38 The Import Structure of LNG from Russia to Japan by Cognitive …
581
Factors
Results
Gazprom development gas field in Iran
Gazprom obtaining interest of gas field in Fa
Gazprom earing capital
Gazprom obtaining interest of gas filed in Ea
development gas field in Irkutsk
Yeltsin visit China
construction South Stream gas pipeline
construction Norud Stream gas pipeline
approval for construction by Mongolia governm
construction Yamal Europe gas pipeline
EUR change into gas energy
CHN strengthen gas infrastructures
CHN gas domestic demand expanding
CHN development domestic gas field
CHN oil domestic demand expanding
CHN development gas field in Central Asia
US Exim bank: destruction financing contract
construction Beijing Root pipeline
Gazprom bidding for Rosneft's stock
1
1
Gazprom increasing difficulty for earning
1
Rosneft obtaining interest of gas field in
Far East
1
Rosneft obtaining interest of gas field in
East Siberia
1
countermeasure global warming
1
CHN economic development
1
1
CHN gas demand increase in urban area
1
1
1
conflict between China and Russia
-1
difficulty for constructing in longitudinal
Korea Peninsula
1
conflict in Korea Peninsula
-1
USA economic punishment for Iran
-1 -1
construction for Beijing Root Pipeline
1 1
1
Fig. 38.2 Cognitive map: period (1-2) (Partially shown)
• Period (1-5): Ukraine crisis ・ Economic sanctions (1-5-3)/Strengthening RussiaJapan cooperation (1-5-1, 1-5-2, 1-5-4, 1-5-5) (Table 38.2).
38.3 Quantitative Analysis: Text Analysis
38.3.1 Methodology
Quantitative analysis was performed using the functions “extraction word: cooccurrence network” and “coding: cross tabulation” of KH Coder’s function.
The function “extracted word: co-occurrence network” is similar to “extracted
word: hierarchical cluster analysis”, and automatically draws a diagram that connects
highly co-occurring words and phrases based on the sentences of the information
source. This co-occurrence refers to the closeness of the appearance pattern of a
word, and a diagram showing this relationship is called a co-occurrence network
diagram. In this process, the list of related factors created in the process as used as
the information source for creating the network diagram. A group of words connected
581
Factors
Results
Gazprom development gas field in Iran
Gazprom obtaining interest of gas field in Fa
Gazprom earing capital
Gazprom obtaining interest of gas filed in Ea
development gas field in Irkutsk
Yeltsin visit China
construction South Stream gas pipeline
construction Norud Stream gas pipeline
approval for construction by Mongolia governm
construction Yamal Europe gas pipeline
EUR change into gas energy
CHN strengthen gas infrastructures
CHN gas domestic demand expanding
CHN development domestic gas field
CHN oil domestic demand expanding
CHN development gas field in Central Asia
US Exim bank: destruction financing contract
construction Beijing Root pipeline
Gazprom bidding for Rosneft's stock
1
1
Gazprom increasing difficulty for earning
1
Rosneft obtaining interest of gas field in
Far East
1
Rosneft obtaining interest of gas field in
East Siberia
1
countermeasure global warming
1
CHN economic development
1
1
CHN gas demand increase in urban area
1
1
1
conflict between China and Russia
-1
difficulty for constructing in longitudinal
Korea Peninsula
1
conflict in Korea Peninsula
-1
USA economic punishment for Iran
-1 -1
construction for Beijing Root Pipeline
1 1
1
Fig. 38.2 Cognitive map: period (1-2) (Partially shown)
• Period (1-5): Ukraine crisis ・ Economic sanctions (1-5-3)/Strengthening RussiaJapan cooperation (1-5-1, 1-5-2, 1-5-4, 1-5-5) (Table 38.2).
38.3 Quantitative Analysis: Text Analysis
38.3.1 Methodology
Quantitative analysis was performed using the functions “extraction word: cooccurrence network” and “coding: cross tabulation” of KH Coder’s function.
The function “extracted word: co-occurrence network” is similar to “extracted
word: hierarchical cluster analysis”, and automatically draws a diagram that connects
highly co-occurring words and phrases based on the sentences of the information
source. This co-occurrence refers to the closeness of the appearance pattern of a
word, and a diagram showing this relationship is called a co-occurrence network
diagram. In this process, the list of related factors created in the process as used as
the information source for creating the network diagram. A group of words connected