ADOVA: Anomaly Detection in Online and Virtual spAces
Emele, CD., Spakov, V., Pang, W., Bone, JD. & Coghill, GM. (2015). 'ADOVA: Anomaly Detection in Online and Virtual spAces'. pp. 38-41.
Online and virtual spaces comprise a myriad of ad-hoc networks
and online communities. Such communities are composed
of smart devices, agents, systems and people who seek
to interact in one way or another. We argue that the task
of detecting anomalies in such settings is non-trivial. The
complexity is further compounded since there is no clear cut
definition/specification of what normal behaviour is, and
how far out an outlier should be before it is detected as
an anomaly. This is often the case with online and virtual
spaces as there is little or no regulation of the interactions
between the various players in online communities. Hence,
detecting anomalous behaviour in such settings poses a huge
In this paper, we investigate how evolutionary
clustering could be exploited to support decision makers,
designers and data scientists in the autonomous detection of
anomalies in online and virtual spaces. We present preliminary
ideas in tackling this issue using a freeform online social
media community (Twitter) and explore how emerging patterns
and trends could help identify clusters of players (or
normal behaviour) and, conversely, anomalies.
The social sciences and the web: From ‘Lurking’ to interdisciplinary ‘Big Data’ research
Bone, JD, Emele, CD, Abdul, AO, Coghill, GM & Pang, W 2016, 'The social sciences and the web: From ‘Lurking’ to interdisciplinary ‘Big Data’ research ' Methodological Innovations, vol. 9, pp. 1-14.
‘Big data’ is an area of growing research interest within sociology and numerous other disciplines. The rapid development of social media platforms and other web resources offer a vast and readily accessible repository of data associated with participants’ activities, attitudes and personal information on a scale and depth that would have previously been difficult to access without substantial resources. However, as well as offering opportunities to social researchers, this medium also presents a significant range of challenges. Ethical issues are one much debated area where social scientists are having to reassess their longstanding modus operandi, given questions regarding access to personal data and ambiguities regarding its status and legitimate usage. In addition, the scale of data accessible and the possible skills required to collect and analyse it is also a critical issue, and is an area that, arguably, has received lesser attention. In its infancy, online research could be fairly rudimentary, employing simple techniques to gather information from weblogs, forums and so on. However, the possibilities now presented by large-scale social media platforms has created the potential for more sophisticated research that often requires specialist technical expertise, involving collaborative work by computer and social scientists working together. This is a scenario that raises its own concerns, not least in terms of forging areas of shared understanding between these disparate disciplines sufficient to facilitate such projects. This article addresses such issues, providing a reflection on the theoretical and practical experience of engaging in online research, from fledgling involvement to embarking on a current collaborative interdisciplinary project. The aim is to provide some insights to other social scientists with respect to some of the potential advantages and pitfalls of web research, while a flavour of the current project, exploring Scottish Referendum and UK General Election related Twitter data, is also presented.