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news because of the profit and growth needs, or renovating the journalism as they put effort to public concerns, the comparison between these two sort of media still worth investigations.
The partisan bias exploration in textual level, words and terms formatting semantic networks would provide different landscape of comparison in the two types of media.
2.3. Media Slant and Bias
Slant or Bias is existed in several aspects in media, not only scholars focused generally on
“media bias”, but also investigated in different scopes such as partisan bias (Merkley, 2019), ideology bias (Jamieson & Cappella, 2008), framing bias (Entman, 2007), and so on. From the past studies, media bias, slant, or partisan bias were in widely discussion (Bourgeois, Rappaz
& Aberer, 2018), and it seemed not attributed to a major theorist (D'Alessio & Allen, 2000).
Scholars proposed their definitions and interpretations on this concept. Media bias is “nothing to do with the honesty or accuracy of the news outlet. Instead, our notion is more like a taste or preference” as Groseclose and Milyo depicted (2005, p. 1204). In Entman’s study (2007), it distinguished “bias” and “slant” differently, while “framing bias” was “consistent patterns in the framing of mediated communication that promote the influence of one side in conflicts over the use of government power” (p. 166), the “slant” was “the framing favors one side over the other in a current or potential dispute.” (p. 165) (Entman, 2007). On the basis of Entman’s definition of “bias” and “slant”, this study would consider “slant” as the major concept, since it is more matched with the context of the study.
Since 1970s to 1990s, slant or bias was widely investigated in newspaper and TV. In recent years, the core definition, measurement or impact of media slant are still diverged
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(Lichter, 2017). As several factors are considered to cause partisan media, to operationalize media bias accurately is not that easy. Several factors were believed by scholars that could affect media slant, such as media’s mediatization, commercial needs, economic marketplace, governmental pressures, public opinions, etc (Gerth & Siegert, 2012; D'Alessio & Allen, 2000;
Lichter, 2017; Groseclose & Mily, 2005). Hopmann et al. (2012) believed that media balance was defined by “political system” and “media routines”. The former involved how the contents cover and treat political actors equally that often occurs in two-party system, and the latter refers to media’s routine news selection based on news values or newsworthiness.
In recent years, some scholars investigated media slant or bias in aspects of economics, proposing economic bias models on the basis of media’s market demand and supply (Gentzkow
& Shapiro, 2010; Lichter, 2017; Gentzkow et al., 2015). Besides, media balance is also affected by sponsors, political institutions, think tanks or specific interest groups (Ferguson, 2016;
Groseclose & Milyo, 2005).
As media slant was believed to affect citizen’s party or position preference (Eberl et al., 2017), the framing of different news media media could explain how media sources select their information and spin an event to the audience (Ferguson, 2016). Therefore, many researchers focused on the content-based analysis, that the framing bias research is the most, or the effects of the news coverage analysis.
Despite the fact that media slant or bias might be attributed to complex factors, from aspects of media contents three sorts bias were developed. Previous scholars (D'Alessio &
Allen, 2000; Eberl et al., 2017) categorized three common sorts of media bias “visibility bias (coverage bias)”, “tonality bias (statement bias)”, and “agenda bias (gatekeeping or selectivity
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bias)". In news outlets, “visibility bias” was treated as a benchmark measured by relative amount of coverage on some politicians or parties (Boomgaarden & Wagner, 2017). Studies partisan balance adopting analysis of visibility bias are believed to be the most, as it is considered straightforward to measure (Hopmann et al., 2012). “Tonality bias” is measured by valences on political parties or actors, evaluating how they are covered, and “agenda bias”
investigated the extent that media highlight specific issues or information in connection with some political actors or parties (Eberl et al., 2017).
Scholars who focused on the media contents conducted content analysis on intensity of campaign and style (Qin, Strömberg & Wu, 2018), agenda setting and framing (Chen et al., 2019; Gerth & Siegert, 2012), or valence of the statements (Rafail & McCarthy, 2018) to measure the slant in news outlets. Chen et al. (2019) compared the haze-related contents on types of media (traditional vs social media) through agenda network analysis, exploring the attributes of haze either reflected threat or efficacy in two types of media.
Gentzkow and Shapiro (2010) proposed a media index to measure political news contents’ attitudes towards Republican or Democrat congress documents. They constructed a new index and compare the phase frequency of newspaper with Republican and Democrat congressional documents, to identify the partisan slant of news media. Another example, Gans and Leigh (2012) also measure news media’s political positions through media mentions of public intellectuals. However, these studies measuring partisan slant only based on frequency of mentions. At this level, they investigated the partisan slant from “visibility bias” aspect, through relative amount of coverage on some politicians or parties (Boomgaarden & Wagner, 2017; Eberl et al., 2017).
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From the aspect of agenda setting or framing, it could compensate for staying at level of frequency. The aspect of “agenda bias”, which measured slant based on agenda level, covering the level of news-story understanding about how journalists or news media selected the issues or concepts (Eberl et al., 2017). For example, Gans and Leigh (2012) coded the political stories on a 5-point scale and calculate the mean score to measure the left-right degree of news media.
Eberl and his colleagues (2017) compared the policy issues portrayed in campaign communications and in media outlets through manual content analysis knowing the universe of news stories. However, many scholars used manual content analysis to measure partisan slant from aspect of agenda setting or framing, in order to understand the news story in news outlets.
In order to fill up the research gap of going beyond the frequency level and simultaneously understanding the selected issues regarding to framing from news media, this research proposed to use semantic network analysis to identify the salient issues, and measure the partisan slant of news media. The semantic analysis based on words and terms mixed the way of investigating media slant through aspects of “visibility bias”, and “agenda bias”
(Boomgaarden & Wagner, 2017). The semantic network analysis involved “visibility bias” as networks are constructed by the frequency of word-occurrence that makes connections; and it involved “agenda bias” as the words provided the salient concepts or issues that communicators put emphais on. Partly based on Gentzkow and Shapiro’s research (2010), this research would also consider contents from two political parties (KMT and DPP) as the partisan parameter, but it would take social media contents to measure the partisan slant. From the aspects of scholars, social media gradually reshapes the formation of journalism, as the “multi-flow”
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communications between social media and news media was observed by scholars (Hilbert, Vásquez, Halpern, Valenzuela & Arriagada, 2017; Shi & Salmon, 2018).