Network analysis of narrative content in large corpora

@article{Sudhahar2013NetworkAO,
  title={Network analysis of narrative content in large corpora},
  author={Saatviga Sudhahar and Gianluca de Fazio and Roberto Franzosi and Nello Cristianini},
  journal={Natural Language Engineering},
  year={2013},
  volume={21},
  pages={81 - 112}
}
Abstract We present a methodology for the extraction of narrative information from a large corpus. The key idea is to transform the corpus into a network, formed by linking the key actors and objects of the narration, and then to analyse this network to extract information about their relations. By representing information into a single network it is possible to infer relations between these entities, including when they have never been mentioned together. We discuss various types of… 
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33 Citations
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33 Citations

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References

SHOWING 1-10 OF 58 REFERENCES
Extracting Social Networks from Literary Fiction
TLDR
The method involves character name chunking, quoted speech attribution and conversation detection given the set of quotes, which provides evidence that the majority of novels in this time period do not fit two characterizations provided by literacy scholars.
Social Network Analysis of Alice in Wonderland
TLDR
This paper annotates Lewis Carroll's Alice in Wonderland using a well-defined annotation scheme which has been used in previous computational models that extract social events from news articles and builds novel types of networks in which links between characters are different types of social events.
Narrative as Data: Linguistic and Statistical Tools for the Quantitative Study of Historical Events *
TLDR
The paper shows that “semantic grammars” provide rigorous tools for the collection of rich event narratives and should draw sociology closer to history, traditionally much more concerned with issues of agency.
Social Media Analytics and Intelligence
TLDR
This special issue samples the state of the art in social media analytics and intelligence research that has direct relevance to the AI subfield from either an methodological or domain perspective.
Network theory, plot analysis
TLDR
This paper is the beginning of an answer in network theory, a theory that studies connections within large groups of objects and reveals many unexpected features of large systems, the most famous one being the so-called "small-world" property, or "six degrees of separation".
Extracting Signed Social Networks from Text
TLDR
This work proposes a new method to automatically construct a signed social network from text that has a polarity associated with every edge and connects out analysis to social psychology theories of signed network, namely the structural balance theory.
Automatic Discovery of Patterns in Media Content
TLDR
The results presented in this survey show how the automatic analysis of millions of documents in dozens of different languages can detect non-trivial macro-patterns that could not be observed at a smaller scale, and how the social sciences can benefit from closer interaction with the pattern analysis, artificial intelligence and text mining research communities.
Question Answering Based on Semantic Graphs
TLDR
A question answering system supported by semantic graphs that provides answers to natural language questions via a visual representation of documents, their associated list of facts described by subject – verb – object triplets, and their summaries.
Graph-based Natural Language Processing and Information Retrieval
TLDR
This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval, bringing together topics as diverse as lexical semantics, text summarization, text mining, ontology construction, text classification, and information retrieved.
NOAM: news outlets analysis and monitoring system
TLDR
NoAM is the data management system behind various applications and scientific studies aiming at modelling the mediasphere, and combines a relational database with state of the art AI technologies, including data mining, machine learning and natural language processing.
...
...