Reproducibility Companion Paper: Visual Sentiment Analysis for Review Images with Item-Oriented and User-Oriented CNN

Quoc-Tuan Truong; Hady W Lauw; Martin Aumüller; Naoko Nitta

doi:10.1145/3394171.3414813

Reproducibility Companion Paper: Visual Sentiment Analysis for Review Images with Item-Oriented and User-Oriented CNN

Quoc-Tuan Truong, Hady W Lauw, Martin Aumüller, Naoko Nitta

Publikation: Konference artikel i Proceeding eller bog/rapport kapitel › Konferencebidrag i proceedings › Forskning › peer review

Abstract

We revisit our contributions on visual sentiment analysis for online review images published at ACM Multimedia 2017, where we develop item-oriented and user-oriented convolutional neural networks that better capture the interaction of image features with specific expressions of users or items. In this work, we outline the experimental claims as well as describe the procedures to reproduce the results therein. In addition, we provide artifacts including data sets and code to replicate the experiments.

Originalsprog	Engelsk
Titel	MM '20: Proceedings of the 28th ACM International Conference on Multimedia
Forlag	Association for Computing Machinery
Publikationsdato	2020
Sider	4444-4447
DOI	https://doi.org/10.1145/3394171.3414813
Status	Udgivet - 2020
Begivenhed	International Conference on Multimedia - Varighed: 12 okt. 2020 → … Konferencens nummer: 28

Konference

Konference	International Conference on Multimedia
Nummer	28
Periode	12/10/2020 → …

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10.1145/3394171.3414813

ACM_MM_2020_Repro_Paper29061Korrektur, 3,03 MB

Citationsformater

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title = "Reproducibility Companion Paper: Visual Sentiment Analysis for Review Images with Item-Oriented and User-Oriented CNN",

abstract = "We revisit our contributions on visual sentiment analysis for online review images published at ACM Multimedia 2017, where we develop item-oriented and user-oriented convolutional neural networks that better capture the interaction of image features with specific expressions of users or items. In this work, we outline the experimental claims as well as describe the procedures to reproduce the results therein. In addition, we provide artifacts including data sets and code to replicate the experiments.",

keywords = "Visual Sentiment Analysis, Convolutional Neural Networks, Online Review Images, Experimental Reproducibility, Data Sets and Code",

author = "Quoc-Tuan Truong and Lauw, {Hady W} and Martin Aum{\"u}ller and Naoko Nitta",

year = "2020",

doi = "10.1145/3394171.3414813",

language = "English",

pages = "4444--4447",

booktitle = "MM '20: Proceedings of the 28th ACM International Conference on Multimedia",

publisher = "Association for Computing Machinery",

address = "United States",

note = "International Conference on Multimedia, ACM MM ; Conference date: 12-10-2020",

}

Truong, Q-T, Lauw, HW, Aumüller, M & Nitta, N 2020, Reproducibility Companion Paper: Visual Sentiment Analysis for Review Images with Item-Oriented and User-Oriented CNN. i MM '20: Proceedings of the 28th ACM International Conference on Multimedia. Association for Computing Machinery, s. 4444-4447, International Conference on Multimedia, 12/10/2020. https://doi.org/10.1145/3394171.3414813

Reproducibility Companion Paper: Visual Sentiment Analysis for Review Images with Item-Oriented and User-Oriented CNN. / Truong, Quoc-Tuan; Lauw, Hady W; Aumüller, Martin et al.
MM '20: Proceedings of the 28th ACM International Conference on Multimedia. Association for Computing Machinery, 2020. s. 4444-4447.

Publikation: Konference artikel i Proceeding eller bog/rapport kapitel › Konferencebidrag i proceedings › Forskning › peer review

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T1 - Reproducibility Companion Paper: Visual Sentiment Analysis for Review Images with Item-Oriented and User-Oriented CNN

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AU - Nitta, Naoko

N1 - Conference code: 28

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N2 - We revisit our contributions on visual sentiment analysis for online review images published at ACM Multimedia 2017, where we develop item-oriented and user-oriented convolutional neural networks that better capture the interaction of image features with specific expressions of users or items. In this work, we outline the experimental claims as well as describe the procedures to reproduce the results therein. In addition, we provide artifacts including data sets and code to replicate the experiments.

AB - We revisit our contributions on visual sentiment analysis for online review images published at ACM Multimedia 2017, where we develop item-oriented and user-oriented convolutional neural networks that better capture the interaction of image features with specific expressions of users or items. In this work, we outline the experimental claims as well as describe the procedures to reproduce the results therein. In addition, we provide artifacts including data sets and code to replicate the experiments.

KW - Visual Sentiment Analysis

KW - Convolutional Neural Networks

KW - Online Review Images

KW - Experimental Reproducibility

KW - Data Sets and Code

U2 - 10.1145/3394171.3414813

DO - 10.1145/3394171.3414813

M3 - Article in proceedings

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Reproducibility Companion Paper: Visual Sentiment Analysis for Review Images with Item-Oriented and User-Oriented CNN

Abstract

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