## 2 Background and Motivation
This prompts us to explore the potential of predicting virtual team performance through multi-modal data analysis, focusing on emotional states and conversational dynamics. This research builds on existing studies that highlight the significance of emotions and communication styles as significant drivers of team outcomes [49]. Given the insightful nature of emotions and conversational patterns in revealing team dynamics and effectiveness, we propose the following hypothesis:  
Teams with higher levels of positive emotional states, such as happiness, will demonstrate improved performance [47; 48]. Balanced conversation dynamics of teams characterized by equitable conversation length and alternating turn-taking behavior among team members positively correlate with improved team performance [15]. Feedback is essential for team dynamics, serving as a critical tool for evaluating and improving performance [14]. Effective feedback in virtual teams can be categorized by its content, source, and level [50]. Content refers to the focus of the feedback, whether it is on team input, mediator processes, or output [51]. Feedback can be subjective, based on perceptions and evaluations, or objective, derived from concrete actions and events [52]. The level of feedback varies between individuals, teams, and team-plus-individuals, providing insights into both collective and individual functioning [53]. Real-time feedback, with its immediacy, can significantly enhance learning and performance by providing instant reinforcement or correction [54]. For virtual teams, it is especially beneficial as it integrates performance-related information with team processes and psychological states, offering immediate insights and facilitating timely adjustments [50]. This immediacy addresses the lack of physical cues and direct interactions, fostering alignment and collaboration [55]. **Hypothesis 3**. : _Teams receiving real-time feedback about their emotional state will show improved performance, as evidenced by increased performance scores [56]._  
One application of real-time feedback is virtual mirroring, where individuals are made aware of their emotions and communication behaviors in real-time [57]. This involves analyzing team communication patterns and mirroring them back to encourage introspection and adaptation, aligning behaviors with team goals. This fosters self-awareness and collective understanding of team emotions, optimizing team dynamics [58]. Use cases in large organizations have shown significant improvements in performance through this method [58], while respecting individual privacy by providing aggregated information. Considering the potential of real-time feedback in emotional regulation and its implications for team strategies, we ask: How does real-time feedback about team emotions affect the emotional state of the team? In response to the research question and based on existing findings in the literature, we have formulated the following hypotheses:  
**Hypothesis 4**. : _Teams exposed to real-time emotional feedback will experience better emotional regulation, evidenced by reduced emotional variance [50]._  
**Hypothesis 5**. : _Teams receiving real-time feedback on their emotional states are likely to exhibit a broader emotional spectrum during collaboration, as indicated by higher variations of positive and negative emotions other than the neutral state [59]._  
This research aims to investigate virtual team dynamics and un-cover the factors that contribute to team success in digitally transformed work environments. We address the overarching research question: \"_How can real-time emotional feedback, informed by multimodal data analysis, enhance the performance and emotional dynamics of virtual teams, and what factors most effectively predict successful team collaboration?_\" Utilizing advanced techniques such as multi-modal data analysis and machine learning, this study seeks actionable insights to optimize team performance with modern digital technology.