dbtropes_feature — Artistic works and their tropes (2016)
- Description
A bipartite network of artistic works (films, series, novels, games, etc.) and the tropes (writing devices and conventions) they use, from the TV Tropes wiki (tvtropes.org), as converted into RDF by the DBTropes project of M. Kiesel (DFKI). DBTropes parsed the pages of TV Tropes, and each example of a trope listed on the page of a work (or each work listed on the page of a trope) became a "feature instance" linking the work to the trope. Nodes are works and tropes, and an edge connects a work to a trope exemplified in it, with one edge per feature instance, so a pair can be connected by several edges when the example appears more than once (e.g. on both pages). This is the monthly DBTropes snapshot of 1 July 2016 (with pages fetched from TV Tropes at various earlier dates). The "item name" pseudo-features that DBTropes attaches to every work are not included.
The network has the following properties:
- (Node)
is_trope: whether the node is a trope (otherwise it is a work). - (Node)
name: the page title (for works, prefixed by the TV Tropes namespace, e.g. "Film: The Matrix"; empty for the 3,053 pages without a title in the dump). - (Node)
page: the TV Tropes page ("Namespace/PageName"). - (Edge)
applicability: a value given by DBTropes to each example: 1 for most examples, -1 for some examples (at least those marked as averted on TV Tropes), or -0.3 (whose meaning is not documented).
- (Node)
- Tags
- Informational Relatedness Unweighted Multigraph Metadata
- Added
- 2020-08-11
- Citation
-
- M. Kiesel, G. A. Grimnes, "DBTropes - a linked data wrapper approach incorporating community feedback." EKAW 2010 Demo & Poster Abstracts, International Conference on Knowledge Engineering and Knowledge Management (2010) web.archive.org
- Upstream URL OK
- https://web.archive.org/web/20161001182354/http://skipforward.opendfki.de/wiki/DBTropes
- Networks
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Tip: hover over a column header for a description.
Column legend
- $\left<k\right>$
- Mean degree
- $\sigma_k$
- Standard deviation of the degrees
- $\lambda_h$
- Largest eigenvalue of the Hashimoto (non-backtracking) matrix
- $\tau$
- Random walk mixing time
- $r$
- Degree assortativity
- $c$
- Global clustering coefficient
- $\oslash$
- (Pseudo-) diameter
- $S$
- Relative size of the largest component
- NPs
- Node properties
- EPs
- Edge properties
- Ridiculograms*
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