论文标题
“如果您建造他们将会来”：自动识别新闻利益相关者，以检测新闻报道中的政党偏好
'If you build they will come': Automatic Identification of News-Stakeholders to detect Party Preference in News Coverage
论文作者
论文摘要
新闻文章中提到的不同利益相关者的覆盖范围显着影响有关新闻发布者的倾斜或极性检测。例如，亲政府的媒体将向政府利益相关者提供更多的报道，以提高他们对新闻受众的访问性。相比之下，反政府新闻机构将更多地关注对手利益相关者的观点，以告知读者政府政策的缺点。在本文中，我们解决了利益相关者从新闻文章中提取的问题，从而确定了新闻报道中存在的固有偏见。在多主题新闻方案中确定潜在的利益相关者是具有挑战性的，因为每个新闻主题都有不同的利益相关者。本文提出的研究利用上下文信息和外部知识来确定新闻文章中特定于主题的利益相关者。我们还将顺序增量聚类算法应用于具有相似利益相关者类型的实体。我们对许多国家和国际新闻机构发表的四项印度政府政策进行了所有新闻文章的实验。我们还进一步概括了我们的系统，实验结果表明，提出的模型可以扩展到其他新闻主题。
The coverage of different stakeholders mentioned in the news articles significantly impacts the slant or polarity detection of the concerned news publishers. For instance, the pro-government media outlets would give more coverage to the government stakeholders to increase their accessibility to the news audiences. In contrast, the anti-government news agencies would focus more on the views of the opponent stakeholders to inform the readers about the shortcomings of government policies. In this paper, we address the problem of stakeholder extraction from news articles and thereby determine the inherent bias present in news reporting. Identifying potential stakeholders in multi-topic news scenarios is challenging because each news topic has different stakeholders. The research presented in this paper utilizes both contextual information and external knowledge to identify the topic-specific stakeholders from news articles. We also apply a sequential incremental clustering algorithm to group the entities with similar stakeholder types. We carried out all our experiments on news articles on four Indian government policies published by numerous national and international news agencies. We also further generalize our system, and the experimental results show that the proposed model can be extended to other news topics.
