Title | Extraction of characteristic description for analyzing news agencies |
Publication Type | Journal Article |
Year of Publication | 2010 |
Authors | Ishida, S, Ma, Q, Yoshikawa, M |
Journal | Journal of Digital Information Management |
Volume | 8 |
Issue | 6 |
Pagination | 349 - 354 |
Date Published | 2010 |
Keywords | News agencies, News analysis, Text characteristics, Text description, Word frequency analysis |
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. |
URL | http://www.scopus.com/inward/record.url?eid=2-s2.0-79960674167&partnerID=40&md5=ecab8d077da920129f8c0e884ea0c5b4 |