Amalgamating social media and music based Information Visualization using AI
In the world of chaos where everyone is seeking motivation, peace or energy to survive the day, most people resort to music to gain those essential elements. Our research in this project entails user grievances while interacting with bulky text- centric interfaces. Research has indeed shown that ’a visual’ flavour to information creates long lasting memories in the reader’s mind, especially the people who think and learn visually. Prior work has shown how Machine Learning and Artificial Intelligence can be used to generate clusters to depict songs that can replace the lengthy playlists in music platforms. Humans, being social animals, look for a community to thrive in. Same is the case with the users of social media applications. Journeying through four user studies, deriving grounded theory codes from the qualitative and quantitative data gathered in interviews and observations, we developed a functional prototype of a social media platform dedicated for music enthusiasts. Iterating over light weight prototypes, resulted from user scenarios and storyboards, the whole development process involved constant user involvement. The user feedback and suggestions extracted from each user study, using the prototype as a probe, were analyzed and incorporated in each iteration. The paper discusses the user research using various study methodologies, the findings discovered during the research, iterative design as well as the future scope of scaling this prototype to facilitate advanced context-aware systems.