We looked at potential variations by the site, geographic area, and you may ethnicity playing with t-evaluation and you can investigation regarding variance (ANOVA) into LIWC class percent. On the a few websites, half a dozen of your own twelve t-screening were significant about pursuing the groups: first-individual only 1 [t(3998) = ?5.61, p Second Dining table dos to possess form, important deviations, and you will contrasts anywhere between ethnic organizations). Contrasts shown extreme differences when considering White and all sorts of most other ethnic groups from inside the five of the half dozen significant ANOVAs. Thus, i provided ethnicity because the a good dummy-coded covariate into the analyses (0 = White, 1 = All other cultural groups).
Of the twelve ANOVA evaluating connected with geographical part, only several were tall (members of the family and you may self-confident emotion). Just like the differences just weren't theoretically significant, i didn't consider geographic part inside further analyses.
Results
Regularity of word fool around with is evident in the detailed statistics (get a hold of Desk step one) and you can via phrase-clouds. The phrase-affect approach depicts by far the most widely used terms and conditions along the whole sample as well as in all the a long time. The term-affect system automatically excludes particular terms and conditions, also content (an excellent, and you can, the) and you can prepositions (to help you, with, on). The remainder blogs terms was scaled in dimensions relative to their regularity, undertaking an user-friendly portrait of the most extremely commonplace posts terms all over the brand new try ( Wordle, 2014).
Figure step 1 reveals the newest 20 common blogs conditions used in the entire attempt. As can rise above the crowd, probably the most frequently employed terminology was in fact like (appearing within the 67% out of users), for example (lookin inside 62% away from users), looking (appearing within the 55% from pages), and you can people (searching for the fifty% of users). Ergo, the most popular terminology was in fact comparable across the age range.
Figure dos suggests the next 29 most frequent content terminology in the the latest youngest and you will oldest age groups. By eliminating the first 20 well-known stuff terms and conditions along side test, i train heterogeneity throughout the dating users. In the next 30 terminology to the youngest age group, raised percentage terms provided score (36% off profiles on the youngest age group), go (33% regarding profiles regarding the youngest https://kissbridesdate.com/american-women/colorado-springs-co/ age group), and work (28% regarding pages regarding youngest age bracket). In contrast, the eldest age group got high percentages of terms and conditions including travel (31% from pages on earliest generation), high (24% off users in the earliest age group), and you can dating (19% out-of profiles on oldest age bracket).
Next 31 most frequent terminology on youngest and you will earliest age teams (shortly after deducting the latest 20 popular terms from Figure step one).
Hypothesis Investigations old Differences in Language within the Relationship Profiles
To check on hypotheses, the newest part of terminology from the relationships character that fit for each and every LIWC category offered just like the built parameters inside the regressions. I checked out decades and gender because separate details along with changing to own web site and ethnicity.
Theory step one: Earlier age could well be in the a higher portion of terms on the following the groups: first-person plural pronouns, family unit members, friends, wellness, and self-confident feelings.
Findings largely offered Theory step 1 (pick Table dos). Four of your own four regressions revealed a serious fundamental perception to possess ages, in a manner that since the ages of brand new reputation copywriter improved, brand new percentage of terms about classification improved from the after the categories: first-person plural, nearest and dearest, wellness, and you may positive feeling. We discover zero extreme ages effect on the ratio out of words on the family group.
a beneficial Gender: 0 (female) and you may 1 (male). b Webpages: The 2 other sites was dictomously coded given that step 1 and you will 0. c Ethnicity: 0 (White) and you will step one (Cultural or racial fraction).
an excellent Gender: 0 (female) and you can step one (male). b Web site: The two other sites have been dictomously coded as the step 1 and you can 0. c Ethnicity: 0 (White) and you may step one (Cultural otherwise racial fraction).