Fig 1.
Theoretical framework illustrating how the subconstructs place meaning and place attachment are related to sense of place.
The bar graphs summarize the findings from this study.
Table 1.
Summary of word analysis separated by the two respondent groups (experts, novices) with descriptive statistics around the number of words listed and their emotional values (valence, arousal, dominance = VAD), and a description of the modifications conducted during data cleaning.
Sentiment values are available for about 78% of words with a VAD value.
Table 2.
Findings from thematic content analysis and coding of the open-ended responses to the question “In no more than two sentences, how do you personally feel about Greenland?” for novice and expert respondents.
Fig 2.
Word clouds of the novice and expert responses to the question: “In no more than two sentences, how do you personally feel about Greenland?” (word cloud left: Novice, right: Expert).
Fig 3.
Word clouds of the novice and expert responses to the question, “What words would you use to describe Greenland?” (word cloud left: Novice, right: Expert).
Fig 4.
Results of emotional value coding of the words differentiated by novices and experts.
Differences are all statistically significant. Left: Emotional value analysis shows the mean values and standard deviation. Right: Percentage of positive and negative polarity of words.
Table 3.
Descriptive statistics and independent t-test results comparing emotional value ratings of words reported by experts and novices.
Table 4.
List of the highest and lowest value words for valence, arousal and dominance.
Note that arousal has a u-shaped distribution, while valence and dominance show a linear correlation from positive (high) to negative (low).
Table 5.
Percentage of words used to describe Greenland relative to the total number of words used by experts and novices across themes that emerged from the place meaning study by [30].