Comparison of video chat software

Abstract

This thesis compares four video-conferencing platforms—Zoom, Google Meet, Microsoft Teams, and Discord—in terms of technical performance, usability, and contextual suitability for academic and professional communication. Twenty-three technically proficient students completed structured tasks across four common contexts (quick personal calls, formal lectures, group projects, and social interaction); they rated installation/setup, audio/video quality, connection stability, usability (learnability, control discoverability, satisfaction, frustration), and feature effectiveness on 5-point scales, provided open-ended comments, and ranked platforms for each scenario. Descriptive statistics and rank summaries were used to quantify performance, and a brief thematic analysis was applied to explain observed patterns. Overall, Google Meet achieved the highest mean score (4.8/5), closely followed by Zoom (4.6/5). Microsoft Teams (4.1/5) and Discord (3.6/5) followed. Effectiveness was context-dependent: Zoom was preferred for structured lectures and formal sessions; Google Meet for low-friction calls and document-centric collaboration; Discord for persistent social/group presence; and Teams remained consistently strong for coordinated organizational work. Qualitative comments emphasized Teams’ integration, Meet’s simplicity, Discord’s community affordances, and Zoom’s strong host controls alongside periodic reliability frustrations. Security and resource-use observations reflect vendor documentation and participant perceptions; no instrumented CPU, memory, or bandwidth measurements or independent security audits were performed. The findings recommend selecting platforms according to context and user goals rather than seeking a universal “best.” Limitations include the small, relatively homogeneous sample (n=23), desktop-only testing, and the time-bounded nature of the evaluation. Future work should incorporate objective resource instrumentation, mobile clients, larger and more diverse populations, and deeper accessibility/usability testing to validate and extend these results.