Indian Journal of Science and Technology
Year: 2018, Volume: 11, Issue: 22, Pages: 1-8
Claudia Martinez-Araneda1 *, Alejandra Segura2 , Christian Vidal-Castro2 andJorge Elgueta2
1 Computer Science Department, Universidad Católica de la Santísima Concepción. Alonso de Ribera 2850, Concepción, Chile; [email protected]
2 Information System Department, Universidad del Bío-Bío, Av. Casilla 5-C, Collao 1202, Concepción, Chile; [email protected], [email protected], [email protected]
*Author for correspondence
Computer Science Department, Universidad Católica de la Santísima Concepción. Alonso de Ribera 2850, Concepción, Chile; [email protected]
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.
Keywords: Bias, Sentiment Analysis, Subjectivity Analysis, Text Mining
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