https://w3id.org/np/RAz-WvUqhGgpt55eGSHL-kbAesZ5S5H3NDS0Zobw6j1yk/Head https://w3id.org/np/RAz-WvUqhGgpt55eGSHL-kbAesZ5S5H3NDS0Zobw6j1yk http://www.nanopub.org/nschema#hasAssertion https://w3id.org/np/RAz-WvUqhGgpt55eGSHL-kbAesZ5S5H3NDS0Zobw6j1yk/assertion https://w3id.org/np/RAz-WvUqhGgpt55eGSHL-kbAesZ5S5H3NDS0Zobw6j1yk http://www.nanopub.org/nschema#hasProvenance https://w3id.org/np/RAz-WvUqhGgpt55eGSHL-kbAesZ5S5H3NDS0Zobw6j1yk/provenance https://w3id.org/np/RAz-WvUqhGgpt55eGSHL-kbAesZ5S5H3NDS0Zobw6j1yk http://www.nanopub.org/nschema#hasPublicationInfo https://w3id.org/np/RAz-WvUqhGgpt55eGSHL-kbAesZ5S5H3NDS0Zobw6j1yk/pubinfo https://w3id.org/np/RAz-WvUqhGgpt55eGSHL-kbAesZ5S5H3NDS0Zobw6j1yk http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.nanopub.org/nschema#Nanopublication https://w3id.org/np/RAz-WvUqhGgpt55eGSHL-kbAesZ5S5H3NDS0Zobw6j1yk/assertion http://id.crossref.org/issn/2376-5992 http://purl.org/dc/terms/title PeerJ Computer Science https://doi.org/10.7717/peerj-cs.189 http://purl.org/dc/terms/abstract The analysis of literary works has experienced a surge in computer-assisted processing. To obtain insights into the community structures and social interactions portrayed in novels, the creation of social networks from novels has gained popularity. Many methods rely on identifying named entities and relations for the construction of these networks, but many of these tools are not specifically created for the literary domain. Furthermore, many of the studies on information extraction from literature typically focus on 19th and early 20th century source material. Because of this, it is unclear if these techniques are as suitable to modern-day literature as they are to those older novels. We present a study in which we evaluate natural language processing tools for the automatic extraction of social networks from novels as well as their network structure. We find that there are no significant differences between old and modern novels but that both are subject to a large amount of variance. Furthermore, we identify several issues that complicate named entity recognition in our set of novels and we present methods to remedy these. We see this work as a step in creating more culturally-aware AI systems. https://doi.org/10.7717/peerj-cs.189 http://purl.org/dc/terms/date 2019-04-18 https://doi.org/10.7717/peerj-cs.189 http://purl.org/dc/terms/isPartOf http://id.crossref.org/issn/2376-5992 https://doi.org/10.7717/peerj-cs.189 http://purl.org/dc/terms/title Evaluating named entity recognition tools for extracting social networks from novels https://doi.org/10.7717/peerj-cs.189 http://purl.org/ontology/bibo/authorList https://w3id.org/np/RAz-WvUqhGgpt55eGSHL-kbAesZ5S5H3NDS0Zobw6j1yk/author-list https://doi.org/10.7717/peerj-cs.189 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Article https://orcid.org/0000-0001-9195-8203 http://schema.org/affiliation https://ror.org/043c0p156 https://orcid.org/0000-0001-9195-8203 http://xmlns.com/foaf/0.1/name Marieke van Erp https://orcid.org/0000-0002-1267-0234 http://schema.org/affiliation https://ror.org/008xxew50 https://orcid.org/0000-0002-1267-0234 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