| Zusammenfassung |
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. We therefore propose 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: RQ1) How can Twitter data be used to enhance survey data? RQ2) How can survey data be used to evaluate existing demographic proxy measures and develop new ones? RQ3) How can we encourage informed consent to social media data linkage? RQ4) Demonstrator Study: How can linked data (direct reported and observed indirect) help us to understand public attitudes towards minority ethnic groups? RQ5) How can social media data be collected, linked to survey data, analysed, archived, and shared in a legal and ethical manner that maintains utility? |
