ABSTRACT
ABSTRACT: Recent efforts to digitize literary works emphasize the importance of a computational route to analyzing large collections of text. To better understand the literary narrative, most research focuses on modeling it from the viewpoint of events or characters. Recently, character-centric approaches have been used to extract relationships between people, which enables better understanding of the narrative. Different methodologies consider distinct types of relationships. The purpose of this paper is to survey the various methodologies that try to infer interpersonal relationships of characters in narratives. The advantages and limitations of each method are compared and the various datasets used in each methodology are discussed in this paper.
