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<Paper uid="W06-1706">
  <Title>Web Coverage of the 2004 US Presidential Election</Title>
  <Section position="3" start_page="1" end_page="35" type="metho">
    <SectionTitle>
2 Impact of New Media on Public
Opinion
</SectionTitle>
    <Paragraph position="0"> Representative democracy offers significant possibilities for exploiting information networks (Holmes 2002), but there is little agreement on their specific impact. Proponents praise the networks' potential to increase the accessibility of information, encourage participatory decisionmaking, and facilitate communication with policy officials and like-minded citizens. From an advocate's perspective, disseminating environmental information via the Internet, directly or through news media, creates awareness by emphasizing the interdependency of ecological, economic, and social issues (Scharl 2004).</Paragraph>
    <Paragraph position="1"> Critics portray McLuhan's global village as a &amp;quot;neofeudal manor with highly fortified and opulent castles (centers of industrial, financial, and media power) surrounded by vast hinterlands of working peasants clamoring for survival and recognition&amp;quot; (Tehranian 1999, p55f.). They argue that information networks polarize society by linking groups with similar political views. Lowoverhead forms of personal publishing (Gruhl, Guha et al. 2004) such as Web logs and online discussion forums, for example, might reinforce a group's world view and shun opposing opinions. This reinforcement, amplified by biased media coverage, polarizes groups (Sunstein 2004) and degrades the climate of public discourse (Horrigan, Garrett et al. 2004).</Paragraph>
    <Paragraph position="2"> The communication strategies of news media, corporations and advocacy organizations affect democratic processes. Yet they only condition, rather than determine these processes. Assuming  deterministic effects of information networks neglects the world's ambivalence, and results in conflicting claims regarding the networks' political impact. News media are free to choose which candidate to emphasize, and how to interpret current events (Wayne 2001). Most Americans prefer unbiased news sources (Horrigan, Garrett et al. 2004), but Web sites tend to reflect their owners' political agenda, and thus contribute to a polarized electorate.</Paragraph>
    <Paragraph position="3"> While a narrow margin decided the last two US presidential elections, differences in the candidates' positions became more pronounced in 2004, and the political deliberation more partisan. Partisans tend to perceive mass media content as biased against their point of view. Explanations for this hostile media effect range from selective recall (preferentially remembering hostile content), selective categorization (perceiving the same content differently) and conflicting standards (considering hostile content as invalid or irrelevant). Recent research suggests that selective categorization best explains hostile media effects (Schmitt, Gunther et al. 2004).</Paragraph>
  </Section>
  <Section position="4" start_page="35" end_page="36" type="metho">
    <SectionTitle>
3 Methodology
</SectionTitle>
    <Paragraph position="0"> Given an increasingly polarized electorate and hostile media effects that impair partisans' judgment, analyzing political Web content requires objective measures of organizational bias. Yet the volume and dynamic nature of Web documents complicate testing the assumption of organizational bias. To address this challenge, the US Election 2004 Web Monitor sampled 1,153 Web sites in weekly intervals. The project drew upon the Newslink.org, Kidon.com and ABYZ-NewsLinks.com directories to compile a list of 42 US news organizations and 72 international sites from four other English-speaking countries: Canada, United Kingdom, Australia and New Zealand. To extend the study, the sample included the Web sites of the Fortune 1000 (the largest US corporations ranked by revenue) and 39 environmental organizations.</Paragraph>
    <Paragraph position="1"> Considering the dynamics of Web content in general and presidential campaigns in particular (Howard 2003), a crawling agent mirrored these Web sites by following their hierarchical structure until reaching 50 megabytes of textual data for news media, and 10 megabytes for commercial and advocacy sites. These limits help compare sites of heterogeneous size, and reduce the dilution of top-level information by content in lower hierarchical levels (Scharl 2000).</Paragraph>
    <Paragraph position="2"> Such a collection of recorded content used for descriptive analysis is often referred to as corpus. This research investigated and visualized regularities in three groups of Web sites by applying methods from corpus linguistics and textual statistics (Biber, Conrad et al. 1998; Lebart, Salem et al. 1998; McEnery and Wilson 2001).</Paragraph>
    <Paragraph position="3"> Quantitative textual analysis of Web documents necessitates three steps in order to yield a useful machine-readable representation (Lebart, Salem et al. 1998): * The first step converts hypertext documents into plain text - i.e., processing the gathered data and eliminating markup code and scripting elements.</Paragraph>
    <Paragraph position="4"> * The second step segments the textual chain into minimal units by removing coding ambiguities such as punctuation marks, the case of letters, hyphens, or points in abbreviations. In the case of the Election Monitor, this process yielded about half a million documents each week, comprising about 125 million words in 10 million sentences. The system then identified and removed redundant segments such as headlines and news summaries, whose appearance on multiple pages distorts frequency counts.</Paragraph>
    <Paragraph position="5"> * The third step, identification, groups identical units and counts their occurrences - i.e., creating an inventory of words, or multi-word units of meaning (Danielsson 2004).</Paragraph>
    <Paragraph position="6"> The frequency of candidate references presented in the following section is based on such an exhaustive index, which often uses decreasing frequency of occurrence as the primary sorting criterion and lexicographic order as the secondary criterion.</Paragraph>
    <Paragraph position="7"> Frequency of References (Attention) Media coverage and public recognition go handin hand (Wayne 2001), documented by strong correlations between the attention of news media and both public salience and attitudes toward presidential candidates (Kiousis and McCombs 2004). The US Election 2004 Web Monitor calculated attention as the relative number of references to a candidate. To determine references to candidates or environmental topics, a pattern matching algorithm considered common term inflections while excluding ambiguous expressions. Only identifying occurrences of george w. bush, for example, ignores equally valid references to president bush and george walker bush.  Yet a general query for bush fails to distinguish the president's last name from references to wilderness areas or woody perennial plants.</Paragraph>
    <Paragraph position="8"> After the election, nearly two thirds of the media references mentioned George W. Bush and Dick Cheney, up four percentage points from the preceding week (Figure 1). About one third reported on John Kerry and John Edwards. The Fortune 1000 companies and environmental organizations dedicated over 80 percent of their coverage to the president and his running mate.</Paragraph>
    <Paragraph position="9"> Across all three samples, the independent team of Ralph Nader and Peter Camejo garnered less than five percent of the attention.</Paragraph>
  </Section>
  <Section position="5" start_page="36" end_page="38" type="metho">
    <SectionTitle>
4 Semantic Orientation of References
</SectionTitle>
    <Paragraph position="0"> (Attitude) Calculating the frequency of candidate references disregards their context (Yi, Nasukawa et al. 2003). Therefore, the system also tracked attitude, the semantic orientation of a sentence towards the candidates (Scharl, Pollach et al.</Paragraph>
    <Paragraph position="1"> 2003).</Paragraph>
    <Paragraph position="2"> The algorithm calculated the distance between the target word and 4,400 positive and negative words from the General Inquirer's tagged dictionary (Stone, Dunphy et al. 1966). Reverse lemmatization added about 3,000 terms to the dictionary by considering plurals, gerund forms, past tense suffixes and other syntactical variations (e.g. manipulate - manipulates, manipulating, manipulated).</Paragraph>
    <Paragraph position="3"> Two sentences from news media on November 4 exemplify positive vs. negative coverage of a topic (zero indicates neutral coverage). The underlined words, identified in the tagged dictionary, were used to compute the semantic orientation of sentences with oil price references.  * &amp;quot;US stocks rallied Wednesday, boosted by shares of health and defence companies that are seen benefiting from the re-election of President George W. Bush, but higher oil prices checked advances&amp;quot; (NEW ZEALAND HERALD).  |(+ 4.09) * &amp;quot;The dollar hit its lowest level in more than eight months against the Euro Thursday, falling sharply on worries about the economic effects of rising oil prices and expectations of continued trade and budget deficits in President Bush's second term&amp;quot; (ST. PETERS-BURG TIMES).  |(- 4.03)  Initially, media coverage favored the Republicans, although the Democratic contenders gained ground in September 2004 (Figure 2). Kerry's performance in the first televised debate accelerated these gains in media attitude, followed by a tight race between the two teams in the four weeks preceding the election. The re-election of George W. Bush again widened the gap, understandably considering the positive connotation of terms such as winning and victory.</Paragraph>
    <Paragraph position="4">  towards the US presidential candidates between September and November 2004 Compared to the news media, the other two samples showed more bias. Fortune 1000 companies presented the Republican candidates most favorably, while environmental organizations tended to criticize the environmental record of George W. Bush - particularly abandoning the Kyoto Treaty ratification, and reducing air pollution controls through the Clear Skies Act. To investigate these claims, separate analyses related environmental issues to Web sites and candidates. In terms of energy policy, for example, one such analysis investigated Web coverage of renewable energy, fossil fuels and nuclear power - a crucial aspect in light of recent geopolitical events and the global environmental impact of US energy policy decisions. On a micro level, the Election Monitor's Web site allowed users to list sentences containing both candidate references and energy-related terms, and sort these sentences by semantic orientation.</Paragraph>
    <Paragraph position="5">  On a macro level, the perceptual map of Figure 3 summarizes the prominence of energy terms among international media sites. The diagram is based on correspondence analysis, which processed the table of term frequencies as of 17 September 2004. Related concepts and organizations appear close to each other in the computationally created two-dimensional space. The circular and rectangular markers represent energy-related concepts and media sites, respectively. When interpreting the diagram it is important to note that term frequency, not media attitude, determines the position of data points.</Paragraph>
    <Paragraph position="6"> The distribution of data points shows a tripolar structure: fossil fuels in the upper left, renewable energies in the upper right, and nuclear energy near the bottom of the diagram. The diagram illustrates news organizations with distinct content - Fox News and Time, for example, with their coverage of nuclear energy and wind energy, respectively. Geographic differences are also apparent. Fossil fuels align with many Australian media, reflecting the country's richness in mineral resources. Most business publications congregate around fossil fuels as well, Business Week being a notable exception.</Paragraph>
    <Paragraph position="7"> References to fuel cells and hydrogen often appear together. Their potential use with various energy sources explains their slightly isolated position. Combining the energy carrier hydrogen with fuel cell conversion technology yields high efficiency and low pollution in applications such as zero-emission vehicles, energy storage and portable electronics.</Paragraph>
  </Section>
  <Section position="6" start_page="38" end_page="38" type="metho">
    <SectionTitle>
5 Refining Attitude Measures
</SectionTitle>
    <Paragraph position="0"> Lexically identical occurrences with differing or even opposite meanings, depending on the context, represent an inherent problem of automatically determining the semantic orientation of Web content (Wilson, Wiebe et al. 2005). Word-sense ambiguity, for example, is a common phenomenon. Arrest as a noun takes custody by legal authority, for example, while arrest as a verb could mean to catch or to stop. Similarly, in economics the noun good refers to physical objects or services. As an adjective, good assigns desirable or positive qualities. Part of speech tagging considers this variability by annotating Web content and distinguishing between nouns, verbs, adjectives and other parts of speech.</Paragraph>
    <Paragraph position="1"> Besides differences in word-sense, analysts also encounter other types of ambiguities - e.g., idiomatic versus non-idiomatic term usage, or various pragmatic ambiguities involving irony, sarcasm, and metaphor (Wiebe, Wilson et al.</Paragraph>
    <Paragraph position="2"> 2005).</Paragraph>
    <Paragraph position="3"> Given the considerable size of the corpus and the need to publish results in weekly intervals, the system was designed to maximize throughput in terms of documents per second. A comparably simple approach restricted to single words and without sentence parsing ensured the timely completion of the weekly calculations.</Paragraph>
    <Paragraph position="4"> Planned extensions will add multiple-word combinations to the tagged dictionary to discern morphologically similar but semantically different terms such as fuel cell and prison cell. Yet the lexis of Web content only partially determines its semantic orientation, despite using multi-word units of meaning instead of single words or lemmas (Danielsson 2004). Prototypical implementations such as the OpinionFinder (Wilson, Hoffmann et al. 2005) have demonstrated that grammatical parsing can successfully address this limitation by identifying ambiguities and capturing meaning-making processes at levels beyond lexis - correctly identifying, annotating and evaluating nested expressions of various complexity (Wiebe, Wilson et al. 2005).</Paragraph>
  </Section>
  <Section position="7" start_page="38" end_page="39" type="metho">
    <SectionTitle>
6 Keyword Analysis
</SectionTitle>
    <Paragraph position="0"> Keyword Analysis locates words in a given text and compares their frequency with a reference distribution from a usually larger corpus of text. To complement measures of attention and attitude towards a candidate, keywords grouped by political party and geographic region highlighted issues associated with each candidate.</Paragraph>
    <Paragraph position="1"> For that purpose, the system compared the term frequencies in sentences mentioning a candidate (target corpus) with the term frequencies in the entire sample of 1,153 Web sites from media organizations, the Fortune 1000, and environmental organizations (reference corpus).</Paragraph>
    <Paragraph position="2"> The results suggest that personalities and campaign events dominate over substantive policy issues, a possible reason for the average voter's limited interest in and knowledge about political processes (Wayne 2001). Table 1 summarizes keywords that US news media associated with the presidential candidates and their running mates in the week preceding the election. The list ranks keywords by decreasing significance, computed via a chi-square test with Yates' correction for continuity. To avoid outliers, the list only considers nouns with at least 100 occurrences in the reference corpus.</Paragraph>
    <Paragraph position="3">  George Bush Dick Cheney John Kerry John Edwards Ralph Nader Peter Camejo debate lynne nominee carolina ballot opinion challenger daughter vietnam running percent running iraq halliburton challenger debate candidacy respondents gore debate debate nominee advocate electors war lesbian massachusetts gephardt party commonwealth speech rumsfeld nomination iowa supreme ballot nominee pensacola war ashton gore endorsement guard rally rival optimism petition nominee hussein wyoming speech north court battleground terrorism wilmington clinton trail pennsylvania balance Table 1. Keywords of US news media (Oct 27, 2004) The keywords document that the television debates between the major candidates and their running mates remained topical up until the election. The war on terrorism and persistent problems in dealing with insurgents in Iraq dogged Bush, while his challenger's service in Vietnam continued to occupy the media.</Paragraph>
    <Paragraph position="4"> Vice-President and former CEO of Halliburton Cheney was busy, traveling to Pensacola, Wyoming and Wilmington and addressing media questions about his wife Lynne and his lesbian daughter Mary. A speech of former President Clinton, joining Kerry in his first appearance after undergoing heart surgery, reminded undecided voters of more prosperous times. At the same time, actor Ashton Kutcher hit the campaign trail for John Edwards, senator from North Carolina and running mate of John Kerry.</Paragraph>
    <Paragraph position="5"> Although the Supreme Court refused his candidacy in Pennsylvania over invalid nominating petitions, Ralph Nader was on the ballot in more than 30 states. Articles about him reiterated controversies over vote-splitting in the previous election, and the Supreme Court's decision to end the Bush vs. Gore recounts in December 2000.</Paragraph>
  </Section>
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