NSMNSS Network Event Cardiff Online Social Media ObServatory (COSMOS)  Background and Implications for Social Research    ...
Background and Implications of COSMOS  •   ‘Coming crisis of empirical sociology’ (Savage and Burrows, 2007)  •   Social m...
Methodological Aim and Objectives of COSMOS  Aim:  • To evaluate the technical, methodological, and ethical challenges    ...
Aim and Objectives of COSMOS DemonstratorProject: Monitoring Social Cohesion and Tension  Aim:  • To analyse social media ...
Cardiff Online Social Media ObServatoryConsi der pr ocessshar i ng – si m l ar t o                i
Implications of COSMOS for Social Research  1.   Is it a surrogate for conventional, terrestrial, social research methods?...
Implications of COSMOS for Social Research  (1.)       Is it a surrogate for conventional, terrestrial, social research   ...
Implications of COSMOS for Social Research  (2.)   Is it an augmentation of conventional, terrestrial, social research met...
Implications of COSMOS for Social Research   (3.) Is it a re-orientation of social research methods? E.g. the emergence of...
Ethical Considerations      (4.) Ethics and the politics of data      –     Panoptic surveillance      –     Feedback cons...
Sentiment and Signature Science ?
Sentiment and Signature Science ?
Mashing Social Media and NeighbourhoodCrime Data?
SOCSI/COMSC Research Network  School of Social Sciences & School of    Computer Science and Informatics            Cardiff...
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COSMOS

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COSMOS

  1. 1. NSMNSS Network Event Cardiff Online Social Media ObServatory (COSMOS) Background and Implications for Social Research Methods William Housley, Matthew Williams, Adam Edwards, Pete Burnap, Malcolm Williams, Luke Sloan, Omer Rana & Nic Avis SOCSI/COMSC Research Network School of Social Sciences & School of Computer Science and Informatics Cardiff University
  2. 2. Background and Implications of COSMOS • ‘Coming crisis of empirical sociology’ (Savage and Burrows, 2007) • Social media and the interactive web (Web2.0) provide potential for systematic data mining and analysis of naturally occurring data thereby rendering new populations visible and thinkable • Development of a ‘social science digital tool kit’
  3. 3. Methodological Aim and Objectives of COSMOS Aim: • To evaluate the technical, methodological, and ethical challenges presented by social media data in the context of social sciences. Objectives: • To demonstrate how APIs can be utilised within the COSMOS platform to crawl, harvest, index and visualise qualitative and quantitative social media data; • To interrogate social media data using social science criteria for quality and robustness; • To examine the ethical and legal issues with harvesting data from social media sources.
  4. 4. Aim and Objectives of COSMOS DemonstratorProject: Monitoring Social Cohesion and Tension Aim: • To analyse social media data for the purposes of monitoring social cohesion and tension before, during and after major events (e.g. urban riots; industrial action; political protests/elections; major sporting events etc.). Demonstrator Objectives: • To examine measures of connectivity in the analysis of social media data in relation to indices of social cohesion and tension; • To examine sentiment about social cohesion and tension in social media data and their correlation with events; • To examine the feasibility of ‘mashing’ official curated data sources with social media data.
  5. 5. Cardiff Online Social Media ObServatoryConsi der pr ocessshar i ng – si m l ar t o i
  6. 6. Implications of COSMOS for Social Research 1. Is it a surrogate for conventional, terrestrial, social research methods? E.g. as an alternative to household surveys, ethnographies, focus groups, interviews, content analysis 2. Is it an augmentation of conventional, terrestrial, social research methods? E.g. a platform for distributed, digital, ethnography; ‘mashing’ social media communications with curated datasets (such as neighbourhood crime statistics) 3. Is it a re-orientation of social research methods? E.g. the emergence of the networked researcher integrating multiple digital data strands in different locations; recognition of new populations (‘object-oriented sociality’, Knorr-Cetina, Latour) 4. Ethical implications? E.g. surveillance and public sociology (panoptic and synoptic power)
  7. 7. Implications of COSMOS for Social Research (1.) Is it a surrogate for conventional, terrestrial, social research methods? E.g. as an alternative to household surveys, ethnographies, focus groups, interviews, content analysis – Low fidelity – relatively impoverished, for example demographic data – Inert – passive data, not elicited though face to face interaction – Noise – problem of identifying relevant information when treating social media traffic as data – Is the analysis of social media data statistically robust ? What does inference mean in relation to research questions and sample in the context of social media traffic
  8. 8. Implications of COSMOS for Social Research (2.) Is it an augmentation of conventional, terrestrial, social research methods? E.g. a platform for distributed, digital, ethnography, networked team coding of large data sets, crowd sourcing ‘Mashing’ social media communications with curated datasets (such as neighbourhood crime statistics) Web 2.0 can provide a means of ‘reaching hard to reach groups’ – e.g. social media can augment poor survey responses and reach marginalised communities
  9. 9. Implications of COSMOS for Social Research (3.) Is it a re-orientation of social research methods? E.g. the emergence of the networked researcher integrating multiple digital data strands in different locations; recognition of new populations (‘object-oriented sociality’, Knorr-Cetina, Latour) – New ways of understanding agency and social organisation using social media as a case example (e.g. Marc Hughes, NodeXL) – investigation and visualisation of classic questions in real time. Possibility of identifying new social categories, connections and relations – Modelling and visualization – re-orientates interpretation of data – Naturally occurring mediated data – ‘pulse of the world’ – Real/Useful Time Analysis – Archiving – Event Analysis – Anomaly Detection - from punctuated to locomotive data collection and analysis – Convergence between computing and social science – networked researcher – New digital tools – platforms and observatories – signature science or predictive science – collaborative and open source
  10. 10. Ethical Considerations (4.) Ethics and the politics of data – Panoptic surveillance – Feedback consequences, auto-poesis and self-referentiality, closed systems – (Double hermeneutic) BUT Synoptic surveillance and public sociology; need to develop digital tools and social analysis within contemporary contours of emerging digital society for public good not private gain; open source.
  11. 11. Sentiment and Signature Science ?
  12. 12. Sentiment and Signature Science ?
  13. 13. Mashing Social Media and NeighbourhoodCrime Data?
  14. 14. SOCSI/COMSC Research Network School of Social Sciences & School of Computer Science and Informatics Cardiff Universityhttp://www.cardiff.ac.uk/socsi/researc h/researchgroups/comsc- socsi/index.html

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