Detailed Statistics and you can Artwork out-of Popular Words
I checked out possible variations by the webpages, geographical part, and ethnicity playing with t-examination and you will data regarding difference (ANOVA) to your LIWC group percentages. With the a couple other sites, half dozen of your own twelve t-examination was indeed significant from the following classes: first-person one [t(3998) = ?5.61, p Supplementary Desk dos to own mode, simple deviations, and contrasts ranging from ethnic organizations). Contrasts found high differences when considering White and all sorts of most other ethnic teams during the five of one's six high ANOVAs. Thus, we integrated ethnicity while the a great dummy-coded covariate inside analyses (0 = Light, 1 = Any cultural communities).
Of 12 ANOVA evaluating related to geographic region, just several was indeed extreme (family relations and you will confident feelings). Since differences weren't commercially meaningful, i don't thought geographic part in the next analyses.
Efficiency
Volume away from term fool around with goes without saying inside the detailed analytics (discover Desk step 1) and you will via keyword-clouds. The definition of-affect method illustrates probably the most widely used words over the whole sample and in each of the a long time. The phrase-cloud program automatically excludes specific words, as well as articles (a, and you will, the) and you will prepositions (to, that have, on). china ladies dating The remainder content words are scaled in size relative to the frequency, carrying out an intuitive portrait of the most prevalent stuff terms all over the new attempt ( Wordle, 2014).
