***** To join INSNA, visit http://www.insna.org ***** Dear colleagues, Applications are invited for a fully funded 3.5-year PhD studentship at University of Exeter. The funding includes fees and a generous stipend of £14.8k per annum. Details are available here: https://urldefense.proofpoint.com/v2/url?u=http-3A__www.exeter.ac.uk_studying_funding_award_-3Fid-3D3037&d=DwIDaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=DBXiDBDzT7NLLFvt3BSMzXzlea_naq6IuMFoPcU8bh0&s=TJmODJLCKDSmlj8bn8b7Jv15tsDrSsAcp2sm0W_HBWY&e= The closing date for applications is 8th March 2018. Please share responsibly with interested individuals and mailing lists. Thanks, Hywel * * * * * * * * * * * * * * * * * * * * * Online (mis)information and climate change: Using network analysis and machine learning to understand environmental debate Despite widespread scientific consensus, climate change remains a controversial and politicised topic. On one side, environmentalists push for greater action to prevent and mitigate the effects of climate change. On the other, a well-funded climate denial lobby promote doubt and confuse public opinion. This debate is actively pursued in online news and social media, where denialist blogs and commentators attempt to discredit the scientific viewpoint with a steady stream of contrarian articles and social media posts. Since climate change is a complex subject, there is significant potential for misinformation. So-called “fake news” has been much discussed in the context of politics, while, automated “bots” and managed social media accounts are known to affect online debates. This PhD project will apply advanced computational methods to understand the online media ecosystem around climate change. In particular, it will seek to characterise the role of misinformation in online climate debates, looking in particular at social media accounts, bots and fake news sites linked to the climate denial viewpoint. Within this topic area there is considerable scope for the student to shape the project towards their own interests. The methods utilised will depend on the exact research question chosen, but are likely to combine complex network analysis, machine learning and text mining. The project will suit a motivated student with a strong quantitative background (e.g. computer science, mathematics, physics) and an interest in how the Web is changing our society. The student will be part of the newly formed Institute for Data Science & Artificial Intelligence at University of Exeter, which has recently joined the Alan Turing Institute. The project offers exceptional opportunities for future employment in academic or commercial data science. 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 (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.