Towards a discourse theory of abstracts and abstracting - Gibson, Timothy Robin (1993)
Abstract 1 This Ph.D. thesis investigates the extent to which certain linguistic variables affect the perceived success of an abstract. In his opening chapter, the author situates the work as a contribution to discourse theory and formulates a set of seven basic research questions the study seeks to answer. Chapter 2 considers the most satisfactory design for the research. Part Two provides a survey of the relevant source material, consisting of reviews of: the Linguistics and Psychology literature; Artificial Intelligence computational summarising systems; and standards and guidelines taken from Information and Library Science. Part Three discusses the data collection: first, the collection of naturally occurring abstracts from a teaching establishment; second, the collection of judgements elicited by means of a set of questionnaires. The remainder of the thesis constitutes an attempt to reconcile these two types of data, words and opinions. The author draws a distinction between the qualitative and quantitative opinions of the judges (which he refers to as 'external measures') and the linguistic features present in the different abstracts ('internal measures') which determine these subjective opinions. Part Four discusses the data analysis, which draws on grammatical techniques from Systemic-Functional theory. In Part Four, hypotheses are investigated which relate the success of the different abstracts as perceived by the judges to the linguistic features present in the texts. Five different types of analysis are piloted using a small number of texts; three of these analyses are taken further and applied to all the abstracts. Part Five consists of two chapters. The first details the conclusions to be drawn from the study and explicitly answers the seven basic research questions introduced in Chapter 1. The second provides some suggestions for further research, chiefly concerning the collection of further external and internal measures. Finally, techniques from multivariate statistics are briefly sketched as a means of reconciling the two types of measure in the future.