NodeXL: Twitter Social Media Network Insights in Just a Few Clicks

Citation

Ahmed W, Meier H & Smith M (2022) NodeXL: Twitter Social Media Network Insights in Just a Few Clicks. In: Quan-Haase A & Sloan L (eds.) The SAGE Handbook of Social Media Research Methods. 2nd ed. London: SAGE, pp. 487-502. https://uk.sagepub.com/en-gb/eur/the-sage-handbook-of-social-media-research-methods/book272098

Abstract
NodeXL enables the collection, analysis, visualization, and reporting on collections of annotated connections. NodeXL network data sets can be imported from a range of data sources and processed into insightful reports that can highlight the overall shape of a network, the main divisions or clusters within it, and the leading voices at the center of each cluster. NodeXL output can be used to inform analysis of complex relationships, often drawn from social media platforms. By removing the need to master programming skills to perform social media network analysis, NodeXL is intended to expand access to the essential data needed for critical empirical studies of computer mediated collective action. This chapter provides an introduction on how to retrieve data using NodeXL and a guide to incorporate findings in academic research and practice. We illustrate these findings with a study of the tweets related to medical condition discussions and the Russell Group universities in the UK. NodeXL seeks to simplify the mechanical process of data collection, analysis, visualization and reporting so that researchers can focus on the meaning and implications of images and data rather than on the process of creating the image and data.

Keywords
Social Media; Social Networks; SNA; Network Analysis; Data Visualization; Collective Action; Computational Social Science; Digital Sociology; Big Data; Influencers