Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/34889
Appears in Collections:Management, Work and Organisation Book Chapters and Sections
Title: NodeXL: Twitter Social Media Network Insights in Just a Few Clicks
Author(s): Ahmed, Wasim
Meier, Harald
Smith, Marc
Contact Email: wasim.ahmed@stir.ac.uk
Editor(s): Quan-Haase, Anabel
Sloan, Luke
Sponsor: Newcastle University
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.) <i>The SAGE Handbook of Social Media Research Methods</i>. 2nd ed. London: SAGE, pp. 487-502. https://uk.sagepub.com/en-gb/eur/the-sage-handbook-of-social-media-research-methods/book272098
Keywords: Social Media
Social Networks
SNA
Network Analysis
Data Visualization
Collective Action
Computational Social Science
Digital Sociology
Big Data
Influencers
Issue Date: 2022
Date Deposited: 7-Oct-2022
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.
Rights: This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. Publisher policy allows this work to be made available in this repository. Published in Quan-Haase A & Sloan L (eds.) The SAGE Handbook of Social Media Research Methods, 2nd ed. London: SAGE, pp. 487-502. Available at: https://uk.sagepub.com/en-gb/eur/the-sage-handbook-of-social-media-research-methods/book272098
URL: https://uk.sagepub.com/en-gb/eur/the-sage-handbook-of-social-media-research-methods/book272098

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