Pub Date : 2013-08-04DOI: 10.4230/OASIcs.CMN.2013.310
K. Truong, G. Westerhof, S. Lamers, F. D. Jong, Anneke M. Sools
Audiovisual collections of narratives about war-traumas are rich in descriptions of personal and emotional experiences which can be expressed through verbal and nonverbal means. We complement a commonly used verbal analysis with a nonverbal one to study emotional developments in narratives. Using automatic text, vocal, and facial expression analysis we found that verbal emotional expressions do not correspond much to nonverbal ones. This observation may have important implications for the way narratives traditionally are being studied. We aim to understand how different modes of narrative expression relate to each other, and to enrich digital audiovisual interview collections with emotion-oriented tags.
{"title":"Emotional Expression in Oral History Narratives: Comparing Results of Automated Verbal and Nonverbal Analyses","authors":"K. Truong, G. Westerhof, S. Lamers, F. D. Jong, Anneke M. Sools","doi":"10.4230/OASIcs.CMN.2013.310","DOIUrl":"https://doi.org/10.4230/OASIcs.CMN.2013.310","url":null,"abstract":"Audiovisual collections of narratives about war-traumas are rich in descriptions of personal and emotional experiences which can be expressed through verbal and nonverbal means. We complement a commonly used verbal analysis with a nonverbal one to study emotional developments in narratives. Using automatic text, vocal, and facial expression analysis we found that verbal emotional expressions do not correspond much to nonverbal ones. This observation may have important implications for the way narratives traditionally are being studied. We aim to understand how different modes of narrative expression relate to each other, and to enrich digital audiovisual interview collections with emotion-oriented tags.","PeriodicalId":311534,"journal":{"name":"Workshop on Computational Models of Narrative","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125749588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-08-01DOI: 10.4230/OASIcs.CMN.2013.293
M. Theune, Thijs Alofs, J. Linssen, Ivo Swartjes
In the emergent narrative approach to Interactive Storytelling, narratives arise from the interactions between player- or computer-controlled characters in a simulated story world. This approach offers much freedom to the players, but this freedom may come at the cost of narrative structure. In this paper we study stories created by children using a storytelling system based on the emergent narrative approach. We investigate how coherent these stories actually are and which types of character actions contribute the most to story coherence, defined in terms of the causal connectedness of story elements. We find that although the children do produce goal-directed story lines, overall the stories are only partially coherent. This can be explained by the improvisational nature of the children’s storytelling with our system, where the interactive experience of the players is more important than the production of a coherent narrative. We also observe that the communication between the children, external to the system, plays an important role in establishing coherence of the created stories.
{"title":"Having one's cake and eating it too: Coherence of children's emergent narratives","authors":"M. Theune, Thijs Alofs, J. Linssen, Ivo Swartjes","doi":"10.4230/OASIcs.CMN.2013.293","DOIUrl":"https://doi.org/10.4230/OASIcs.CMN.2013.293","url":null,"abstract":"In the emergent narrative approach to Interactive Storytelling, narratives arise from the interactions between player- or computer-controlled characters in a simulated story world. This approach offers much freedom to the players, but this freedom may come at the cost of narrative structure. In this paper we study stories created by children using a storytelling system based on the emergent narrative approach. We investigate how coherent these stories actually are and which types of character actions contribute the most to story coherence, defined in terms of the causal connectedness of story elements. We find that although the children do produce goal-directed story lines, overall the stories are only partially coherent. This can be explained by the improvisational nature of the children’s storytelling with our system, where the interactive experience of the players is more important than the production of a coherent narrative. We also observe that the communication between the children, external to the system, plays an important role in establishing coherence of the created stories.","PeriodicalId":311534,"journal":{"name":"Workshop on Computational Models of Narrative","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130160619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-05-01DOI: 10.4230/OASIcs.CMN.2013.158
Angela Nyhout, D. O'Neill
Although narratives often contain detailed descriptions of space and setting and readers frequently report vividly imagining these story worlds, evidence for the construction of spatial representations during narrative processing is currently mixed. In the present study, we investigated 7 year old children's ability to construct spatial representations of narrative spaces and compared this to the ability to construct representations from non-narrative descriptions. We hypothesized that performance would be better in the narrative condition, where children have the opportunity to construct a multi-dimensional situation model built around the character's motivations and actions. Children listened to either a narrative that included a character traveling between 5 locations in her neighbourhood or a description of the same 5-location neighbourhood. Those in the narrative condition significantly outperformed those in the description condition in constructing the layout of the neighbourhood locations. Moreover, regression analyses revealed that whereas performance on the narrative version was predicted by narrative comprehension ability, performance on the description version was predicted by working memory ability. These results suggest the possibility that building spatial representations from narratives and non-narratives may engage different cognitive processes.
{"title":"Constructing Spatial Representations from Narratives and Non-Narrative Descriptions: Evidence from 7-year-olds","authors":"Angela Nyhout, D. O'Neill","doi":"10.4230/OASIcs.CMN.2013.158","DOIUrl":"https://doi.org/10.4230/OASIcs.CMN.2013.158","url":null,"abstract":"Although narratives often contain detailed descriptions of space and setting and readers frequently report vividly imagining these story worlds, evidence for the construction of spatial representations during narrative processing is currently mixed. In the present study, we investigated 7 year old children's ability to construct spatial representations of narrative spaces and compared this to the ability to construct representations from non-narrative descriptions. We hypothesized that performance would be better in the narrative condition, where children have the opportunity to construct a multi-dimensional situation model built around the character's motivations and actions. Children listened to either a narrative that included a character traveling between 5 locations in her neighbourhood or a description of the same 5-location neighbourhood. Those in the narrative condition significantly outperformed those in the description condition in constructing the layout of the neighbourhood locations. Moreover, regression analyses revealed that whereas performance on the narrative version was predicted by narrative comprehension ability, performance on the description version was predicted by working memory ability. These results suggest the possibility that building spatial representations from narratives and non-narratives may engage different cognitive processes.","PeriodicalId":311534,"journal":{"name":"Workshop on Computational Models of Narrative","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126682561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4230/OASIcs.CMN.2016.9
Adam Amos-Binks, David L. Roberts, R. Young
Branching story games have gained popularity for creating unique playing experiences by adapting story content in response to user actions. Research in interactive narrative (IN) uses automated planning to generate story plans for a given story problem. However, a story planner can generate multiple story plan solutions, all of which equally-satisfy the story problem definition but contain different story content. These differences in story content are key to understanding the story branches in a story problem's solution space, however we lack narrative-theoretic metrics to compare story plans. We address this gap by first defining a story plan summarization model to capture the important story semantics from a story plan. Secondly, we define a story plan comparison metric that compares story plans based on the summarization model. Using the Glaive narrative planner and a simple story problem, we demonstrate the usefulness of using the summarization model and distance metric to characterize the different story branches in a story problem's solution space.
{"title":"Summarizing and Comparing Story Plans","authors":"Adam Amos-Binks, David L. Roberts, R. Young","doi":"10.4230/OASIcs.CMN.2016.9","DOIUrl":"https://doi.org/10.4230/OASIcs.CMN.2016.9","url":null,"abstract":"Branching story games have gained popularity for creating unique playing experiences by adapting story content in response to user actions. Research in interactive narrative (IN) uses automated planning to generate story plans for a given story problem. However, a story planner can generate multiple story plan solutions, all of which equally-satisfy the story problem definition but contain different story content. These differences in story content are key to understanding the story branches in a story problem's solution space, however we lack narrative-theoretic metrics to compare story plans. We address this gap by first defining a story plan summarization model to capture the important story semantics from a story plan. Secondly, we define a story plan comparison metric that compares story plans based on the summarization model. Using the Glaive narrative planner and a simple story problem, we demonstrate the usefulness of using the summarization model and distance metric to characterize the different story branches in a story problem's solution space.","PeriodicalId":311534,"journal":{"name":"Workshop on Computational Models of Narrative","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121079539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4230/OASIcs.CMN.2013.43
David A. Broniatowski, V. Reyna
A major concern regarding the study of narratives regards how they are indexed and retrieved. This is a question which touches on the structure of human memory in general. Indeed, if narratives capture the substance of human thought, then data that we have already collected regarding human memory is of central importance to the computational study of narrative. Fuzzy Trace Theory assumes that memory for narrative is simultaneously stored at multiple levels of abstraction and, whenever possible, decision-makers interpret a stimulus qualitatively and therefore operate on a simple - typically categorical - "gist" representation. Here, we present a computational model of Fuzzy Trace Theory applied to explain the impact of changes in a narrative upon risky-choice framing effects. Overall, our theory predicts the outcome of 20 experimental effects using only three basic assumptions: 1) preference for lowest level of gist, that is, categorical processing; 2) decision options that fall within the same categorical description are then interpreted using finer-grained (ordinal or verbatim) distinctions; and 3) once the options are mentally represented, decision preferences are generated on the basis of simple positive vs. negative valences stored in long-term memory (e.g., positive value for human lives). A fourth assumption - that negatively-valenced decision options are preferentially converted to positive decision options - is used when categories are not otherwise comparable.
{"title":"Gist and Verbatim in Narrative Memory","authors":"David A. Broniatowski, V. Reyna","doi":"10.4230/OASIcs.CMN.2013.43","DOIUrl":"https://doi.org/10.4230/OASIcs.CMN.2013.43","url":null,"abstract":"A major concern regarding the study of narratives regards how they are indexed and retrieved. This is a question which touches on the structure of human memory in general. Indeed, if narratives capture the substance of human thought, then data that we have already collected regarding human memory is of central importance to the computational study of narrative. Fuzzy Trace Theory assumes that memory for narrative is simultaneously stored at multiple levels of abstraction and, whenever possible, decision-makers interpret a stimulus qualitatively and therefore operate on a simple - typically categorical - \"gist\" representation. Here, we present a computational model of Fuzzy Trace Theory applied to explain the impact of changes in a narrative upon risky-choice framing effects. Overall, our theory predicts the outcome of 20 experimental effects using only three basic assumptions: 1) preference for lowest level of gist, that is, categorical processing; 2) decision options that fall within the same categorical description are then interpreted using finer-grained (ordinal or verbatim) distinctions; and 3) once the options are mentally represented, decision preferences are generated on the basis of simple positive vs. negative valences stored in long-term memory (e.g., positive value for human lives). A fourth assumption - that negatively-valenced decision options are preferentially converted to positive decision options - is used when categories are not otherwise comparable.","PeriodicalId":311534,"journal":{"name":"Workshop on Computational Models of Narrative","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124670284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4230/OASIcs.CMN.2014.209
Alan Tapscott, Joaquim Colás, A. Moghnieh, J. Blat
We propose a modified Entity Relationship (E-R) model, traditionally used for software engineering, to structure, store and share plot data. The flexibility of E-R modelling has been demonstrated by its decades of usage in a wide variety of situations. The success of the E-R model suggests that it could be useful for collaborating fiction authors, adding a certain degree of computational power to their process. We changed the E-R model syntax to better suit the story plans, switching the emphasis from generic types to instanced story entities, but preserving relationships and attributes. We conducted a small-scale basic experiment to study the impact of using our modified E-R model on authors when understanding and contributing into a pre-existing fiction story plan. The results analysis revealed that the E-R model supports authors as effectively as written text in reading comprehension, memory, and contributing. In addition, the results show that, when combined together, the written text and the E-R model help participants achieve better comprehension--always within the frame of our experiment. We discuss potential applications of these findings.
{"title":"Modifying Entity Relationship Models for Collaborative Fiction Planning and its Impact on Potential Authors","authors":"Alan Tapscott, Joaquim Colás, A. Moghnieh, J. Blat","doi":"10.4230/OASIcs.CMN.2014.209","DOIUrl":"https://doi.org/10.4230/OASIcs.CMN.2014.209","url":null,"abstract":"We propose a modified Entity Relationship (E-R) model, traditionally used for software engineering, to structure, store and share plot data. The flexibility of E-R modelling has been demonstrated by its decades of usage in a wide variety of situations. The success of the E-R model suggests that it could be useful for collaborating fiction authors, adding a certain degree of computational power to their process. We changed the E-R model syntax to better suit the story \u0000plans, switching the emphasis from generic types to instanced story entities, but preserving relationships and attributes. We conducted a small-scale basic experiment to study the impact of using our modified E-R model on authors when understanding and contributing into a pre-existing fiction story plan. The results analysis revealed that the E-R model supports authors as effectively as written text in reading comprehension, memory, and contributing. In addition, the results show that, when combined together, the written text and the E-R model help participants achieve better comprehension--always within the frame \u0000of our experiment. We discuss potential applications of these findings.","PeriodicalId":311534,"journal":{"name":"Workshop on Computational Models of Narrative","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116266114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4230/OASIcs.CMN.2015.23
B. Cardier
Modeling the effect of context on interpretation, for the purposes of building intelligent systems, has been a long-standing problem: qualities of logic can restrict accurate contextual interpretation, even when there is only one context to consider. Stories offer a range of structures that could extend formal theories of context, indicating how arrays of inferred contexts are able to knit together, making an ontological reference that is specific to the particular set of circumstances embodied in the tale. This derived ontology shifts as the text unfolds, enabling constant revision and the emergence of unexpected meanings. The described approach employs dynamic knowledge representation techniques to model how these structures are built and changed. Two new operators have been designed for this purpose: governance and causal conceptual agents. As an example, a few lines from the story Red Riding Hood As a Dictator Would Tell It are used to demonstrate how a story interpretive framework can be continually re-made, in a way that produces unexpected interpretations of terms.
{"title":"The Evolution of Interpretive Contexts in Stories","authors":"B. Cardier","doi":"10.4230/OASIcs.CMN.2015.23","DOIUrl":"https://doi.org/10.4230/OASIcs.CMN.2015.23","url":null,"abstract":"Modeling the effect of context on interpretation, for the purposes of building intelligent systems, has been a long-standing problem: qualities of logic can restrict accurate contextual interpretation, \u0000even when there is only one context to consider. Stories offer a range of structures that could extend formal theories of context, indicating how arrays of inferred contexts are able to knit together, making an ontological reference that is specific to the particular set of circumstances embodied in the tale. This derived ontology shifts as the text unfolds, enabling constant revision and the emergence of unexpected meanings. The described approach employs dynamic knowledge representation techniques to model how these structures are built and changed. Two new operators have been designed for this purpose: governance and causal conceptual agents. As an example, a few lines from the story Red Riding Hood As a Dictator Would Tell It are used to demonstrate how a story interpretive framework can be continually re-made, in a way that \u0000produces unexpected interpretations of terms.","PeriodicalId":311534,"journal":{"name":"Workshop on Computational Models of Narrative","volume":"59 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114001099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4230/OASIcs.CMN.2014.116
W. MacDougall, R. West, Chris Genovesi
The use of narrative is ubiquitous in the development, exercise, and communication of expertise. Expertise and narrative, as complex cognitive capacities, have each been investigated quite deeply, but little attention has been paid to their interdependence. We oer here the position that treating these two domains together can fruitfully inform the modeling of expert cognition and behavior, and present the framework we have been using to develop this approach, the SGOMS macro-cognitive architecture. Finally, we briefly explore the role of narrative in an SGOMS model of cooperative video game playing. 1998 ACM Subject Classification H.1.0 Models and Principles: General, I.2.0 Artificial Intelligence: Cognitive simulation, I.2.8 Problem Solving, Control Methods, and Search: Plan execution, formation, and generation, I.2.11 Distributed artificial intelligence: Multiagent systems, I.6.5 Model Development: Modeling methodologies
{"title":"Modeling the Function of Narrative in Expertise","authors":"W. MacDougall, R. West, Chris Genovesi","doi":"10.4230/OASIcs.CMN.2014.116","DOIUrl":"https://doi.org/10.4230/OASIcs.CMN.2014.116","url":null,"abstract":"The use of narrative is ubiquitous in the development, exercise, and communication of expertise. Expertise and narrative, as complex cognitive capacities, have each been investigated quite deeply, but little attention has been paid to their interdependence. We oer here the position that treating these two domains together can fruitfully inform the modeling of expert cognition and behavior, and present the framework we have been using to develop this approach, the SGOMS macro-cognitive architecture. Finally, we briefly explore the role of narrative in an SGOMS model of cooperative video game playing. 1998 ACM Subject Classification H.1.0 Models and Principles: General, I.2.0 Artificial Intelligence: Cognitive simulation, I.2.8 Problem Solving, Control Methods, and Search: Plan execution, formation, and generation, I.2.11 Distributed artificial intelligence: Multiagent systems, I.6.5 Model Development: Modeling methodologies","PeriodicalId":311534,"journal":{"name":"Workshop on Computational Models of Narrative","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124334263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4230/OASIcs.CMN.2013.61
Erica Cosentino, I. Adornetti, F. Ferretti
Models of discourse and narration elaborated within the classical compositional framework have been characterized as bottom-up models, according to which discourse analysis proceeds incrementally, from phrase and sentence local meaning to discourse global meaning. In this paper we will argue against these models. Assuming as a case study the issue of discourse coherence, we suggest that the assessment of coherence is a top-down process, in which the construction of a situational interpretation at the global meaning level guides local meaning analysis. In support of our hypothesis, we explore the role of executive functions (brain functions involved in planning and organization of goal-oriented behaviors) in coherence's establishment, discussing the results of several studies on narrative abilities of patients with brain injuries. We suggest that, compared to other models of discourse processing focused on comprehension, our model is a viable candidate for an integrated account of discourse comprehension and production.
{"title":"Processing Narrative Coherence: Towards a Top-Down Model of Discourse","authors":"Erica Cosentino, I. Adornetti, F. Ferretti","doi":"10.4230/OASIcs.CMN.2013.61","DOIUrl":"https://doi.org/10.4230/OASIcs.CMN.2013.61","url":null,"abstract":"Models of discourse and narration elaborated within the classical \u0000compositional framework have been characterized as bottom-up models, \u0000according to which discourse analysis proceeds incrementally, from \u0000phrase and sentence local meaning to discourse global meaning. In this \u0000paper we will argue against these models. Assuming as a case study the \u0000issue of discourse coherence, we suggest that the assessment of \u0000coherence is a top-down process, in which the construction of a \u0000situational interpretation at the global meaning level guides local \u0000meaning analysis. In support of our hypothesis, we explore the role of \u0000executive functions (brain functions involved in planning and \u0000organization of goal-oriented behaviors) in coherence's establishment, \u0000discussing the results of several studies on narrative abilities of \u0000patients with brain injuries. We suggest that, compared to other \u0000models of discourse processing focused on comprehension, our model is \u0000a viable candidate for an integrated account of discourse \u0000comprehension and production.","PeriodicalId":311534,"journal":{"name":"Workshop on Computational Models of Narrative","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121435892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4230/OASIcs.CMN.2013.129
Elektra Kypridemou, Loizos Michael
The ability to identify similarities between narratives has been argued to be central in human interactions. Previous work that sought to formalize this task has hypothesized that narrative similarity can be equated to the existence of a common summary between the narratives involved. We offer tangible psychological evidence in support of this hypothesis. Human participants in our empirical study were presented with triples of stories, and were asked to rate: (i) the degree of similarity between story A and story B; (ii) the appropriateness of story C as a summary of story A; (iii) the appropriateness of story C as a summary of story B. The story triples were selected systematically to span the space of their possible interrelations. Empirical evidence gathered from this study overwhelmingly supports the position that the higher the latter two ratings are, the higher the first rating also is. Thus, while this work does not purport to formally define either of the two tasks involved, it does argue that one can be meaningfully reduced to the other.
{"title":"Narrative Similarity as Common Summary","authors":"Elektra Kypridemou, Loizos Michael","doi":"10.4230/OASIcs.CMN.2013.129","DOIUrl":"https://doi.org/10.4230/OASIcs.CMN.2013.129","url":null,"abstract":"The ability to identify similarities between narratives has been argued to be central in human interactions. Previous work that sought to formalize this task has hypothesized that narrative similarity can be equated to the existence of a common summary between the narratives involved. We offer tangible psychological evidence in support of this hypothesis. Human participants in our empirical study were presented with triples of stories, and were asked to rate: (i) the degree of similarity between story A and story B; (ii) the appropriateness of story C as a summary of story A; (iii) the appropriateness of story C as a summary of story B. The story triples were selected systematically to span the space of their possible interrelations. Empirical evidence gathered from this study overwhelmingly supports the position that the higher the latter two ratings are, the higher the first rating also is. Thus, while this work does not purport to formally define either of the two tasks involved, it does argue that one can be meaningfully reduced to the other.","PeriodicalId":311534,"journal":{"name":"Workshop on Computational Models of Narrative","volume":"55 34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132080216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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