@article {257,
	title = {Extraction of characteristic description for analyzing news agencies},
	journal = {Journal of Digital Information Management},
	volume = {8},
	year = {2010},
	note = {Export Date: 10 July 2014},
	month = {2010},
	pages = {349 - 354},
	abstract = {News agencies report news from different viewpoints and with different writing styles and these differences often ap pear in their article descriptions. We propose a method to extract characteristic descriptions on certain entities (persons, locations, organizations, etc.) in news agency articles. For a given entity, a description is one tuple (called an SVO tuple) consisting of that entity and other words or phrases appearing in the same sentence on the basis of their SVO (Subject (S), Verb (V) and Object (O)) roles. We extract characteristic descriptions of entities by computing the fre quency and inverse agency frequency of each description. By arranging characteristic descriptions chronologically, we were able to ascertain the left-or right-leanings of news agencies and how those leanings varied with the passage of time.},
	keywords = {News agencies, News analysis, Text characteristics, Text description, Word frequency analysis},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-79960674167\&partnerID=40\&md5=ecab8d077da920129f8c0e884ea0c5b4},
	author = {Ishida, S. and Ma, Q. and Yoshikawa, M.}
}
