Analysing Twitter Discourse on Extreme Events and Climate Change Using Quantitative Research Methods and Applying Theoretical Interpretations

Abstract

This method case study describes how we extracted and analyzed data from Twitter as part of a research project to investigate how users connected climate change to extreme weather events during 2008–2017. The paper describes how the open-source tool, Mecodify, was used as a fundamental part of the method to download data from Twitter and identify key insights through tables, graphs and machine-readable files. The paper goes into detail to describe the steps that were taken from the building the search query to analyzing, aggregating, and visualizing the data used to describe the findings. Although Mecodify facilitated the process significantly, the paper highlights some of the challenges that were confronted during different research stages and how they were overcome. The aim is to provide social media researchers with some useful insights for their own research.

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