基于深度人工智能研究社交媒体图像对用户对社会政治事件的情绪的影响
Nafiseh Jabbari Tofighi1, Reda Alhajj1,2,3
1Department of Computer Engineering, Istanbul Medipol University, Istanbul, Turkey.
PloS one
|July 30, 2025
概括
社交媒体图像显著影响公众对社会政治事件的情绪. 这项研究发现,在各种运动中,视觉内容和用户意见之间存在强烈的正相关性,突出显示图像.
科学领域:
- 计算社会科学 计算社会科学
- 媒体研究 媒体研究
- 人工智能的人工智能
背景情况:
- 社交媒体平台是信息传播和公共话语的主要道.
- 视觉内容在在线沟通和论形成中发挥着越来越重要的作用.
- 了解视觉媒体对公众情绪的影响对于分析社会政治动态至关重要.
研究的目的:
- 研究社交媒体视觉内容对有关社会政治事件的用户情绪的影响.
- 量化各种社会运动中图像和论之间的相关性.
- 发展对视觉元素如何塑造人们对社会政治问题的态度的更深入的理解.
主要方法:
- 分析与社会政治事件相关的社交媒体帖子 (标签,关键词,图片,评论).
- 应用先进的机器学习和深度学习技术来分析文本数据的情感分析.
- 相关性分析以确定视觉内容与用户表达的情绪之间的关系.
主要成果:
- 在视觉内容和跨运动的公众情绪之间始终观察到强烈的正相关性.
- 反战示威活动显示了最高的相关性 (PLCC:0.709,SROCC:0.723).
- 气候变化抗议活动表现出最低的相关性 (PLCC:0.531,SROCC:0.611),PLCC的总体范围为0.615-0.709,SROCC的范围为0.611-0.723.
结论:
- 社交媒体上的视觉内容显著塑造了用户情绪和公众对社会政治事件的看法.
- 这些发现强调了图像在影响人们对社会和政治运动的态度方面的力量.
- 开发的数据集和方法提供了对在线意见动态有价值的见解.
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