An Automated Approach to Investigating the Online Media Coverage of U.S. Presidential Elections

Abstract

ABSTRACT. This paper presents the U.S. Election 2004 Web Monitor, a public Web portal that captured trends in political media coverage before and after the 2004 U.S. presidential election. Developed by the authors of this article, the webLyzard suite of Web mining tools provided the required functionality to aggregate and analyze about a half-million documents in weekly intervals. The study paid particular attention to the editorial slant, which is defined as the quantity and tone of a Web site's coverage as influenced by its editorial position. The observable attention and attitude toward the candidates served as proxies of editorial slant. The system identified attention by determining the frequency of candidate references and measured attitude towards the candidate by looking for positive and negative expressions that co-occur with these references. Keywords and perceptual maps summarized the most important topics associated with the candidates, placing special emphasis on environmental issues. KEYWORDS. U.S. presidential elections, media monitoring, Web mining, natural language processing, semantic orientation, keyword analysis Arno Scharl is the Vice President of MODUL University Vienna where he also heads the Department of New Media Technology (www.modul.ac.at/nmt). Prior to this appointment, he was a Key Researcher at the Austrian Competence Center for Knowledge Management, held professorships at Graz University of Technology and the University of Western Australia, and had joined Curtin University of Technology and the University of California at Berkeley as a Visiting Fellow. His current research projects focus on the integration of semantic and geospatial technology, human-computer interaction, computer-mediated collaboration, ontology learning, and the various aspects of environmental online communication.Albert Weichselbraun is an Assistant Professor at the Department of Information Systems and Operations at Vienna University of Economics and Business Administration (ai.wu-wien.ac.at). After completing two Master's degrees in Economics and Chemical Engineering, his doctoral thesis focused on ontology-based text classification. Dr. Weichselbraun leads the technical development of webLyzard (www.webLyzard.com) and the IDIOM Project (www.idiom.at) with a special focus on the analytical methods involved. His current research focuses on ontology evolution and learning, text mining and the application of semantic technologies to information retrieval.

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