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A Cross-Media Method of Stakeholder Extraction for News Contents Analysis

机译:利益相关者抽取的跨媒体方法用于新闻内容分析

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We are studying contents analysis of multimedia news as a solution to the issue of bias, which multimedia news, as a reflection of the real world, is also facing. For the contents analysis, we use a stakeholder model representing descriptions of different stakeholders, which are defined as the main participants in an event. In this paper, we propose a method of detecting stakeholders as the core component of the stakeholder-oriented analysis. In our work, a stakeholder is assumed to appear in the video clips and be mentioned in the closed captions frequently. Given a series of video clips and their closed captions reporting the same event, we extract stakeholder candidates from both textual and visual descriptions. After that, we calculate the degree of exposure for each candidate to identify stakeholders. We also present experimental results that validate our method.
机译:我们正在研究多媒体新闻的内容分析,以解决偏见问题,而多媒体新闻作为现实世界的反映也正面临着这一问题。对于内容分析,我们使用利益相关者模型来表示不同利益相关者的描述,这些利益相关者的定义被定义为事件的主要参与者。在本文中,我们提出了一种检测利益相关者的方法,该方法是利益相关者导向分析的核心组成部分。在我们的工作中,假定利益相关者出现在视频剪辑中,并且经常在隐藏式字幕中被提及。给定一系列视频片段及其报道同一事件的隐藏式字幕,我们从文本和视觉描述中提取利益相关者候选者。此后,我们计算每个候选人的暴露程度以识别利益相关者。我们还提供了验证我们的方法的实验结果。

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