摘要翻译:
大众传媒的消费者必须有一个全面、平衡和多元的新闻选择,以获得无偏见的视角;但实现这一目标可能非常具有挑战性、费力和耗时。随着时间的推移,新闻故事的发展,它的一致性,以及媒体不同程度的报道,是一个有责任心的读者必须克服的挑战,以减轻偏见。在本文中,我们提出了一个智能代理框架,目前有助于分析萨尔瓦多在线新闻的主要来源。我们展示了如何将现有的文本分析工具和Web2.0技术与最少的人工干预相结合,以帮助个人进行合理的决策过程,同时让媒体机构对他们的工作负责。
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英文标题:
《Alleviating Media Bias Through Intelligent Agent Blogging》
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作者:
Ernesto Diaz-Aviles
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最新提交年份:
2009
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分类信息:
一级分类:Computer Science 计算机科学
二级分类:Artificial Intelligence 人工智能
分类描述:Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域,除了视觉、机器人、机器学习、多智能体系统以及计算和语言(自然语言处理),这些领域有独立的学科领域。特别地,包括专家系统,定理证明(尽管这可能与计算机科学中的逻辑重叠),知识表示,规划,和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要:
Consumers of mass media must have a comprehensive, balanced and plural selection of news to get an unbiased perspective; but achieving this goal can be very challenging, laborious and time consuming. News stories development over time, its (in)consistency, and different level of coverage across the media outlets are challenges that a conscientious reader has to overcome in order to alleviate bias. In this paper we present an intelligent agent framework currently facilitating analysis of the main sources of on-line news in El Salvador. We show how prior tools of text analysis and Web 2.0 technologies can be combined with minimal manual intervention to help individuals on their rational decision process, while holding media outlets accountable for their work.
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PDF链接:
https://arxiv.org/pdf/0902.0798