To introduce students to key methodological concerns of working with Twitter data. To guide students in gaining first-hand experience collecting, visualising and exploring Twitter data. To enable students to see how to make sense of Twitter data for social scientific purposes. To point towards a more general role for social media and digital data in social science research.

(LO1) Understand the methodological continuities and discontinuities between social media analytics and 'traditional' social science methods.

(LO2) Be able to extract and visualise Twitter data using research-oriented software.

(LO3) Be able to reflect on the methodological link between the technical aspects of Twitter analyticsresearch work and the social scientific findings that result.

(LO4) Appreciate the potential for social media and digital data analytics to provide insight on social scientific research topics.

(S1) Digital researching; participating in emerging academic practices that both leverage and concentrate topically on digital social interaction

(S2) The application of software and information technology in developing, addressing and presenting scholarly research

(S3) Research management skills, including elements such as developing and piloting a research strategy, engaging in considerations of ethics in regard to (digital) research data, undertaking exploratory empirical research involving data collection, visualising and making sense of data, and presenting research in written format

(S4) Problem solving and creative critical thinking; making sociogical sense of data which is not produced (primarily) for the purposes of social scientific research

(S5) Reflexive thinking around the research process; self-analysis of the journey from software tools and "raw" data to social scientific explanations of it

The teaching and learning strategy of the module is based around providing students with the knowledge and skills necessary to engage with Twitter data, practically and methodologically, from the social scientific perspective. Having received guidance from the module leader in the workshop sessions, students will be able to explore these ideas for themselves through an independently-conducted small-scall research project. Teaching will take place over two days. Day 1 will comprise a one hour lecture, a one hour tutorial, and a two hour lab practical session. Day 2 will comprise a four hour lab practical session.

Teaching Method 1 - Lecture
Description: Students will receive a (one hour) lecture to provide students with knowledge of a range of methodological issues pertinent to digital data and social media analytics.
Attendance Recorded: Yes

Teaching Method 2 - Tutorial
Description: Students will be given a guided walkthrough of a Twitter analytics software package to give students experience with collecting and visualising data, where the instructor will demonstrate the package in action and students will follow alongside.
Attendance Recorded: Yes

Teaching Method 3 - laboratory Work
Description: In a "computer lab" setup, students will be given opportunity to undertake their own investigations into Twitter analytics using the demonstrated software package, applying their knowledge and skills to a research topic of their choice. An instructor will be on-hand to address issues as they arise.
Attendance Recorded: Yes