*****  To join INSNA, visit  *****

Dear all,

Applications are invited for a 4-year PhD studentship at University of 
Exeter. The position is fully funded including fees and a generous 
stipend of £14.5k per annum. Details are available here:

The closing date for applications is 10th August 2017. Please share 
responsibly with interested individuals and mailing lists.



* * * * * * * * * * * * * * * * * * * * *

      Complex network analysis and machine learning for large-scale

The rise of the web and digital media has seen an explosion in the 
availability of big social data. This PhD project will apply natural 
language processing to large collections of text documents harvested 
from the web (e.g. social media, blogs, online news), in order to 
construct networks of interaction between people and organisations. 
These networks will then be analysed to explore how they change in 
response to external events, with the aim of developing methods to 
predict real-world events before they occur. For example, one 
application of such methods might be to derive a dynamic network of 
relationships between politicians based on online news articles – could 
this network be used to reveal patterns of power and influence, identify 
new political players, or to predict election outcomes?

The student will learn natural language processing and network analysis, 
with aspects of machine learning for identification of influential 
actors. The fully funded 4-year project is co-sponsored by University of 
Exeter and a fast-growing data science company with offices in London 
and Bristol. The studentship will be based in the Computer Science 
department at University of Exeter and will interact with a vibrant 
interdisciplinary data science research community centred on the new 
Data Science Institute. The project offers excellent prospects for 
training and career progression.

Candidates should have a strong background in a quantitative discipline 
(e.g. maths, physics, computer science), with programming skills and 
experience of data analysis.

Interested candidates are encouraged to contact Dr Hywel Williams 
([log in to unmask]) for further information.

Dr Hywel T P Williams
College of Engineering, Mathematics & Physical Sciences
University of Exeter, UK
Room: Laver 722        Phone: +44 1392 723777
Office hours: Tuesday 2-3pm

SOCNET is a service of INSNA, the professional association for social
network researchers ( To unsubscribe, send
an email message to [log in to unmask] containing the line
UNSUBSCRIBE SOCNET in the body of the message.