Investigating peacebuilding approaches via NVivo
Xiaoying Wang
Background
Analysis of social media and ubiquitous data plays a critical role in humanities and social sciences these days with the prevalence of social media. Dr Arif Saba from Alfred Deakin Institute for Citizenship and Globalisation in the School of Humanities and Social Sciences, Deakin University, has such a research project which utilises social media data from X (Twitter) as its primary data source. The project seeks to analyse the contents of specified X accounts engaged in digital or public diplomacy through a detailed analysis of the negotiation between the Taliban and the US that led to the 2020 Doha Agreement. The project aims to identify and analyse various discourses put forth by the negotiating parties during the peace process.
Challenge
It is challenging how to best utilise advanced digital technology such as NVivo to analyse X data to find out whether and to what extent the dataset includes key themes or pre-identified keywords under specified research questions and in what context they have been used, particularly for researchers whose expertise is in human and social science instead of advanced digital technology. It could be time-consuming and involve tremendous labour work to retrieve the relative information from thousands of X posts.
Solution
Dr Arif Saba was suggested to contact the digital research team at Deakin and found Dr Xiaoying Wang, a local Digital Research Analyst (DRA) placed by Intersect in the digital research team at Deakin University. Xiaoying suggested install and utilise the NCapture module (a free web-browser extension for Chrome that enables web content to be gathered and imported into NVivo) to collect posts from identified sources on X. She then presented and introduced NVivo functionalities such as identifying main themes by word frequency and retrieving keywords or themes through search queries so that related fragments of text are located and categorised to derive meaningful insights.
To collect and analyse the X data, Dr Saba utilized the NVivo software, which facilitated the downloading of tweets from the two X accounts – covering the period from November 2018 to October 2021. A total of n=677 and n=490 tweets from the selected X accounts were collected for analysis.
Outcome
The NVivo software played a crucial role in the analysis of the collected tweets. The utilisation of NCapture enables the automation of data collection from X in a quick manner. NVivo also facilitated the identification of key themes, and the contextual information surrounding the identified themes. Hence, meaningful insights buried in huge data can be derived efficiently, and significant time and labour can be saved at the same time. This case study demonstrates the efficiency that NVivo enhances in humanities and social sciences. Dr. Wang will continue working together with Dr Saba on the visualisation of changes in key themes over time using Excel bar charts.
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