Cardiff Online Social Media Observatory (COSMOS): Social Media and Data Mining
Our empirical research programme is contextualised in terms of the ‘coming crisis of empirical sociology’ (Savage and Burrows, 2007), which is located in the increasing asymmetry between traditional social scientific methods and the power of transactional data generated through the internet. This has led some commentators to question the extent to which University-based sociology and social science can compete with the data rich resources built into the marketing and data generation strategies of the large multi-national corporations that hold and marshal much of this transactional data. Our projects are being realised through ground breaking, revolutionary, interdisciplinary engineering solutions for next generation social scientific research. This work will assist in the practical facilitation of the proposed Cardiff Online Social Media Observatory (COSMOS) - Funded Projects. With the explosion in social media and the interactive web (Web2.0) the potential for systematic data mining and mixed method analysis in relation to key social science concerns and questions is now possible; COSMOS will provide a means of operationalising a next generation ‘social computational tool kit’. It will also provide a means of augmenting social science research training through the provision of new methodological tools and options for researchers conducting social inquiry in the 21st century.
Funded Projects
Digital Social Research Tools, Tension Indicators and Safer Communities: a demonstration of the Cardiff Online Social Media Observatory (COSMOS)
(Matthew Williams, William Housley, Adam Edwards, Malcolm Williams, Omer Rana and Nick Avis)
Tension indicators or ‘community monitoring systems’ have been developed by police services for the purposes of anticipatory governance to provide early warning of civil unrest and its escalation into major instances of collective violence. Hitherto this community monitoring has been terrestrial, premised on qualitative intelligence from front-line police officers and other ‘sentinels’ such as watch committees, residents and tenants associations, local media and criminal justice data, including records of court proceedings. The development of digital social research tools, particularly for mining social media, can make a major contribution to the indication of tensions in anticipation of major civil unrest. Furthermore, existing research has framed the issue of tension indicators and community safety in ‘panoptic’ terms, reflecting the interests of public authorities in enhancing their surveillance powers for monitoring populations of interest. A major implication of the social media explosion facilitated through Web 2.0 technologies and other digital technology (such as mobile telephones), however, is the rise of the ‘synoptic’ power for the many to watch the few, of citizens to better hold public authorities, such as police forces, to account for their actions. This also provides opportunities for investigating rival accounts of civil unrest, in particular through accessing the sentiments expressed by those directly involved. The potential of the COSMOS to mine and analyse social media also provides resources for non-governmental organisations and the wider citizenry to draw on digital social research in relation to major social-political problems, such as ‘community cohesion’, thereby supporting deliberative democratic processes that can enhance civil liberties.
Automating Sentiment Analysis from Social Data: A Scoping Study
CUROP (Cardiff University)
The growth of the “Social Web” and the corresponding rise in available “emotional text” (through on-line social network platforms such as Facebook and blogging platforms such as BlogSpot) over the past few years has led to an increased interest in sentiment analysis. Research that makes use of such analysis primarily focuses on extraction of text fragments that contain a particular viewpoint – to subsequently support the development of recommendation systems based on data acquired from a large user community. Aggregating the outcome of such an analysis with demographic information enables a better understanding of how a particular community “feels” at a given point in time. This therefore provides a very powerful, automated, research tool for social scientists, to better understand how a community responds to a particular geo-political event. This multi-disciplinary project will make use of the “We Feel Fine” Application Programming Interface (API) from Stanford University and better understand how such a tool could facilitate social sciences research. This project will link in with work on social network analysis (using data mining and graph analysis techniques) within COMSC. It will also build upon a strategic research direction between the two schools, in the establishment of a SOCSI-COMSC research group to investigate how automated social data/media analysis can facilitate social science research.
Postgraduate Projects (COMSC/SOCSI)
Edwin Chappell (COMSC)
David Hannerford (COMSC)