Research Associate

Advert

Research Associate

Cardiff University School of Social Sciences is looking to recruit a Research Associate. The successful candidate will join the research team of the ESRC project Understanding [Offline/Online] Society: Linking Surveys with Twitter Data – a collaborative project between the School of Social Sciences Cardiff University, the Institute for Social and Economic Research (ISER) University of Essex, and NatCen. The postholder will contribute towards a range of work packages involving data collection, generation and analysis of social survey and Twitter data, and pursue excellence in research through contributing to publications and dissemination activities.

We are looking for a candidate with experience of working with Twitter or other social media data data and who is proficient in ‘R’ and/or Python. We anticipate the role involving innovative computational social science approaches, including: co-developing methods for operationalising socially interesting and relevant variables from the wide range of data available through the Twitter API; algorithmic design; categorisation; and data management.

This is a full time post, 35 hours a week, fixed term to the 28th February 2023. 

The post is based in Cardiff University, but will require occasional travel to London and Essex to work in secure data labs (all travel and subsistence costs will be covered by the project).

Salary: £34,304 - £40,927 per annum (Grade 6)

Responsible to Prof Luke Sloan, Principal Investigator

For further enquiries contact Prof Luke Sloan, [email protected] Telephone 029 2087 0262

Date advert posted: Tuesday, 5 October 2021

Closing date: Tuesday, 2 November 2021

This post has previously been advertised to employees of Cardiff University only.  We now invite external applications.

Please be aware that Cardiff University reserves the right to close this vacancy early should sufficient applications be received.

Cardiff University is committed to supporting and promoting equality and diversity and to creating an inclusive working environment. We believe this can be achieved through attracting, developing, and retaining a diverse range of staff from many different backgrounds.  We therefore welcome applicants from all sections of the community regardless of sex, ethnicity, disability, sexual orientation, trans identity, relationship status, religion or belief, caring responsibilities, or age.  In supporting our employees to achieve a balance between their work and their personal lives, we will also consider proposals for flexible working or job share arrangements.

“Cardiff University is a signatory to the San Francisco Declaration on Research Assessment (DORA), which means that in hiring and promotion decisions we will evaluate applicants on the quality of their research, not publication metrics or the identity of the journal in which the research is published. More information is available at: https://www.cardiff.ac.uk/research/our-research-environment/integrity-and-ethics/responsible-research-assessment”

Job Description

Research

• To conduct innovative quantitative research on social survey and Twitter data and contribute to the overall research performance of the School and University by the production of measurable outputs including bidding for funding, publishing in national academic journals and presenting at conferences.
• To attend and or present at conferences/seminars at a local and national level as required.
• To undertake administrative tasks associated with the research project, including the planning and organisation of the project and the implementation of procedures required to ensure accurate and timely reporting.
• To review and synthesise existing research literature within the field.
• To participate in School research activities.
• To build and create networks both internally and externally to the university, to influence decisions,   explore future research requirements, and share research ideas for the benefit of research projects.

Other

• To undergo personal and professional development that is appropriate to and which will enhance performance.
• To participate in School administration and activities to promote the School and its work to the wider University and the outside world.
• Any other duties not included above, but consistent with the role.

Person Specification

Essential Criteria

Postgraduate degree at PhD level (or nearing completion/submission) in a related subject area or equivalent or relevant industrial experience.

An established expertise and proven portfolio of research and/or relevant industrial experience within the following research fields:

• Analysis of Twitter data OR analysis of other social media data using methods/techniques that can be applied to Twitter data.
• Quantitative data analysis

Experience of ‘R’ and/or Python.

Knowledge of current status of research in specialist field.

Proven ability to present and communicate research (can be evidenced through a range of outputs including: publications; conferences; submitted work under review; or other research outputs).

Knowledge and understanding of competitive research funding to be able to develop applications to funding bodies.

Proven ability in effective and persuasive communication of complex analyses.

Ability to lead analysis packages.

Proven ability to demonstrate creativity, innovation and team-working within work.

Proven ability to work without close supervision.

Desirable Criteria

• Experience of working with Twitter data.
• Experience of working with quantitative survey data
• Experience of accessing APIs.
• Knowledge of machine learning approaches.
• Experience of working with linked data.

NOTE

The Person Specification is split into 2 sections: essential and desirable.  Please demonstrate clearly how you meet all of the essential criteria.  Where possible you should give examples of how, when and where you have used your experience, knowledge, specific skills and abilities to match those required for this particular job role.

Please ensure that you communicate this fully by creating a supporting statement document, listing all of the criteria and commenting against each one as to how you meet them.  This will need to be completed before you begin making your application on line as you will be required to upload it. 

When attaching the supporting statement to your application profile, please ensure that you put your name and the  vacancy reference number, e.g. Supporting Statement for XXXXBR.’

The desirable section contains a list of skills, qualifications and experience that it would be beneficial for the jobholder to have.

All short-listing decisions will be based initially on essential criteria, with desirable being used to further select or deselect candidates as appropriate. 

We interview those candidates who are the closest match to the identified criteria.

Additional Information

Understanding [Offline/Online] Society Project Summary
Understanding behaviours, attitudes and identities in online space is a key challenge for 21st Century Social Science. The opportunities provided by social media platforms such as Twitter are significant, with between 300 and 500 million tweets generated a day representing interactions, networks, opinions and reactions at a highly granular temporal (and sometimes spatial) level. On average 4,500 tweets are authored every second and this velocity of data offers us a real-time insight into the social world. However, the fly in the ointment for researchers is that we have a limited understanding of who (or what in the case of 'bots') is present in the online space and to what extent the online representation of social actors can be taken to represent the social world. The fundamental concerns of what can be known and how we can know it need to be addressed before social science can embrace, albeit with a healthy dose of caution, Twitter as a source of knowledge on the social world.
In light of this, this project sets out to establish what insights Twitter can offer us into social phenomenon through the linkage of the content and metadata of tweets with survey data from three major UK surveys - British Social Attitudes 2015, Understanding Society Innovation Panel 2017 and the NatCen Panel. In essence, this project is an exercise in method, calibration and verification, through taking what we know about a respondent and exploring to what extent a given known characteristic may manifest (or not) in the online setting, and vice versa. There is clear methodological value in this - gaining consent to link additional sources of data to survey responses is increasingly used to enhance the value of survey data, validate survey measures, and address issues with nonresponse. However, most previous research on consent has focused on administrative records, and understanding consent relating to other new forms of data is needed.
With novel methods there are limitations to working theoretically - unpredicted limitations may become apparent, and the value of the design not be evident without a real research context. The project will therefore undertake further data collection as part of substantive case study concerning attitudes and behaviours toward ethnic minorities that will aim to uncover 'hidden' challenges and demonstrate how this methodology can be employed, as well as contributing to the substantive literature. To maximise the value of the research for the wider academic community, this work will in turn inform a work package focusing solely on archiving, sharing and re-use of the linked dataset and/or a derivative of it. Whilst Twitter is only one of many social media platforms, it is the most open and accessible and provides a proving ground on which issues of consent, linkage, archiving and sharing can be tested and evaluated. We anticipate that many of the lessons and protocols developed as part of this research will be operationally applicable to other social media platforms.
In summary, the research project seeks to answer the following research questions:

• How can Twitter data be used to enhance survey data?
• How can survey data be used to evaluate existing demographic proxy measures and develop new ones?
• How can we encourage informed consent to social media data linkage?
• Demonstrator Study: How can linked data (direct reported and observed indirect) help us to understand public attitudes towards minority ethnic groups?
• How can social media data be collected, linked to survey data, analysed, archived, and shared in a legal and ethical manner that maintains utility?

 

Further details of the School's activities can be found on our home page:

http://www.cardiff.ac.uk/social-sciences

Job Category

Academic - Research