Elsevier

Social Networks

Volume 63, October 2020, Pages 21-37
Social Networks

Measuring centrality in film narratives using dynamic character interaction networks

https://doi.org/10.1016/j.socnet.2020.03.003Get rights and content

Highlights

  • Questions of time, order and sequence are critical in analysis of narrative.

  • We present a dynamic measure of the relative importance of characters in fictional texts.

  • Illustrated through analysis of gender in 2015 film Star Wars: The Force Awakens.

  • Narrative text represented as dynamic network based on character interaction.

  • Measure helps illuminate narrative dynamics which static measures cannot capture.

Abstract

The tools of social network analysis offer a promising framework for studying fictional texts and the relational activity of the characters therein. The goal of this paper is to offer both a conceptual refinement of the project of measuring the centrality of characters within narratives using network tools, as well as the proposal of a novel measure with which to do so. Conceptually, we argue that as questions of time, order and sequence are central in narratives, measures of characters’ narrative importance should be based on dynamic network representations which respect the time-ordering of narrative events. We suggest a directed dynamic measure of relative character importance based on character interactions and illustrate it through an examination of gender in the 2015 film Star Wars: The Force Awakens. We find that the measure helps illuminate important narrative dynamics which cannot be captured by static measures, and presents a platform on which future character network research can productively build.

Introduction

This paper aims to develop a character interaction-based approach to investigating the positions of characters within film narratives. As we outline in the following section, several studies now exist which recognise the potential of network analysis for offering insights into the study of fictional narrative texts and the characters therein (e.g. Moretti, 2011; Sack, 2014; Waumans et al., 2015). These studies range from in-depth textual readings of particular texts to computational interventions in literary network extraction with little to no literary analysis. What the studies all share is the assumption that network tools might assist in the analysis of narrative texts, an assumption largely born out of the growing field of digital humanities scholarship. In this paper, we aim to contribute to the literature in this area by intervening in the discussion of how we relate node-level network measures to interpretative readings of characters’ positions within narratives. Engaging with key ideas from narratology and narrative comprehension scholarship, we argue that the dominant approach of applying off-the-shelf centrality measures such as degree and betweenness to aggregated static character networks limits the usefulness of the character networks approach because of the amount of narrative information that is lost through aggregation. Instead, we draw on recent developments in representing and analysing temporal network dynamics to develop a dynamic measure of the relative narrative positions of characters through time (Broccatelli et al., 2016; Everett et al., 2018; Moody, 2002). Our contention is that dynamic approaches such as the one we pursue here are needed in order to capture the way the story is told through its characters. Thus, we contribute both a conceptual refinement to the project of measuring narrative centrality in character networks, as well as the proposal of a novel measure for doing so. These contributions are offered as exploratory steps towards a more analytically productive platform for future network-based study of narrative texts.

The structure of the paper is as follows. In the next section, we provide an outline of existing approaches to analysing fictional texts through character network models. Then, we consider the problem of how to say something meaningful about the relative importance of nodes within the narrative, focusing on how to appropriately represent narratives as network data given the importance of sequence in narratives. We suggest a number of principles for measuring narrative centrality, and outline a method for configuring film texts as character interaction networks based on the distribution of lines of dialogue between characters. Following this discussion, we propose a new approach to measuring the narrative positions of characters in fictional texts and define a dynamic relational measure based on the acts of speaking and being spoken to. As well as offering a conceptual modelling framework for analysing the relative importance of characters in a narrative, some formal properties of the proposed measure are further explored in the appendix. Because of the dynamic nature of the measure, only some properties are analytically tractable, and we cannot provide an exhaustive formal analysis within the scope of this paper. However, the analysis of idealised examples we present could be complemented by simulations in the future. Finally, we offer an application of this measure to the 2015 film Star Wars: The Force Awakens, drawing out the gendered dynamics in the film. This case study illustrates some of the things the measure allows us to observe about the ways in which characters relate to the narrative that cannot be inferred from static measures. In particular, through a focus on the vocal and relational disempowerment of women in film narratives, we show that the approach allows us to use character network data to engage with existing debates in the study of social representation in fictional narrative texts in a way which previous character network approaches cannot. We argue that by focusing on the conceptual links between narrative texts and the way we represent them as data, network-based measures such as this have the potential to contribute more to character-oriented scholarship on those texts than existing approaches have been able to offer.

Section snippets

Character networks

A character network is any network representation in which the nodes are characters in a fictional text. There now exists a number of character network-based studies of literary texts (e.g. Agarwal et al., 2012; Elson et al., 2010; Grayson et al., 2016; Kydros et al., 2015; Jayannavar et al., 2015; Min and Park, 2016; Moretti, 2011; Sack, 2014; Waumans et al., 2015). These literary character network studies have primarily been concerned with questions of network topology, the process of

Relating network positions to narrative positions

One of the ways in which network tools can be brought to bear on the study of narrative texts is through the application of measures of node importance to the characters in a text in order to explore existing debates and theories concerning issues such as visibility, representation and the relationship between characters and narratives. The strategy that has been pursued in existing character networks approaches has been to apply standard network centrality measures (such as degree and

Data representation

In order to operationalise the ideas in the previous section, we assume a dialogue-based character interaction network model designed to investigate questions of vocal and relational (dis)empowerment in Hollywood narratives (see Jones, 2018). Unlike existing approaches to character networks which tend to deploy automatic extraction methods based on textual proximity (discussed in Section 2), the manual approach proposed here constructs ties based on direct interaction between characters, as we

Application: women in popular film

In this section we provide an example of how the measure can be applied to real questions about narrative texts using the example of gendered representation in film. In particular, we focus on the issue of the vocal and relational disempowerment of female characters in popular Hollywood cinema.

Discussion

Fig. 1, Fig. 2 plot the speaking and spoken-to measures, respectively, using the λ value of 0.01. Lower λ values allow for smoother trajectories for the characters but make the measure less sensitive, which makes it harder for characters to establish their centrality later in the film. A second consequence of this insensitivity is that the score of characters who establish a high centrality earlier in the film but do not continue to contribute vocally to the film thereafter will decline at a

Conclusions

In this paper we have aimed to develop a more integrated conceptual-methodological approach to the node-level analysis of character networks based on fictional texts. Thus, the paper contributes on two fronts: (1) a conceptual refinement of the character networks approach to analysing fictional texts, and (2) the development of a dynamic node-level measure for analysing the positions of characters within such texts. The conceptual refinement is found in the departure from the existing approach

Declaration of Competing Interest

None.

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