Exploring entity sentiments on AI image generator technology: Analysis of DeviantArt forum comments

Luo, Manman; Lee, Hyun Seung

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https://hdl.handle.net/2142/122829 Copy

Description

Title

Exploring entity sentiments on AI image generator technology: Analysis of DeviantArt forum comments

Author(s)

• Luo, Manman
• Lee, Hyun Seung

Issue Date

2024-03-20

Keyword(s)

• Entity Sentiment Analysis
• AI Image Generator
• Data Analysis

Abstract

Entity sentiment analysis examines opinions expressed towards a specific en-tity in documents. Most current entity sentiment analysis studies focus on en-tities such as products and restaurants. The development of AI image genera-tor technology recently brought technological innovation in the art creation process. Understanding sentiments of users who are interested in art creation associated with AI image generator technology is crucial for both the AI technology developers and the users themselves. This study analyzes 1,424 comments from DeviantArt website forum to understand sentiments of the website users towards AI image generator technology and the key aspects that contribute to their sentiments. The preliminary result revealed that senti-ments were primarily expressed towards three entities: AI-generated artwork, AI image generator technology itself, and creators utilizing AI image genera-tors. Notably, negative sentiments predominantly were expressed towards AI-generated artworks and creators using AI image generators, comprising 67.4% of negative sentiments, while positive sentiments were most pro-nounced for AI image generator technology itself, accounting for 28.6%. Further analysis identified aspects that contributed to the positive and nega-tive sentiments towards different entities. The preliminary findings showed multifaceted nature of entity sentiments within AI image generator technolo-gy context.

Publisher

iSchools

Series/Report Name or Number

iConference 2024 Proceedings

Type of Resource

Other

Language

eng

Handle URL

https://hdl.handle.net/2142/122829

Copyright and License Information

Copyright 2024 is held by Manman Luo and Hyun Seung Lee. Copyright permissions, when appropriate, must be obtained directly from the authors.

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