Search for journalists: New York Times challenge report
Presented at the Workshop on Human-Computer Interaction and Information Retrieval , New Brunswick, NJ
We investigate how a user-centred design to search can improve the support of user tasks specific to journalism. Illustrated by example information needs, sampled from our own exploration of the New York Times annotated corpus, we demonstrate how domain specific notions rooted in a field theory of journalism can be transformed into effective search strategies. We present a method for search-context aware classification of authorities, witnesses, reporters and columnists. A first search strategy supports the journalistic task of investigating the trustworthiness of a news source, whereas the second search strategy supports assessments of the objectivity of an author. In principle, these strategies can exploit the semantic annotations the corpus; however, based on our preliminary work with the corpus, we conclude that straightforward full-text search is still a crucial component of any effective search strategy, as only recent articles are annotated, and annotations are far from complete.
|Keywords||journalism, faceted search, interactive IR|
|THEME||Information (theme 2)|
|Conference||Workshop on Human-Computer Interaction and Information Retrieval|
Boscarino, C, de Vries, A.P, & Alink, W. (2010). Search for journalists: New York Times challenge report. In Proceedings of the Fourth Workshop on Human-Computer Interaction and Information Retrieval. MSFT research.