3 - Content Analysis of Social Media

Summary

This chapter outlines how social media data, such as Facebook and Twitter, can be used to study language attitudes. This comparatively recent method in language attitudes research benefits from the immediate accessibility of large amounts of data from a wide range of people that can be collected quickly and with minimal effort – a point in common with attitude studies using print data. At the same time, this method collects people’s spontaneous thoughts, that is unprompted attitudinal data – a characteristic usually attributed to methods drawing on speech data. The study of language attitudes in social media data can, however, yield wholly different insights from writing and speech data. The chapter discusses the advantages and pitfalls of different types of content analysis as well as the general limitations of the method. The chapter presents an overview of software programmes to collect social media data, as well as geo-tagging, and addresses data analysis as well as the general usefulness of the method (e.g. its applicability around the world or the potential for diachronic attitudinal change). The case study in this chapter uses examples from Twitter, focusing on attitudes towards the Welsh accent in English.