@inproceedings{dai-etal-2018-fine,
title = "Fine-grained Structure-based News Genre Categorization",
author = "Dai, Zeyu and
Taneja, Himanshu and
Huang, Ruihong",
editor = "Caselli, Tommaso and
Miller, Ben and
van Erp, Marieke and
Vossen, Piek and
Palmer, Martha and
Hovy, Eduard and
Mitamura, Teruko and
Caswell, David and
Brown, Susan W. and
Bonial, Claire",
booktitle = "Proceedings of the Workshop Events and Stories in the News 2018",
month = aug,
year = "2018",
address = "Santa Fe, New Mexico, U.S.A",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-4308",
pages = "61--67",
abstract = "Journalists usually organize and present the contents of a news article following a well-defined structure. In this work, we propose a new task to categorize news articles based on their content presentation structures, which is beneficial for various NLP applications. We first define a small set of news elements considering their functions (e.g., \textit{introducing the main story or event, catching the reader{'}s attention} and \textit{providing details}) in a news story and their writing style (\textit{narrative} or \textit{expository}), and then formally define four commonly used news article structures based on their selections and organizations of news elements. We create an annotated dataset for structure-based news genre identification, and finally, we build a predictive model to assess the feasibility of this classification task using structure indicative features.",
}
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<abstract>Journalists usually organize and present the contents of a news article following a well-defined structure. In this work, we propose a new task to categorize news articles based on their content presentation structures, which is beneficial for various NLP applications. We first define a small set of news elements considering their functions (e.g., introducing the main story or event, catching the reader’s attention and providing details) in a news story and their writing style (narrative or expository), and then formally define four commonly used news article structures based on their selections and organizations of news elements. We create an annotated dataset for structure-based news genre identification, and finally, we build a predictive model to assess the feasibility of this classification task using structure indicative features.</abstract>
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%0 Conference Proceedings
%T Fine-grained Structure-based News Genre Categorization
%A Dai, Zeyu
%A Taneja, Himanshu
%A Huang, Ruihong
%Y Caselli, Tommaso
%Y Miller, Ben
%Y van Erp, Marieke
%Y Vossen, Piek
%Y Palmer, Martha
%Y Hovy, Eduard
%Y Mitamura, Teruko
%Y Caswell, David
%Y Brown, Susan W.
%Y Bonial, Claire
%S Proceedings of the Workshop Events and Stories in the News 2018
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico, U.S.A
%F dai-etal-2018-fine
%X Journalists usually organize and present the contents of a news article following a well-defined structure. In this work, we propose a new task to categorize news articles based on their content presentation structures, which is beneficial for various NLP applications. We first define a small set of news elements considering their functions (e.g., introducing the main story or event, catching the reader’s attention and providing details) in a news story and their writing style (narrative or expository), and then formally define four commonly used news article structures based on their selections and organizations of news elements. We create an annotated dataset for structure-based news genre identification, and finally, we build a predictive model to assess the feasibility of this classification task using structure indicative features.
%U https://aclanthology.org/W18-4308
%P 61-67
Markdown (Informal)
[Fine-grained Structure-based News Genre Categorization](https://aclanthology.org/W18-4308) (Dai et al., EventStory 2018)
ACL