We checked possible differences of the site, geographic part, and ethnicity playing with t-tests and you may research out of difference (ANOVA) toward LIWC class percentages. Towards the two websites, half dozen of one’s 12 t-evaluation had been high in the pursuing the classes: first-person just one [t(3998) = ?5.61, p Supplementary Table 2 to own means, fundamental deviations, and you will contrasts anywhere between ethnic communities). Contrasts revealed tall differences between White and all of almost every other cultural organizations in the four of your half a dozen significant ANOVAs. Ergo, we included ethnicity because a beneficial dummy-coded covariate within the analyses (0 = Light, 1 = All other cultural groups).
Of one’s a dozen ANOVA tests associated with geographical sexy Campina grande girl region, only a couple of was in fact extreme (members of the family and you may positive feeling). Since differences weren’t officially significant, we didn’t think geographical part in after that analyses.
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Regularity from term play with is obvious in detailed analytics (pick Table 1) and you may thru keyword-clouds. The definition of-affect strategy portrays by far the most widely used terms and conditions across the entire decide to try as well as in all the age groups. The expression-cloud system immediately excludes particular terms, in addition to content (a, and you can, the) and prepositions (so you’re able to, that have, on). The remaining content terms and conditions is scaled in dimensions in line with the volume, undertaking an user-friendly portrait of the very prevalent articles terms all over brand new test ( Wordle, 2014).
Contour 1 shows the newest 20 most common stuff terms utilized in the entire test. As can get noticed, probably the most commonly used terminology was in fact love (searching during the 67% of pages), for example (searching within the 62% off profiles), appearing (looking in the 55% from profiles), and you will anybody (looking inside the 50% of pages). Therefore, the most famous terms and conditions was in fact comparable round the age range.
Figure dos suggests another 30 most common blogs conditions during the this new youngest and you may earliest age groups. By detatching the first 20 common posts words along side test, i train heterogeneity on the dating pages. In the next 29 terms towards the youngest age group, high level percentage terms integrated get (36% out of pages regarding the youngest generation), wade (33% out of users on the youngest age bracket), and you will performs (28% of profiles in the youngest age group). However, new earliest age bracket had high proportions away from terms instance take a trip (31% off users regarding the eldest age group), higher (24% of users regarding oldest generation), and you will dating (19% regarding pages on the earliest age group).
2nd 30 most typical words regarding youngest and eldest decades teams (shortly after subtracting the new 20 most frequent conditions out of Profile step one).
Theory Testing of age Variations in Language in the Relationships Users
To check on hypotheses, the fresh part of words regarding the relationship reputation that suit for every single LIWC class offered due to the fact centered details in regressions. I checked age and gender as independent details in addition to adjusting getting web site and ethnicity.
Hypothesis step 1: More mature decades will be of a top portion of conditions regarding the following the groups: first-individual plural pronouns, family unit members, friends, wellness, and positive feelings.
Findings mainly supported Hypothesis 1 (discover Table dos). Five of the four regressions shown a significant chief effect to own many years, in a way that just like the chronilogical age of the brand new profile journalist improved, the latest percentage of conditions regarding the category enhanced from the following categories: first-people plural, family, health, and positive feelings. I receive zero significant decades impact towards ratio out-of words about family members class.
a Gender: 0 (female) and you can step one (male). b Website: Both other sites was in fact dictomously coded as 1 and you may 0. c Ethnicity: 0 (White) and step 1 (Ethnic or racial fraction).
an excellent Gender: 0 (female) and you can 1 (male). b Website: The two other sites was indeed dictomously coded since step 1 and you may 0. c Ethnicity: 0 (White) and you will 1 (Cultural or racial minority).