activity
20152018
most citedDetermining the Veracity of Rumours on Twitter

62 citations · 85 across the 7 of their papers we have counts for

collaborators

8 papers

eess.SP2018★ 3 cited

Optimising Parameters in Recurrence Quantification Analysis of Smart Energy Systems

Georgios Giasemidis, Danica Vukadinovic Greetham

Recurrence Quantification Analysis (RQA) can help to detect significant events and phase transitions of a dynamical system, but choosing a suitable set of parameters is crucial for…

eess.SP2018

Energy Disaggregation for SMEs using Recurrence Quantification Analysis

Laura Hattam, Danica Vukadinovic Greetham

Energy disaggregation determines the energy consumption of individual appliances from the total demand signal, which is recorded using a single monitoring device. There are varied…

physics.soc-ph2017★ 5 cited

An innovation diffusion model of a local electricity network that is influenced by internal and external factors

Laura Hattam, Danica Vukadinovic Greetham

Haynes et al. (1977) derived a nonlinear differential equation to determine the spread of innovations within a social network across space and time. This model depends upon the imi…

cs.SI2016★ 62 cited

Determining the Veracity of Rumours on Twitter

Georgios Giasemidis, Colin Singleton, Ioannis Agrafiotis +4

While social networks can provide an ideal platform for up-to-date information from individuals across the world, it has also proved to be a place where rumours fester and accident…

physics.soc-ph2016

Green neighbourhoods in low voltage networks: measuring impact of electric vehicles and photovoltaics on load profiles

Laura Hattam, Danica Vukadinovic Greetham

In the near future various types of low-carbon technologies (LCTs) are expected to be widely employed throughout the United Kingdom. However, the effect that these technologies wil…

cs.SI2016

In the mood: the dynamics of collective sentiments on Twitter

Nathaniel Charlton, Colin Singleton, Danica Vukadinović Greetham

We study the relationship between the sentiment levels of Twitter users and the evolving network structure that the users created by @-mentioning each other. We use a large dataset…