MATHEMATICAL RATIONALE FOR CREATING AN APPLICATION FOR CONDUCTING RANDOM MEETINGS «COFFEE BREAK»
Abstract
Modern society is facing an increasing trend of social isolation, as people increasingly rely on social media for interaction instead of face-to-face communication. This lack of in-person contact often leads to feelings of loneliness and disconnection. This study proposes the concept of a mobile application, CoffeeBreak, designed to counteract these trends by offering users a platform to arrange brief, in-person meetings, such as a quick coffee chat. By encouraging users to meet in real life, the application aims to foster meaningful social connections and combat the sense of isolation prevalent in today’s digital world. The core innovation of CoffeeBreak lies in its unique approach to matchmaking. Instead of presenting users with an overwhelming array of choices, the app offers a single match within a specified timeframe, thus addressing the common issue of decision paralysis that can arise when users are presented with too many options. By simplifying the process, CoffeeBreak allows users to spend less time making selections and more time connecting with others. This approach is inspired by practices adopted within large companies, where employees use bots in work chat groups to find a partner for a short meeting. These interactions help raise awareness about the activities in other departments and foster informal and professional connections. Expanding this practice to a broader societal level, CoffeeBreak is intended to provide individuals with the opportunity to network beyond their immediate professional circles. This research has established a conceptual system model and developed the mathematical frameworks necessary to support this type of meeting arrangement. Specifically, the study has defined the concept of the CoffeeBreak mobile application, outlined the system model with detailed subsystems and environment interactions, and formulated mathematical models to form the basis of the candidate selection algorithm. The model ensures that users are matched in a way that promotes engagement, as each participant can be assured that their matched partner is equally motivated for the encounter. As the application continues to evolve, it can incorporate additional scheduling criteria to enhance the quality of matches and distribution. For example, if a user attends a meeting within the first two days, they could unlock the potential for additional matches by the end of the week. Ultimately, CoffeeBreak aims to broaden users' horizons, help them form new professional and informal connections, and enhance their social skills. This study’s findings lay the groundwork for a new tool that encourages in-person interactions, enabling individuals to expand their social networks in a balanced and purposeful manner.
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