作为文本模型的自动足球比赛报告

IF 0.8 3区 文学 Q3 COMMUNICATION
Text & Talk Pub Date : 2024-01-25 DOI:10.1515/text-2022-0173
Simon Meier-Vieracker
{"title":"作为文本模型的自动足球比赛报告","authors":"Simon Meier-Vieracker","doi":"10.1515/text-2022-0173","DOIUrl":null,"url":null,"abstract":"This paper deals with automated football match reports as a common genre of automated journalism. Based on a corpus of automated and human-written reports (<jats:italic>n</jats:italic> = 1,302) on the same set of matches and with reference to linguistic concepts of text and textuality, the textual properties of these texts are analyzed both quantitatively and qualitatively. The analysis is based on the idea that the task of text generation can be described as the task of automatically selecting cues of textuality such as connectives or signals of thematic relatedness. The results show that automated and human-written texts differ significantly in the use of these cues, particularly in the use of linguistic means for creating evaluation and contrast, and thus allow to trace in detail, how these cues contribute to cohesion, coherence and narrative qualities. Different from computational linguistic approaches focused on optimizing text generation algorithms, this paper proposes to use automated texts, which are to some extent imperfect, as models of textuality that through their imperfection can say something about the nature of texts in general. The paper thus contributes to the field of (mostly communication studies) research on automated journalism in which the texts themselves are rarely investigated.","PeriodicalId":46455,"journal":{"name":"Text & Talk","volume":"2 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automated football match reports as models of textuality\",\"authors\":\"Simon Meier-Vieracker\",\"doi\":\"10.1515/text-2022-0173\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with automated football match reports as a common genre of automated journalism. Based on a corpus of automated and human-written reports (<jats:italic>n</jats:italic> = 1,302) on the same set of matches and with reference to linguistic concepts of text and textuality, the textual properties of these texts are analyzed both quantitatively and qualitatively. The analysis is based on the idea that the task of text generation can be described as the task of automatically selecting cues of textuality such as connectives or signals of thematic relatedness. The results show that automated and human-written texts differ significantly in the use of these cues, particularly in the use of linguistic means for creating evaluation and contrast, and thus allow to trace in detail, how these cues contribute to cohesion, coherence and narrative qualities. Different from computational linguistic approaches focused on optimizing text generation algorithms, this paper proposes to use automated texts, which are to some extent imperfect, as models of textuality that through their imperfection can say something about the nature of texts in general. The paper thus contributes to the field of (mostly communication studies) research on automated journalism in which the texts themselves are rarely investigated.\",\"PeriodicalId\":46455,\"journal\":{\"name\":\"Text & Talk\",\"volume\":\"2 1\",\"pages\":\"\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2024-01-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Text & Talk\",\"FirstCategoryId\":\"98\",\"ListUrlMain\":\"https://doi.org/10.1515/text-2022-0173\",\"RegionNum\":3,\"RegionCategory\":\"文学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMMUNICATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Text & Talk","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1515/text-2022-0173","RegionNum":3,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMMUNICATION","Score":null,"Total":0}
引用次数: 0

摘要

本文论述了自动足球比赛报道这一常见的自动新闻体裁。基于同一组比赛的自动报告和人工撰写报告的语料库(n = 1,302),并参考文本和文本性的语言学概念,对这些文本的文本属性进行了定量和定性分析。分析所依据的理念是,文本生成任务可以描述为自动选择文本性线索(如连接词或主题相关性信号)的任务。分析结果表明,自动生成的文本和人类撰写的文本在使用这些线索,特别是在使用语言手段进行评价和对比方面存在显著差异,因此可以详细追踪这些线索如何促进内聚力、连贯性和叙事质量。与专注于优化文本生成算法的计算语言学方法不同,本文建议使用在某种程度上并不完美的自动文本,将其作为文本性的模型,通过它们的不完美来说明文本的一般性质。因此,本文对自动新闻学研究领域(主要是传播学研究)做出了贡献,因为该领域很少对文本本身进行研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated football match reports as models of textuality
This paper deals with automated football match reports as a common genre of automated journalism. Based on a corpus of automated and human-written reports (n = 1,302) on the same set of matches and with reference to linguistic concepts of text and textuality, the textual properties of these texts are analyzed both quantitatively and qualitatively. The analysis is based on the idea that the task of text generation can be described as the task of automatically selecting cues of textuality such as connectives or signals of thematic relatedness. The results show that automated and human-written texts differ significantly in the use of these cues, particularly in the use of linguistic means for creating evaluation and contrast, and thus allow to trace in detail, how these cues contribute to cohesion, coherence and narrative qualities. Different from computational linguistic approaches focused on optimizing text generation algorithms, this paper proposes to use automated texts, which are to some extent imperfect, as models of textuality that through their imperfection can say something about the nature of texts in general. The paper thus contributes to the field of (mostly communication studies) research on automated journalism in which the texts themselves are rarely investigated.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Text & Talk
Text & Talk Multiple-
CiteScore
1.70
自引率
16.70%
发文量
70
期刊介绍: Text & Talk (founded as TEXT in 1981) is an internationally recognized forum for interdisciplinary research in language, discourse, and communication studies, focusing, among other things, on the situational and historical nature of text/talk production; the cognitive and sociocultural processes of language practice/action; and participant-based structures of meaning negotiation and multimodal alignment. Text & Talk encourages critical debates on these and other relevant issues, spanning not only the theoretical and methodological dimensions of discourse but also their practical and socially relevant outcomes.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信