Study On The Information Visualization Model Of Special News Texts Set

With the fast development of network technology, Internet network has become an important part of people's learning, life and entertainment. Accessing to the internet network, people will find many kinds of news, which is listed in the form of texts mostly, and couldn't find the useful information to them quickly from the random information. After studying the theory of information visualization and complex network,the paper proposes a information visualization model of special news texts set, associating the news elements'characteristic and users'information needs. Then, the paper visualizes the Wenchuan earthquake reconstruction news texts set on Sina as an example. The paper achieves the research results listed as below: First, after studying the theory of news'elements, information visualization, complex network, texts'digging, corporative broad network and etc., the paper proposes a information visualization model of special news texts set, associating users'information needs and basing on the theory of Stuart K. Card and time wall model. Then, the paper formalizes the model's elements.Second, the paper explains the concept of the granularity of news texts'keywords, and narrates the principles and methods of news texts'keywords'selection. Regarding every keyword of the news'texts as a project, the paper illuminates the association rules of keywords by using the corporative broad network.Third, the paper distills the keywords of Wenchuan earthquake reconstruction news texts set on Sina. Then, it processes them by using concept hierarchy theory on the basis of the keywords'granularity and forms the keywords'database. Finally, it constructs the association matrix by using Excel on the basis of association rules.Fourth, the paper visualizes the association of Wenchuan earthquake reconstruction news texts set by using Ucinet on the basis of association matrix and analyses these results.Fifth, the paper analyses the change of Wenchuan earthquake reconstruction news texts set. Then, it proposes the concept of event attention-getting degree, analyses the change of all events keywords'attention-getting degree and of primary events keywords'attention-getting degree.