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

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › 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.

Original language	English
Title of host publication	MM '20: Proceedings of the 28th ACM International Conference on Multimedia
Publisher	Association for Computing Machinery
Publication date	2020
Pages	4444-4447
DOIs	https://doi.org/10.1145/3394171.3414813
Publication status	Published - 2020
Event	International Conference on Multimedia - Duration: 12 Oct 2020 → … Conference number: 28

Conference

Conference	International Conference on Multimedia
Number	28
Period	12/10/2020 → …

Keywords

Visual Sentiment Analysis
Convolutional Neural Networks
Online Review Images
Experimental Reproducibility
Data Sets and Code

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10.1145/3394171.3414813

ACM_MM_2020_Repro_Paper29061Proof, 3.03 MB

Cite this

@inproceedings{330acc265c6347608d2b50b4fa5d2ee1,

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, 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. in MM '20: Proceedings of the 28th ACM International Conference on Multimedia. Association for Computing Machinery, pp. 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. p. 4444-4447.

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › 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

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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

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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BT - MM '20: Proceedings of the 28th ACM International Conference on Multimedia

PB - Association for Computing Machinery

T2 - International Conference on Multimedia

Y2 - 12 October 2020

ER -

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

Abstract

Conference

Keywords

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