Wattpad large-scale analysis

The frist large-scale quantiative and qualitative study of the digital social reading platform Wattpad.

– 2019 –

with Simone Rebora (University of Verona, University of Basel) and Gerhard Lauer (University of Basel)

We presented an overview of the possibility offered by a digital social reading platform like Wattpad for the study of reader response. We used various quantitative methods to show the world distribution and language diversity of Wattpad stories (30 million titles) and readers. We also used sentiment analysis to detect the cognitive and emotional response to text paragraphs, and network analysis to understand how interactions between readers can affect reading comprehension and aesthetic appreciation. This study is an example of how “scalable reading” – the combination of close and distant reading – can be successfully employed for the study of literature.

Tools and skills

R, NLTK, CLD2, Google Maps Place Autocomplete API, Syuzhet, Gephi, Flourish, R markdown

Web scraping, language detection, location standardisation, sentiment analysis, network analysis, linear regression

Outputs

Pianzola, Federico, Simone Rebora, and Gerhard Lauer. 2020. “Wattpad as a resource for literary studies. Quantitative and qualitative examples of the importance of digital social reading and readers’ comments in the margins”. PLoS ONE 15.1: e0226708. Data and code: https://osf.io/5gxmn/