NewsViz: Emotional Visualization of News Stories

Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text, pages 125–130, Los Angeles, California, June 2010. c⃝2010 Association for Computational Linguistics NewsViz: Emotional Visualization of News Stories Eva Hanser, Paul Mc Kevitt, Tom Lunney and Joan Condell School of Computing & Intelligent Systems Faculty of Computing & Engineering University of Ulster, Magee Derry/Londonderry, BT48 7JL Northern Ireland hanser-e@email.ulster.ac.uk, {p.mckevitt, tf.lunney, j.condell}@ulster.ac.uk Abstract 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 en- ables animators to further refine the anima- tions. Here, we focus on the emotion extrac- tion component of NewsViz which facilitates subtle background visualization. NewsViz de- tects moods from news reports. The origi- nal text is part-of-speech tagged and adjec- tives and/or nouns, the word types convey- ing 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. Differ- ent 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 emo- tion 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 com- mon linguistic knowledge. 1 Introduction News reports are regarded as objective facts, com- monly delivered in an objective, unbiased manner and represented in a neutral and formal format: typ- ically a static headline, a summarizing paragraph with one image and eventually the body text with one to three more images. Even though reporters find the content of news stories worth mentioning for emotional reasons and the content often affects read- ers emotionally, story brevity, scarce background in- formation and poor combination of visual and verbal information hinders learning and feeling by view- ers. In order to reach the audience emotionally, to educate and to entertain, emphasis on visual ele- ments is important as they tend to be more memo- rable than verbal ones. The emphasis of NewsViz lies on expression, impacting on the reader’s under- standing of the article and making it more memo- rable. The software prototype, NewsViz, automat- ically creates animations from news articles. Ab- stract design elements show emotions conveyed in the stories. The main objective of NewViz remains information provision and thus our focus is emotion extraction which is universally applicable and with- out opinion bias. NewsViz is an efficient software tool for designers to be able to build daily …

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