveraging SMI, authorities and digital platforms can proactively identify and disrupt illegal activities, particularly on platforms like Facebook, which are frequently exploited by traffickers. The findings call for urgent, collaborative, and ethical action among institutions, law enforcement, and social media companies to enhance the effectiveness of digital tools in addressing this global issue. The Scopus database was not included in the analysis, and so the inability to access specific data may have restricted the scope of the research. The conclusion highlights that SMI is a promising approach to monitoring and combating wildlife trafficking. It emphasises originality by suggesting that maximising its effectiveness requires integrated and ethical action between institutions, authorities, and digital platforms. This study underscores the critical role of SMI in revolutionising enforcement practices and digital communication strategies to combat wildlife trafficking. | eng |
| dc.identifier.citation | Santos, L.; Lopes, L.; Correia, M. (2025). Social media intelligence and wildlife crime: A quantitative analysis. International Journal of Marketing, Communication and New Media. ISSN: 2182-9306. 13:25, p.235-258 | |
| dc.identifier.doi | 10.54663/2182-9306.2025.v.13.n.235-258 | |
| dc.identifier.issn | 2182-9306 | |
| dc.identifier.uri | http://hdl.handle.net/10198/35822 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Social media marketing | |
| dc.subject | Social media plataforms | |
| dc.subject | Social media intelligence | |
| dc.subject | Data-driven marketing | |
| dc.subject | Marketing analytics | |
| dc.subject | Wildlife crime | |
| dc.subject | Ilegal trafficking | |
| dc.title | Social media intelligence and wildlife crime: A quantitative analysis. | por |
| dc.type | research article | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 258 | |
| oaire.citation.issue | 25 | |
| oaire.citation.startPage | 235 | |
| oaire.citation.title | International Journal of Marketing, Communication and New Media | |
| oaire.citation.volume | 13 | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| person.familyName | Lopes | |
| person.givenName | Luisa | |
| person.identifier.ciencia-id | E41C-366E-BE9E | |
| person.identifier.orcid | 0000-0003-2039-0125 | |
| relation.isAuthorOfPublication | 4410123f-7cc3-4a8d-a596-4a08d1d13b5b | |
| relation.isAuthorOfPublication.latestForDiscovery | 4410123f-7cc3-4a8d-a596-4a08d1d13b5b |