A Novel Method for Extracting Dynamic Character Network from Movie

Tran, Quang Dieu; Hwang, Dosam; Lee, O-Joun; Jung, Jason J.

doi:10.1007/978-3-319-58967-1_6

Cited by 5 publications

(5 citation statements)

References 5 publications

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“…Certain authors extract a dynamic but cumulative network [167,175,247,264]. This means that, to obtain the graph representing a given moment in the narrative, they do not use only the corresponding time slice, but rather the portion of the narrative going from the very start to the considered moment, as illustrated by Figure 10.…”

Section: /75mentioning

confidence: 99%

“…Static networks present an obvious limitation, as identified by numerous authors in the context of character networks [11,35,184,208,247]: they result in a significant information loss, as they completely hide the chronology of the interactions. Yet, the order in which events occur is crucial to characterize a story, and for the writer it is generally at the core of the writing process.…”

Section: Dynamic Networkmentioning

confidence: 99%

“…Other than that, the principle is the same as before: they perform a temporal integration over this period, and do so for every moment in the narrative to get a series of graphs constituting their dynamic network. As before, some authors consider unweighted graphs [264], others use the numbers of interactions [167,247,272] or the total interaction scores [245] as edge weights. Nalisnick & Braid [175] proceed similarly, but as their interaction scores are signed, the weights of the edges do not necessarily increase with time.…”

Section: /75mentioning

confidence: 99%

See 2 more Smart Citations

Extraction and Analysis of Fictional Character Networks

Labatut

Bost

2019

ACM Comput. Surv.

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A character network is a graph extracted from a narrative, in which vertices represent characters and edges correspond to interactions between them. A number of narrative-related problems can be addressed automatically through the analysis of character networks, such as summarization, classification, or role detection. Character networks are particularly relevant when considering works of fictions (e.g. novels, plays, movies, TV series), as their exploitation allows developing information retrieval and recommendation systems. However, works of fiction possess specific properties making these tasks harder.This survey aims at presenting and organizing the scientific literature related to the extraction of character networks from works of fiction, as well as their analysis. We first describe the extraction process in a generic way, and explain how its constituting steps are implemented in practice, depending on the medium of the narrative, the goal of the network analysis, and other factors. We then review the descriptive tools used to characterize character networks, with a focus on the way they are interpreted in this context. We illustrate the relevance of character networks by also providing a review of applications derived from their analysis. Finally, we identify the limitations of the existing approaches, and the most promising perspectives.

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Section: /75mentioning

confidence: 99%

Section: Dynamic Networkmentioning

confidence: 99%

Section: /75mentioning

confidence: 99%

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Extraction and Analysis of Fictional Character Networks

Labatut

Bost

2019

ACM Comput. Surv.

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“…Since narrative works and stories are time-sequential, the existing studies [6,9,27] have defined the character network as a dynamic social network. They attempted to analyze stories' development based on how character networks dynamically evolve.…”

Section: Character Network and Plot Structuresmentioning

confidence: 99%

Plot Structure Decomposition in Narrative Multimedia by Analyzing Personalities of Fictional Characters

2021

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This study aims to decompose plot structures of stories in narrative multimedia (i.e., creative works that contain stories and are distributed through multimedia). Since a story is interwoven with main plots and subplots (i.e., primary and ancillary story lines), decomposing a story into multiple story lines enables us to analyze how events in the story are allocated and logically connected. For the decomposition, the existing studies employed character networks (i.e., social networks of characters that appeared in a story) and assumed that characters’ social relationships are consistent in a story line. However, these studies overlooked that social relationships significantly change around major events. To solve this problem, we attempt to use the changes for distinguishing story lines rather than suffer from the changes. We concentrate on the changes in characters’ social relationships being the result of changes in their personalities. Moreover, these changes gradually proceed within a story line. Therefore, we first propose features for measuring changes in personalities of characters: (i) Degrees of characters in character networks, (ii) lengths of dialogues spoken by characters, and (iii) ratios of out-degrees for in-degrees of characters in character networks. We supposed these features reflect importance, inner/outer conflicts, and activeness of characters, respectively. Since characters’ personalities gradually change in a story line, we can suppose that the features also show gradual story developments in a story line. Therefore, we conduct regression for each feature to discover dominant tendencies of the features. By filtering scenes that do not follow the tendencies, we extract a story line that exhibits the most dominant personality changes. We can decompose stories into multiple story lines by iterating the regression and filtering. Besides, personalities of characters change more significantly in major story lines. Based on this assumption, we also propose methods for discriminating main plots. Finally, we evaluated the accuracy of the proposed methods by applying them to the movies, which is one of the most popular narrative multimedia.

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“…Various studies have been conducted for extracting social networks in narrative artworks and discovering narrative features from the social networks [46]. These studies extracted the social networks from texts [47,48], videos [33,49,50], or both of them [51,52]. A few studies applied sentiment analysis to enrich the social networks [34,53].…”

Section: Related Workmentioning

confidence: 99%

Discovering Social Desires and Conflicts from Subculture Narrative Multimedia

et al. 2020

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This study aims at discovering social desires and conflicts from subculture narrative multimedia. Since one of the primary purposes in the subculture consumption is vicarious satisfaction, the subculture works straightforwardly describe what their readers want to achieve and break down. The latent desires and conflicts are useful for understanding our society and realizing smart governance. To discover the social issues, we concentrate on that each subculture genre has a unique imaginary world that consists of inventive subjects. We suppose that the subjects correspond to individual social issues. For example, game fiction, one of the popular genres, describes a world like video games. Under game systems, everyone gets the same results for the same efforts, and it can be interpreted as critics for the social inequality issue. Therefore, we first extract subjects of genres and measure the membership degrees of subculture works for each genre. Using the subjects and membership degrees, we build a genealogy tree of subculture genres by tracing their evolution and differentiation. Then, we extract social issues by searching for the subjects that come from the real world, not imaginary. If a subculture work criticizes authoritarianism, it might include subjects such as government officials and bureaucrats. A combination of the social issues and genre genealogy tree will show diachronic changes in our society. We have evaluated the proposed methods by extracting social issues reflected in Korean web novels.

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A Novel Method for Extracting Dynamic Character Network from Movie

Cited by 5 publications

References 5 publications

Extraction and Analysis of Fictional Character Networks

Extraction and Analysis of Fictional Character Networks

Plot Structure Decomposition in Narrative Multimedia by Analyzing Personalities of Fictional Characters

Discovering Social Desires and Conflicts from Subculture Narrative Multimedia

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