Ulster University Logo

NewsViz: emotional visualization of news stories

Hanser, E, McKevitt, P, Lunney, TF and Condell, J (2010) NewsViz: emotional visualization of news stories. In: Proc. of the NAACL-HLT Workshop on Computational Approaches to Analysis and Generation of Emotion in Text, Millennium Biltmore Hotel, Los Angeles, CA, USA. Association for Computational Linguistics (ACL). 6 pp. [Conference contribution]

PDF - Published Version

URL: http://www.aclweb.org/anthology/W10-0215


The NewsViz system aims to enhance news reading experiences by integrating 30 seconds long Flash-animations into news article web pages depicting their content and emotional aspects. NewsViz interprets football match news texts automatically and creates abstract 2D visualizations. The user interface enables animators to further refine the animations.Here, we focus on the emotion extraction component of NewsViz which facilitates subtle background visualization. NewsViz detects moods from news reports. The original text is part-of-speech tagged and adjectives and/or nouns, the word types conveying most emotional meaning, are filtered out and labeled with an emotion and intensity value. Subsequently reoccurring emotions are joined into longer lasting moods and matched with appropriate animation presets. Different linguistic analysis methods were tested on NewsViz: word-by-word, sentence-based and minimum threshold summarization, to find a minimum number of occurrences of an emotion in forming a valid mood. NewsViz proved to be viable for the fixed domain of football news, grasping the overall moods and some more detailed emotions precisely. NewsViz offers an efficient technique to cater for the production of a large number of daily updated news stories. NewsViz bypasses the lack of information for background or environment depiction encountered in similar applications.Further development may refine the detection of emotion shifts through summarization with the full implementation of football and common linguistic knowledge.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Faculty of Arts
Faculty of Arts > School of Creative Arts and Technologies
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:21219
Deposited By: Professor Paul McKevitt
Deposited On:06 Mar 2012 09:53
Last Modified:09 Dec 2015 11:02

Repository Staff Only: item control page