Reading Digital Fiction Project Second-Person Narration Study 2 data

Summary

These data were collected January-March 2016 at Sheffield Hallam University, Sheffield, UK, as part of the Reading Digital Fiction project study on second-person narration. Sixteen 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 and an associated structured interview. Screenshots from a digital fiction were used to create a structured reading set so that each participant viewed the same lexia in the same order during the study. The screenshots are based on The Princess Murderer (2003), by Deena Larsen and geniwate (available at http://www.deenalarsen.net/princess/). 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. For linguistic analysis purposes, please note that the following participants are not native speakers of English: SHUB0101 Gargi. The scales are scanned copies of Likert scales completed by hand by participants.

Keywords: second-person; you; empirical; narratology; cognitive poetics; stylistics; digital fiction; electronic literature
Creators:
Academic units: Faculty of Development and Society (D&S) > Academic Departments > Department of Humanities
Faculty of Development and Society (D&S) > Research Centres > Humanities Research Centre (HRC)
Funders:
Funder NameGrant NumberFunder ID
Arts and Humanities Research CouncilAH/K004174/1http://dx.doi.org/10.13039/501100000267
Copyright Holders: Sheffield Hallam University
Publisher of the data: SHU Research Data Archive (SHURDA)
Publication date: 30 June 2017
Data last accessed: 26 September 2017
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-170009
SHURDA URI: http://shurda.shu.ac.uk/id/eprint/57

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