Abstract
Conventional pos-neg model of sentiment analysis primarily for review documents is inappropriate for news articles because of the sentiment diversity of the latter. We design three-dimension sentiments that are more suitable for the analysis of news articles. For a contentious topic, different news websites may have different sentiment tendencies and the tendencies may vary over time. To catch this feature, we construct a sentiment dictionary and develop a system that can extract news articles' sentiments, present sentiment variation over time inside a news website, and compare sentiment correlation between news websites. © 2012 Springer-Verlag.
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CITATION STYLE
Zhang, J., Kawai, Y., Kumamoto, T., Nakajima, S., & Shiraishi, Y. (2012). Diverse sentiment comparison of news websites over time. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7327 LNAI, pp. 434–443). https://doi.org/10.1007/978-3-642-30947-2_48
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