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  1. 02 情報科学
  2. 02 国際会議論文

Aspect-based Analysis of Advertising Appeals for Search Engine Advertising

http://hdl.handle.net/10061/0002000458
http://hdl.handle.net/10061/0002000458
3b263f17-fd92-486f-90a6-044bb73d3051
アイテムタイプ 会議発表論文 / Conference Paper(1)
公開日 2024-06-07
タイトル
タイトル Aspect-based Analysis of Advertising Appeals for Search Engine Advertising
言語
言語 eng
資源タイプ
資源タイプ conference paper
アクセス権
アクセス権 open access
著者 Murakami, Soichiro

× Murakami, Soichiro

en Murakami, Soichiro

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Zhang, Peinan

× Zhang, Peinan

en Zhang, Peinan

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Hoshino, Sho

× Hoshino, Sho

en Hoshino, Sho

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上垣外, 英剛

× 上垣外, 英剛

WEKO 35596

ja 上垣外, 英剛

ja-Kana カミガイト, ヒデタカ

en Kamigaito, Hidetaka


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Takamura, Hiroya

× Takamura, Hiroya

en Takamura, Hiroya

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Okumura, Manabu

× Okumura, Manabu

en Okumura, Manabu

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抄録
内容記述タイプ Abstract
内容記述 Writing an ad text that attracts people and persuades them to click or act is essential for the success of search engine advertising. Therefore, ad creators must consider various aspects of advertising appeals (A3) such as the price, product features, and quality. However, products and services exhibit unique effective A3 for different industries. In this work, we focus on exploring the effective A3 for different industries with the aim of assisting the ad creation process. To this end, we created a dataset of advertising appeals and used an existing model that detects various aspects for ad texts. Our experiments demonstrated %through correlation analysis that different industries have their own effective A3 and that the identification of the A3 contributes to the estimation of advertising performance.
書誌情報 en : Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track

p. 69-78, 発行日 2022-07-10
会議情報
会議名 Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track
開始年 2022
開始月 07
開始日 10
終了年 2022
終了月 07
終了日 15
開催地 Seattle
開催国 USA
出版者
出版者 Association for Computational Linguistics
出版者版DOI
関連タイプ isReplacedBy
識別子タイプ DOI
関連識別子 https://doi.org/10.18653/v1/2022.naacl-industry.9
出版者版URI
関連タイプ isReplacedBy
識別子タイプ URI
関連識別子 https://aclanthology.org/2022.naacl-industry.9/
権利
権利情報Resource http://creativecommons.org/licenses/by/4.0/
権利情報 $00A92022 Association for Computational Linguistics
著者版フラグ
出版タイプ NA
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