Investigating public biodiversity conservation awareness based on the propagation of wildlife-related incidents on the Sina Weibo social media platform

Abstract

The use of social media platforms (e.g. Twitter and Facebook) to raise public awareness towards wildlife conservation is an emerging discussion. However, little is currently known about the propagation pattern of wildlife-related information on social media. In this study, a quantitative model was developed based on 230 independent cetacean stranding incidents (2008–2018) across mainland China from a popular Chinese social media platform (Sina Weibo). This model enabled analysis of the post formation process, identification of the key factors influencing the popularity of the posts and wildlife-related incidents, and allowed investigation of public opinions. The results showed that central media users can increase the overall possibility of elevating incident popularity by ∼75 times, an attractive species or incident by ∼5 times, and a negative social ethics incident by ∼3 times. Traditional media users and celebrity influencers performed key roles in affecting the level of re-posting. Online audiences of highly popular posts predominantly encompassed both users from relatively developed regions and female users. It was observed that posts which became popular within ∼12 h retained their influence for ∼3 d. Post popularity was closely related to comment counts rather than forwarding in the first day of posting and the whole status retention time. Public opinion generally expressed a supportive attitude towards wildlife conservation, but lacked in-depth thinking, and individual responsibility was expressed through revival incidents. In order to raise public awareness towards biodiversity conservation, social media–based wildlife information dissemination should balance the content of attractive and non-charismatic species or incidents and include more positive emotions. Posts via traditional users (especially central media users) and opinion leaders (celebrities) can attract a highly educated audience and females, and thus evoke increased comment numbers during the first day of posting. This will help to popularise conservation knowledge and legislation with continuous efforts.

Keywords

• biodiversity conservation
• public perceptions
• big data
• data mining
• ordinal multi-nominal logistic model