Analyzing Social Landscapes: Visualizing the Key Elements of Social Media Dynamics

Social media provides valuable insights into societal opinions and user interactions. Social landscapes, created from these interactions, offer a comprehensive view of online conversations and social media dynamics. The development of advanced data analytics tools has made the creation of social landscapes for larger populations increasingly common and accessible for researchers. This underscores the importance of clearly defining and organizing the insights we seek from social landscapes. We introduce a methodology to analyze the social structure through social landscapes. We have identified 12 key elements that encapsulate the insights expected from social landscapes. Then, we integrate two comprehensive social landscape approaches into our methodology that effectively provide insights into the key elements previously outlined. These two approaches illuminate different facets of social media dynamics: one focuses on the content generated and the other on relationship-based interactions. First, we revisit the concept of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">galaxies</i> as a single time-based snapshot of large-scale online conversations. Second, we introduce a technique that utilizes the network of user interactions on social media to map social structures. We propose a novel method to construct a sociopolitical spectrum using discourse trajectory inference (pseudotime transformation), marking its first use outside bioinformatics literature. Finally, we take the introduced methodology to evaluate how each social landscape enhances our understanding of social media dynamics. These insights can help to structure the insights we aim to extract from social landscapes and provide practical tools for media analysts and strategists aiming to analyze social media dynamics effectively.