Sentiment analysis of German social media data for natural disasters
نویسندگان
چکیده
Analysis of social media and traditional media provides significant information to first responders in times of natural disasters. Sentiment analysis, particularly of social media originating from the affected population, forms an integral part of multifaceted media analysis. The current paper extends an existing methodology to the domain of natural disasters, broadens the support of multiple languages and introduces a new manner of classification. The performance of the approach is evaluated on a recently collected dataset manually annotated by three human annotators as a reference. The experiments show a high agreement rate between the approach taken and the annotators. Furthermore, the paper presents the initial application of the resulting technology and models to sentiment analysis of social media data in German, covering data collected during the Central European floods of 2013.
منابع مشابه
Natural Language Processing for Health and Social Media Authors:
Intro Social media, such as Twitter, has shown great potential to analyze real world events, such as politics, product sentiment and natural disasters. In recent years, social media has emerged in the health community, particularly in public health, as a revolutionary data source for a wide range of problems. Vast amounts of naturalistic population data can be collected through social media muc...
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