Suwani Gunasekara

While short video platforms such as TikTok, YouTube Shorts, and Instagram Reels are frequently criticised for facilitating the spread of misinformation, they are also increasingly leveraged as tools for countering it through debunking content. Although video-based corrections have demonstrated effectiveness, their persuasive impact may depend on the richness of their audio-visual elements. This study examines the persuasive efficacy of three fundamental presentation styles commonly used in short-form video content: (1) videos featuring only captions, (2) captions accompanied by relevant images, and (3) captions presented alongside the creator’s visible face. Our results indicate that videos incorporating either relevant and engaging imagery or the creator’s facial presence are significantly more persuasive than those relying solely on captions. Based on these findings, we propose practical recommendations for improving the effectiveness of debunking videos, with the aim of promoting belief revision and mitigating misinformation on short video platforms.

Social media has blurred the line between professional journalism and personality-driven commentary, yet we know little about how users evaluate credibility and engage with news from influencers and legacy media when they appear in the same feed. This short paper investigates how political ideology and news source type shape perceived credibility and follow intentions on Instagram. We conducted a mixed-methods experiment where U.S.-based participants (N=120) viewed a set of real news posts and rated the credibility of four accounts (two legacy media–based, two influencer-based), balanced by ideology (two left-leaning, two right-leaning), and indicated whether they would follow each account. Our findings suggest that perceived credibility on Instagram is multi-dimensional, rooted in ideological alignment, yet moderated by institutional signals and perceived authenticity. These insights highlight how platform design and source dynamics can reinforce selective exposure, with implications for both mitigating polarisation and strengthening trust in online news ecosystems.

Virtual influencers (VIs) are gaining prominence on social media. Although fictional, they frequently adopt the communication strategies used by human influencers (HIs) to foster stronger audience connections. In this paper, we examine differences in user engagement between HIs and three VI types (Mimic-Real Human, Animated Human, Non-Human) when sharing self-disclosure content on Instagram. We analysed captions, reels, likes, and comments from eight influencers, and categorised their posts by self-disclosure category (informational, cognitive, affective), level (none, low, high), and emotional valence, alongside sentiment analysis of comments. Our findings show that HIs attracted higher positive engagement and lower negative comments compared to all VI types. However, Mimic-Real Human VIs outperform other influencer types, including HIs, by receiving a higher proportion of likes and comments in specific self-disclosure categories. These results advance our understanding of user engagement in the evolving virtual influencer ecosystem and provide recommendations for the design of virtual personas.