Visualisation for social media analytics: landscape of R packages

While existing literature indicates challenges and difficulties involved in analyzing social media data, limited research evaluated the capabilities of visualization methods to understand the behavior of individuals through their connections on social media platforms. Despite the need and growing demand in the industry at all stages of collection, preparation and analysis; a structured approach is missing in identifying the appropriate methods for visualization in social media analytics. To address the gap, we explored literature to propose methods to benefit researchers and practitioners who seek better understanding of analyzing social media data through visualization. This paper investigates the use of open source R environment in visualization with a focus on application in Social Network Analytics (SNA) and Social media analytics (SMA). SNA provides a foundation to study complex networks by considering distinct elements (nodes or vertices) and the connections between them (links or edges). The aim is to identify existing approaches and tools used in social network science and map them to existing packages and tools for visualization in SNA and SMA. This study contributes to the literature by providing an organized framework of available visualization tools in R that fit the needs of SNA and SMA. This provides opportunities for further application and software development to address emerging areas of need through analyzing the landscape of R packages.