License: Creative Commons Attribution 3.0 Unported license (CC-BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.LDK.2019.24
URN: urn:nbn:de:0030-drops-103882
URL: https://drops.dagstuhl.de/opus/volltexte/2019/10388/
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Lin, Yi-Ju ; Hsieh, Shu-Kai

The Secret to Popular Chinese Web Novels: A Corpus-Driven Study

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OASIcs-LDK-2019-24.pdf (0.3 MB)


Abstract

What is the secret to writing popular novels? The issue is an intriguing one among researchers from various fields. The goal of this study is to identify the linguistic features of several popular web novels as well as how the textual features found within and the overall tone interact with the genre and themes of each novel. Apart from writing style, non-textual information may also reveal details behind the success of web novels. Since web fiction has become a major industry with top writers making millions of dollars and their stories adapted into published books, determining essential elements of "publishable" novels is of importance. The present study further examines how non-textual information, namely, the number of hits, shares, favorites, and comments, may contribute to several features of the most popular published and unpublished web novels. Findings reveal that keywords, function words, and lexical diversity of a novel are highly related to its genres and writing style while dialogue proportion shows the narration voice of the story. In addition, relatively shorter sentences are found in these novels. The data also reveal that the number of favorites and comments serve as significant predictors for the number of shares and hits of unpublished web novels, respectively; however, the number of hits and shares of published web novels is more unpredictable.

BibTeX - Entry

@InProceedings{lin_et_al:OASIcs:2019:10388,
  author =	{Yi-Ju Lin and Shu-Kai Hsieh},
  title =	{{The Secret to Popular Chinese Web Novels: A Corpus-Driven Study}},
  booktitle =	{2nd Conference on Language, Data and Knowledge (LDK 2019)},
  pages =	{24:1--24:8},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-105-4},
  ISSN =	{2190-6807},
  year =	{2019},
  volume =	{70},
  editor =	{Maria Eskevich and Gerard de Melo and Christian F{\"a}th and John P. McCrae and Paul Buitelaar and Christian Chiarcos and Bettina Klimek and Milan Dojchinovski},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2019/10388},
  URN =		{urn:nbn:de:0030-drops-103882},
  doi =		{10.4230/OASIcs.LDK.2019.24},
  annote =	{Keywords: Popular Chinese Web Novels, NLP techniques, Sentiment Analysis, Publication of Web novels}
}

Keywords: Popular Chinese Web Novels, NLP techniques, Sentiment Analysis, Publication of Web novels
Collection: 2nd Conference on Language, Data and Knowledge (LDK 2019)
Issue Date: 2019
Date of publication: 16.05.2019


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