Visualizing and Quantifying Impact and Effect in Twitter Narrative using Geometric Data Analysis
Fionn Murtagh, Monica Pianosi, Richard Bull

TL;DR
This paper introduces a geometric data analysis approach to visualize and quantify the impact and effect of Twitter narratives, focusing on significant events and environmental campaigns to measure behavioral change and social media influence.
Contribution
It presents an innovative geometric multivariate analysis method for visualizing and quantifying Twitter narratives and behavioral changes in social media campaigns.
Findings
Effective visualization of Twitter narratives.
Quantification of behavioral change in campaigns.
Assessment of statistical significance in social media data.
Abstract
We use geometric multivariate data analysis which has been termed a methodology for both the visualization and verbalization of data. The general objectives are data mining and knowledge discovery. In the first case study, we use the narrative surrounding very highly profiled tweets, and thus a Twitter event of significance and importance. In the second case study, we use eight carefully planned Twitter campaigns relating to environmental issues. The aim of these campaigns was to increase environmental awareness and behaviour. Unlike current marketing, political and other communication campaigns using Twitter, we develop an innovative approach to measuring bevavioural change. We show also how we can assess statistical significance of social media behaviour.
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Taxonomy
TopicsData-Driven Disease Surveillance · Complex Network Analysis Techniques · Data Visualization and Analytics
