I examined prospective variations of the site, geographic area, and you may ethnicity playing with t-evaluating and analysis of variance (ANOVA) into LIWC classification proportions. Into two websites, half dozen of your several t-testing have been extreme throughout the following groups: first-individual only one [t(3998) = ?5.61, p Secondary Dining table dos for form, fundamental deviations, and you can contrasts between cultural teams). Contrasts shown extreme differences between White and all other cultural groups inside the five of six high ANOVAs. Therefore, i included ethnicity since the an excellent dummy-coded covariate within the analyses (0 = Light, step one = Some other cultural teams).
Of several ANOVA screening associated with geographic part, simply two were significant (nearest and dearest and you can positive feelings). While the differences weren’t officially meaningful, i didn’t imagine geographical area from inside the then analyses.
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Volume from phrase play with is evident inside the detailed analytics (come across Table step one) and you can thru term-clouds. The phrase-cloud approach illustrates the most popular conditions along the entire test and in all the age groups. The definition of-cloud system instantly excludes specific conditions, in addition to stuff (a good, and, the) and you will prepositions (so you’re able to, having, on). The rest content terms and conditions is scaled in proportions in accordance with their regularity, undertaking an intuitive portrait quite common stuff terms round the this new sample ( Wordle, 2014).
Shape step 1 reveals new 20 most common stuff terms found in the entire shot. As can rise above the crowd, one particular commonly used conditions have been love (appearing within the 67% from pages), instance (lookin during the 62% from profiles), searching (searching in the 55% of users), and you can anyone (appearing into the fifty% out-of profiles).