國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
context, KMT actors dominated the discussion of Shenao power plant issue, compared to DPP actors. In addition, the Storm Media (STOM), which was commonly considered as pro-KMT among Taiwanese readers, revealed its slant towards DPP. In fact, the result suggested smaller differences between the value of correlation to be pro-KMT or pro-DPP. It might be due to the higher rate of review articles (13.3%) that might influence the constructions of word and matrix, and affect result of QAP analysis.
4.4. Semantic Network Analysis: Pro-DPP/KMT News Media in Shenao’s Issue
To answer RQ3, this research selected the news media as pro-DPP group and pro-KMT group, according to the results of RQ2. The QAP correlation score in RQ2 determined the partisan slant and the classification of pro-DPP or pro-KMT media. Any news media brand that had higher correlation score to either DPP or KMT parameter would be sorted as the DPP or KMT leaning media. Based on the QAP results, totally 498 (19%) articles from two news media brands were sorted as pro-DPP set, and 2,129 (81%) articles from eight news media brands were sorted as pro-KMT set. Table 8 described the article counts of each news media brand.
This research built up a pro-KMT and a pro-DPP semantic network for analysis. Similar to the analysis process in RQ1, the UCINET 6 conducted the analysis with eigenvector centrality to measure the influence of salient concepts in networks. It would compare the salient concepts between pro-DPP and pro-KMT news media.
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
Table 8
List of Pro-DPP and Pro-KMT News Media
News Media Code Article Counts
Pro-DPP News Media
SETN - Sanlih E-Television online (三立新聞網) SETN 265
Storm Media (風傳媒) STOM 233
Totals of Pro-DPP News Media (n=2,627) 498 (19%)
Pro-KMT News Media
TVBS News online TVBS 185
ETTV news online (EBC news) (東森新聞) ETTV 32
Apple Daily online (壹蘋果日報) APPL 143
UDN - United Daily News online (聯合新聞網) UDN 829
Liberty Times online (自由時報) LIB 143
NOWNEWS (今日新聞) NOW 223
ETtoday (東森新聞雲) ETT 265
Newtalk (新頭殼) NEW 282
Totals of Pro-KMT News Media (n=2,627) 2,129 (81%)
Totals of News Media Articles 2,627 (100%)
Table 9 revealed the top-ten words ranked by eigenvector centrality values, suggested the influence ranking of the concepts among the semantic network. The result suggested the same words but different ranking in the first six words on pro-DPP and pro-KMT networks. Both pro-DPP and pro-KMT emphasized the “深澳 (Shenao)”, “國
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
民黨 (KMT)”, “燃煤電廠 (coaled-fired power plant)”, “民進黨 (DPP)”, “深澳電廠 (Shenao power plant)”, “市長 (mayor)” and “新北 (New Taipei City)”.
Table 9
Top-Ten Salient Concepts with Greatest Eigenvector Centralities: KPP and Pro-KMT News Media
Rank Pro-DPP Pro-DPP
Eigenvalue Pro-KMT Pro-KMT
Eigenvalue
1 深澳 5032.48 深澳 20662.27
2 國民黨 932.25 國民黨 3914.10
3 燃煤電廠 639.65 深澳電廠 1608.03
4 民進黨 374.02 市長 1244.55
5 深澳電廠 310.33 燃煤電廠 1013.70
6 市長 262.75 民進黨 945.34
7 新北 215.62 新北 806.37
8 選舉 201.00 政府 702.54
9 政策 194.98 政策 673.51
10 賴清德 179.44 台灣 657.68
The different salient words between the pro-DPP and pro-KMT news media suggested that the concepts of “選舉 (election)” and “賴清德 (Lai, Ching-Te)”, were more salient and only presented in pro-DPP media, and “台灣 (Taiwan)”, which only presented in top-ten salient concepts in KMT media. As for the salient conept of “台灣 (Taiwan)”, several pro-KMT media outlets mentioned Taiwan citizen’s health, potential or current districts of air
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
pollution in Taiwan, or the energy supply for Taiwanese. Basically these issues tied with issue-based or environment relevant information. It corresponded to the results of QAP analysis in RQ2, as most of the KMT actors dominated the discussions of Shenao power plant issue, compared to DPP actors, although most news media contents were issue-based which felt concerned more about what environmental groups discussed. News media might cover more about what KMT actors focused, such as the referendum, countersign like “anti-Shenao power plant”, and so on, which led the partisan leaning of pro-KMT. “台灣 (Taiwan)” was one of the salient concepts that tied with the issue-based or environment relevant contents.
Figure 9 illustrated the semantic networks of news articles of pro-DPP and pro-KMT news media, labelled from the results of partisan slant analysis (RQ2), regarding Shenao issue.
Similar to RQ1, the node size was weighed based on document frequency of the top-100 words in each network, by Gephi, using Force Atlas and Fruchterman-Reingold algorithms (Cherven, 2013; Bastian et al., 2009) to sketch the layout of semantic networks. Key concepts identified in both the pro-DPP and pro-KMT media were the Shenao power plant, two major political parties (DPP and KMT), and the words related to the government. Regarding the differences between pro-KMT and pro-DPP media, pro-DPP news media hightlighted more on the word of “台北 (Taipei)”. Since Taipei City was nearby New Taipei City, Taipei mayor Wen-Ze Ke’s commentary of Shenao power plant became a focus in many pro-DPP news media outlets.
Compared to the results in RQ1, two sorts of news media focused similarly on Shenao power plant issue, partisan, politics, and environmental concerns. It indicated that KMT and pro-DPP media focused on the similar issue, which means there was no salient difference among news media brands despite possessing either partisan leaning.
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
Figure 9
Semantic Networks of Pro-DPP and Pro-KMT News Media (Labelled from Partisan Slant Analysis-RQ2) in Shenao Issue
Pro-DPP News Media
Pro-KMT News Media
‧
國立 政 治 大 學