Detailed Statistics and you may Artwork of Popular Words
I checked possible differences by the webpages, geographical part, and you will ethnicity playing with t-tests and you can studies off difference (ANOVA) towards the LIWC group proportions. Toward a couple of other sites, six of your own twelve t-evaluating was indeed significant on adopting the categories: first-person one [t(3998) = ?5.61, p Additional Dining table 2 for mode, simple deviations, and contrasts between ethnic groups). Contrasts revealed high differences between Light as well as other cultural communities for the five of your own half dozen significant ANOVAs. Thus, we provided ethnicity since a great dummy-coded covariate for the analyses (0 = White, step one = Any other ethnic groups).
Of your several ANOVA evaluating linked to geographical part, just two had been extreme (members of the family and you may self-confident feelings). As the distinctions just weren’t commercially important, we failed to think geographic part in then analyses.
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Regularity out of phrase fool around with goes without saying in the detailed statistics (find Dining table step one) and you can thru phrase-clouds. The phrase-affect strategy depicts the most widely used terminology along the entire attempt and also in each of the age range. The definition of-cloud system automatically excludes certain conditions, including content (a good, and you may, the) and you will prepositions (so you’re able to, with, on). The rest stuff terms and conditions is actually scaled in dimensions in line with the regularity, starting an intuitive portrait quite commonplace blogs conditions around the the fresh new sample ( Wordle, 2014).
Shape 1 suggests new 20 most frequent stuff terminology utilized in the whole shot. As can rise above the crowd, many frequently employed words have been love (looking into the 67% from users), eg (lookin for the 62% regarding users), appearing (searching within the 55% from pages), and you may someone (appearing in fifty% regarding pages).