Measuring Information Propagation in Literary Social Networks

Abstract

We present the task of modeling information propagation in literature, in which we seek to identify pieces of information passing from character A to character B to character C, only given a description of their activity in text. We describe a new pipeline for measuring information propagation in this domain and publish a new dataset for speaker attribution, enabling the evaluation of an important component of this pipeline on a wider range of literary texts than previously studied. Using this pipeline, we analyze the dynamics of information propagation in over 5,000 works of English fiction, finding that information flows through characters that fill structural holes connecting different communities, and that characters who are women are depicted as filling this role much more frequently than characters who are men.

QuoteKG: A Multilingual Knowledge Graph of Quotes

“…For example, there have been analyses of how social movements and global events affect language [14] and how the words used by public persons carry political backgrounds [35]. (iii) Quotes also play an important role when observing information propagation [31] and the bias potentially caused by one-sided selection of quotes [25]. (iv) QuoteKG can also serve as an additional resource for machine translation, given that it contains 38, 931 quotes with mentions in different languages.…”

“…Provenance of quotes is also an indispensable criterion in the Book of Fake Quotes [4]. There are few machine-readable monolingual quote collections 30,31 [10,24,34]. These corpora are typically monolingual and extracted from news.…”

How quantifying the shape of stories predicts their success

“…These tools may be particularly useful for researchers in philosophy, English, and other disciplines who are interested in quantifying aspects of discourse. Researchers in the digital humanities have recently made a number of interesting advances (8,9,13,45,46), and with the right tools, hopefully scholars can begin to quantify features of culture only dreamed about previously.…”

Proceedings of the Third Workshop on Narrative Understanding

“…The pipeline attributes quotes to characters with the deterministic approach of Muzny et al (2017), which uses sieves such as looking for character mentions that are the head words of known speech verbs. We use a standalone re-implementation of this approach by Sims and Bamman (2020) that allows using the pipeline's character coreference as input. Muzny et al (2017)'s approach assigns quotes to character mentions and then to character clusters.…”