Year of entry: 2018
Course unit details:
Understanding Social Media
|Unit level||Level 1|
|Teaching period(s)||Semester 2|
|Offered by||Social Statistics|
|Available as a free choice unit?||Yes|
1. Twitter, Facebook, You Tube - An Introduction to social media data and types
2. How to analyse social media. Basic statistical skills for data analysis (counts, %s, bar charts, histograms, scatterplots)
3. Practical session (1) - Excel taster training and tasks (Lab) (%s, means)
4. Big Bad Data? What can you claim? Sampling and inference for social media data
5. Analysing social media including social network analysis
6. Measurement debates. Data quality issues and social media data eg: coverage, performance and fake accounts and ethics
7. Practical session (2) Designing social research using social media (Group work)
8. Practical session (3) Data collection (Group work)
9. Practical session (4) Data analysis (Lab)
10. More data for social research? Linking social media data with other data sources for understanding society eg surveys, ESDS, administrative data. Report writing skills, course overview and assignment
Tutorials (10 x 1hr tutorials).
The tutorials will be linked to each lecture and based around embedding practical skill learning using tasks and group work.
The tutorials will form part of the formative assessment for the course where students present ideas and draft outlines for discussion and feedback. In addition, students will be given the opportunity to do a practice essay and will get feedback on their writing. The essay will be linked to Lectures 6 and 7. Feedback will be given during tutors' office hours in the last week of the semester.
The unit aims to:
(i). To develop the students understanding of social research methods using social media data such as Facebook, Twitter and Blogs.
(ii). To inform students about research design and ethical issues concerning the use of social media data in research.
(iii). To introduce students to the analytical skills used in collecting and analysing social media data.
(iv). To provide students with a basic training in the use of software for the handling and the analysis of social media data.
(v). To develop students understanding and critical skills in such areas as sampling, sample bias and statistical inference in social research.
(vi). To enable students to develop and write a dissertation research proposal based around using such data should they choose to.
Student should/will (please delete as appropriate) be able to
Knowledge and Understanding: A critical understanding of the evidence and debates regarding the use of social media data for understanding society.
Intellectual skills: An understanding of good practices in research design, evaluating evidence and data and assessing robustness. Develop critical skills in evaluating data and methods through lectures, lab sessions, group work and independent reading.
Practical skills: An understanding of social statistics and practical experience of data analysis including using software for social research. Develop skills in evaluating evidence and scientific claims.
Transferable skills and personal qualities: Critical data analysis and evaluation skills. Social statistics and data analysis skills are in high demand in the labour market. The group work will also aid the student in developing their communication and team working skills.
Teaching and learning methods
The module will involve: lectures, group work, lab classes as well as data gathering and analysis tasks.
Extensive use will be made of relevant on-line resources including: data archives, analysis and data visualisation tools and literature resources as well as video and radio recordings. Moreover, the data itself will be accessed on-line.
Blackboard resources will be used to enable students to access software for the collection and analysis of social media data. Other possible options will include asking students to write their own Blogs during the course. We may also use Blackboard discussions as a form of measuring student participation.
The lecture component will provide a theoretical and methodological framework for learning about how to use social media data. Practical sessions will give students hands on experience in all aspects of data analysis and interpretation and using appropriate software for data manipulation. Such skills are highly transferable.
The emphasis on the use of real data to answer real questions is designed to engage students and enable students to consider using such approaches as part of their own dissertation research.
Elliot, M. and Purdam, K. (forthcoming) 'Exploiting New sources of Data' in Halfpenny, P. and Proctor, R. (eds) Innovations in Digital Social Research Methods. Sage
González-Bailón, S. Wang, N., Rivero, A.Borge-Holthoefer, J. and Moreno, Y. (2013) Assessing the Bias in Communication Networks Sampled from Twitter. See Available at SSRN: http://ssrn.com/abstract=2185134 or http://dx.doi.org/10.2139/ssrn.2185134
Halfpenny, P. and Proctor, R. (forthcoming) (eds) Innovations in Digital Social Research Methods. Sage
Mason, J. and Dale, A. (2011) Understanding Social Research, Sage.
Murthy, D. (2012) Towards a Sociological Understanding of Social Media: Theorizing Twitter. Sociology. December 2012 vol. 46 no. 6 1059-1073
Purdam. K and Elliot, M. (forthcoming) 'The Changing Social Data Landscape' in Halfpenny, P.
and Proctor, R. (eds) Innovations in Digital Social Research Methods. Sage, The Sage Encyclopaedia of Social Science Research Methods. Sage.
Thelwall, M. and Viz, F. (2013) Researching Social Media. Sage
Vis, F., (2012) 'Twitter as a reporting tool for breaking news', Digital Journalism 1(1).
Vis, F., (2012), 'Reading the Riots on Twitter: who tweeted the riots?', Researching Social Media Blog, 24 January, http://researchingsocialmedia.org/2012/01/24/reading-the- riots-on-twitter-who-tweeted-the-riots/
Research Methods Centre http://www.ncrm.ac.uk/
Oxford Internet Institute www.oii.ox.ac.uk/
Oxford e Research Centre www.oerc.ox.ac.uk/
|Scheduled activity hours|
|Assessment written exam||2|
|Practical classes & workshops||10|
|Independent study hours|
|Kingsley Purdam||Unit coordinator|