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Is News Really Pessimistic? Sentiment Analysis of Chilean Online Newspaper Headlines

机译:新闻真的很悲观吗?智利在线报纸头条的情感分析

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Objectives: This paper explores the popular belief that all news is bad news. Many claim not to read newspapers to avoid knowing about the worst of our society. We want tear down the myth by applying a Sentiment Analysis (SA) approach. Method/Analysis: This work applies sentiment analysis techniques to study the headline bias of online newspapers for the period between March 2014 and April 2015. We analyzed 2953 headlines gathered from five of the most popular Chilean newspapers which are available online and offer RSS feeds. Findings: Our results show a roughly equivalent percentage of positive bias (38%) and negative bias (37%) instances, with 25% of headlines exhibiting a neutral bias. Automatic classification performance is promising, with decent classifier performance and sensitivity, with plenty of room for improvement. Novelty/Improvement: This work also a domain-specific Spanish language tagged corpus was generated as a result of this work, which is a valuable resource for future studies.
机译:目标:本文探讨了所有新闻都是坏消息的普遍观念。许多人声称不读报纸是为了避免了解我们社会的最糟糕状况。我们希望通过应用情感分析(SA)方法来打破神话。方法/分析:这项工作运用情感分析技术研究了2014年3月至2015年4月这段时间在线报纸的标题偏差。我们分析了从5种最受欢迎​​的智利报纸中收集的2953个标题,这些报纸可以在线获得并提供RSS feed。调查结果:我们的结果显示,正面偏见(38%)和负面偏见(37%)的百分比大致相当,其中25%的标题显示中立偏见。自动分类的性能是有希望的,它具有不错的分类器性能和灵敏度,还有很大的改进空间。新颖性/改进:由于这项工作,还生成了具有特定领域西班牙语标记的语料库,这是将来研究的宝贵资源。

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