Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Penryn, UK.
World Parrot Trust, Hayle, UK.
Conserv Biol. 2022 Apr;36(2):e13858. doi: 10.1111/cobi.13858. Epub 2022 Jan 17.
Wildlife trade has rapidly expanded on social media platforms in recent years, offering an easy means for traders to access international markets. Investigating this trade activity poses a complex challenge to researchers seeking to understand online trade and moderators seeking to disrupt illicit and harmful activity. Current survey methods frequently rely on text-based searches and focus on posts in which the advertisement is explicit. However, such approaches risk overlooking a growing volume of relevant content, particularly outside social media groups. We used posts from pages promoting West African birds for trade as a case study to explore the availability of information for making inferences about trade activity on social media, specifically information indicating that trade activity was occurring or that could be used to infer trade routes. We recorded 400 posts from 12 pages that we inferred either promoted or facilitated wildlife trade, of which 19.7% were explicit advertisements and 23.8% contained taxa-related terms. In the remaining 341 posts, profile information was the most common indicator of trade activity, but a variety of indicators (e.g., images of birds in trade and trade enquiries) were identified across imagery, text, and comments. We identified multiple types of geographical information that could help infer trade routes and thus the likely legality of trade, although most were relatively rare and sometimes contradictory. Our findings suggest that triangulating multiple types of information from within, across, and beyond posts is vital for effectively identifying and interpreting wildlife trade content on social media. Therefore, were commend that expert-mediated triangulation should be integrated in and used alongside automated detection systems and moderating practices of social media companies.
近年来,野生动物交易在社交媒体平台上迅速扩张,为交易商提供了进入国际市场的便捷途径。研究人员若要了解在线交易,监管者若要打击非法和有害活动,都面临着这一交易活动的复杂挑战。目前的调查方法经常依赖于基于文本的搜索,并侧重于广告明确的帖子。然而,这种方法有可能会忽略大量相关内容,尤其是在社交媒体群组之外。我们使用了宣传西非鸟类贸易的页面上的帖子作为案例研究,以探讨在社交媒体上进行贸易活动推断的信息可用性,特别是表明贸易活动正在发生或可用于推断贸易路线的信息。我们从 12 个页面上记录了 400 个帖子,我们推断这些页面要么宣传,要么为野生动物交易提供便利,其中 19.7%是明确的广告,23.8%包含与分类群相关的术语。在其余 341 个帖子中,个人资料信息是最常见的交易活动指标,但在图像、文本和评论中都发现了各种指标(例如,交易中的鸟类图像和贸易咨询)。我们确定了多种类型的地理信息,这些信息有助于推断贸易路线,从而推断贸易的合法性,尽管大多数信息相对较少,而且有时相互矛盾。我们的研究结果表明,从帖子内部、帖子之间和帖子之外三角测量多种类型的信息对于有效地识别和解释社交媒体上的野生动物交易内容至关重要。因此,我们建议将专家介导的三角测量纳入社交媒体公司的自动检测系统和监管实践中,并加以使用。