Today, my colleagues from the University of Bristol presented our joint paper entitled: Popularity and Geospatial Spread of Trends on Twitter: A Middle Eastern Case Study at ICCCI 2018, the 10th International Conference on Computational Collective Intelligence in Bristol. This builds upon our recent work on obtaining insight from big social datasets; in this case looking at the popularity and spread of trending topics on Twitter through a case study of seven countries in the Middle East.
The abstract of the paper is below; you can read the full paper online as part of LNCS 11055, or access via my institutional repository:
Popularity and Geospatial Spread of Trends on Twitter: A Middle Eastern Case Study
Nabeel Albishry, Tom Crick, Tesleem Fagade and Theo Tryfonas
Thousands of topics trend on Twitter across the world every day, making it increasingly challenging to provide real-time analysis of current issues, topics and themes being discussed across various locations and jurisdictions. There is thus a demand for simple and extensible approaches to provide deeper insight into these trends and how they propagate across locales. This paper represents one of the first studies to look at geospatial spread of trends on Twitter, presenting various techniques to provide increased understanding of how trends on social networks can spread across various regions and nations. It is based on a year-long data collection (N=2,307,163) and analysis between 2016–2017 of seven Middle Eastern countries (Bahrain, Egypt, Kuwait, Lebanon, Qatar, Saudi Arabia, and the United Arab Emirates). Using this year- long dataset, the project investigates the popularity and geospatial spread of trends, focusing on trend information but not processing individual topics, with the findings showing that likelihood of trends spreading to other locales is to a large extent influenced by the place in which it first appeared.
(also see: Publications)
Digital, Data & Policy 