Reading Digital Fiction Project Second-Person Narration Study 1 Data

Summary

These data were collected in November 2014 at Sheffield Hallam University, Sheffield, UK, as part of the Reading Digital Fiction project study on second-person narration. Three people participated in the study. The significant data collection consisted of an audio-recorded structured reading of a piece of digital fiction along with a series of scales designed as a questionnaire. Participants read The Princess Murderer (2003), by Deena Larsen and geniwate (available at http://www.deenalarsen.net/princess/). Screenshots of The Princess Murderer were then used to create a structured reading set so that each participant viewed the same lexias in the same order during the study. They were originally shown as a slideshow with sound effects to recreate the reading experience of the live web version. The transcripts are anonymized transcriptions of the structured reading session for each participant. The scales are a record of the participants' responses to the question "To whom does 'you' refer in this screen?" for each screenshot in the stimulus set. Answers range from "you = a fictional character" to "you = me the reader"

Keywords: digital fiction, electronic literature, empirical, cognitive poetics, stylistics, cognitive narratology,
Creators:
Academic units: Faculty of Social Sciences and Humanities (SSH) > Academic Departments > Department of Humanities
Faculty of Social Sciences and Humanities (SSH) > Research Centres > Humanities Research Centre (HRC)
Funders:
Funder NameGrant NumberFunder ID
Arts and Humanities Research CouncilAH/K004147/1http://dx.doi.org/10.13039/501100000267
Copyright Holders: Sheffield Hallam University
Publisher of the data: SHU Research Data Archive (SHURDA)
Publication date: 5 September 2017
Data last accessed: 1 May 2018
Embargo expiry date: 1 July 2022
Reason(s) for restriction and conditions for access: The embargo has been set 5 years after the end of the project to allow the creators to publish work analyzing the data before releasing the data to the public.
DOI: http://doi.org/10.17032/shu-170006
SHURDA URI: https://shurda.shu.ac.uk/id/eprint/56

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