We examined prospective distinctions from the website, geographical region, and you may ethnicity having fun with t-evaluation and you may investigation away from difference (ANOVA) towards LIWC group percentages. To the several websites, half dozen of your a dozen t-evaluating was tall throughout the adopting the classes: first-person one [t(3998) = ?5.61, p Second Desk dos to possess form, simple deviations, and you will contrasts between cultural organizations). Contrasts shown extreme differences when considering Light and all sorts of other ethnic organizations inside four of your half a dozen tall ANOVAs. Hence, i provided ethnicity as the a good dummy-coded covariate in the analyses (0 = White, step 1 = Any kind of ethnic teams).

Of twelve ANOVA evaluation linked to geographical part, simply a couple of had been high (relatives and you can confident emotion). As the differences just weren't officially meaningful, we didn't envision geographical region in the next analyses.

Overall performance

Regularity away from keyword play with is obvious in descriptive statistics (get a hold of Desk step one) and you may thru keyword-clouds. The definition of-cloud strategy portrays by far the most commonly used terms and conditions along side entire sample and also in each one of the a long time. The word-cloud program immediately excludes particular terminology, as well as articles (an excellent, and you can, the) and you can prepositions (so you can, with, on). The rest content conditions try scaled in size in line with their regularity, creating an user-friendly portrait of the very most common blogs terminology round the the fresh new test ( Wordle, 2014).

Profile step one reveals brand new 20 most commonly known content terms and conditions included in the entire take to. As well as rise above the crowd, the most frequently employed conditions have been like (searching during the 67% of users), including (lookin inside the 62% out of users), appearing (searching inside the 55% regarding pages), and you will some one (looking into the 50% of users). Ergo, widely known conditions was basically comparable all over age groups.

Contour 2 reveals the second 31 most common articles terms from inside the the youngest and you can earliest age groups. By eliminating the original 20 prominent articles terminology across the take to, i illustrate heterogeneity on the dating pages. Next 30 conditions towards youngest generation, high level percentage terms integrated get (36% from profiles on youngest age group), wade (33% off users from the youngest generation), and you can performs (28% out of profiles throughout the youngest age group). Conversely, the newest oldest generation had highest percentages of terminology such travel (31% out-of pages regarding eldest age bracket), great (24% off pages regarding oldest age bracket), and relationship (19% of users in the eldest generation).

2nd 31 most commonly known words throughout the youngest and you may eldest ages organizations (immediately following subtracting the brand new 20 common terms and conditions away from Shape 1).

Theory Investigations of age Differences in Words for the Relationship Profiles

To check on hypotheses, new portion of conditions from the relationships profile that fit for every single LIWC class offered as the built parameters in the regressions. I examined ages and you may intercourse because separate parameters together with adjusting having webpages and you will ethnicity.

Theory 1: More mature years is for the a higher percentage of conditions in the adopting the groups: first-people plural pronouns, family members, nearest and dearest, wellness, and you can confident emotion.

Results mostly supported Theory step 1 (look for Desk 2). Four of the four regressions revealed a critical head feeling for age, in a fashion that while the period of the fresh new profile author enhanced, the newest part of conditions about class enhanced regarding following categories: first-person plural, friends, wellness, and confident emotion. We discover no significant age feeling towards proportion of conditions on household members group.

a sex: 0 (female) and step one (male). b Webpages: Both other sites had been dictomously coded because step one and you will 0. c Ethnicity: 0 (White) and you may step one (Cultural otherwise racial minority).

a sex: 0 (female) and step 1 (male). b Web site: The two websites was indeed dictomously coded just like the step one and you can 0. c Ethnicity: 0 (White) and 1 (Ethnic or racial minority).