submitted to 11th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2014, University Park, PA, USA
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.To access the complete article, please fill in the form below.
Your name and e-mail are going to be used in order to send you only the research file and not any additional commercial material. You can change your mind at any time by clicking the unsubscribe in the footer of the email that you receive from us, or by contacting dataprotectionofficer@hensoldt-analytics.com. Please find out about your rights and choices and how we use your information in our Privacy Policy.
