AI summaries on social media are reshaping how users form opinions about political topics, yet their influence remains largely unexamined despite their widespread deployment. This paper investigates how two types of AI summaries affect user opinions and engagement: textual summaries of discussion narratives and percentage breakdowns of agreement/disagreement. Through a 144-participant experiment on simulated online discussion threads, we found that displaying commenter agreement percentages amplified social conformity towards the majority views beyond reading comments alone. Conversely, AI narrative summaries created misperceptions of balance in polarised threads, reducing opinion change. While these summaries did not influence participants’ willingness to engage, toxic discussions deterred participation even when participants held majority views. Based on our findings, we provide critical design interventions for industry and researchers to mitigate these tools’ polarising effects, paving the way for responsible AI deployment on social media platforms.

Short-form video platforms have become major channels for misinformation, with their rich multimodal features making false claims highly believable. HCI research shows that providing corrections in the same modality as the misinformation can be an effective solution. However, since corrections and misinformation convey contradicting information, the order in which one is exposed to them can impact what one believes. We conducted a between-subjects mixed-methods experiment where participants (N=120) rated the credibility of misinformation statements before and after viewing misinformation videos paired with correction videos. Corrections were shown either before, during, or after misinformation. Across all three timings, corrections reduced belief in misinformation, but post-exposure corrections proved most effective and mid-exposure corrections least effective. These findings suggest that correction mechanisms should appear after misinformation exposure, while avoiding mid-exposure interruptions that reduce impact. We outline design recommendations for integrating correction videos into short-form video platforms to improve resilience against misinformation.

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.

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.

Virtual AI-generated Influencers (VAIIs) are increasingly being used by corporations and public agencies, raising questions about how their visual design and communication strategies impact end-users’ propensity to accept the messages they deliver. We examined the impact of human-likeness (how closely a VAII resembles a human) and self-disclosure (whether the message contains personal information) on message acceptance, alongside dispositional factors like empathy and anthropomorphising tendencies. In a mixed-methods experiment, participants (N=120) watched short-form videos featuring VAIIs of varying human-likeness (High/Moderate-High/Moderate-Low/Low) and self-disclosure (present/absent). We observed the strongest message acceptance from the VAIIs with the lowest human-likeness, and message rejection for VAIIs with moderate to low human-likeness. Additionally, participants’ message acceptance was influenced by their empathy tendencies. Our qualitative analysis revealed further insights into participants’ perceptions of the human-likeness of VAIIs, their discomfort with self-disclosure, and their tendency to anthropomorphise VAIIs. These findings provide important implications for the design of VAIIs.

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As the number of applications installed on smartphones continues to grow, the task of effectively managing location privacy has become increasingly complex. In this paper, we explore the factors that influence users' privacy-preserving intentions and contrast them with their actual behaviours. In addition, we compare location privacy concerns across different apps investigating the impact of app-specific features on the willingness to disclose location information. Our findings highlight significant challenges in privacy management due to privacy fatigue and perceived usability. Furthermore, participants raised the importance of more uniform standards regarding location privacy settings across various applications, calling for more detailed and interactive well-informed consent processes that highlight the risks instead of the benefits of disclosing location information. This research contributes important insights towards the development of more effective privacy settings that can foster increased user engagement in managing location privacy on smartphones.