I examined possible variations by website, geographical part, and you can ethnicity using t-examination and you can study off variance (ANOVA) to your LIWC category proportions. To your a couple of other sites, half a dozen of 12 t-evaluation have been tall on following the kinds: first-person just one [t(3998) = ?5.61, p Second Dining table 2 to own form, important deviations, and you can contrasts ranging from cultural organizations). Contrasts shown high differences when considering Light as well as most other cultural communities in four of your six high ANOVAs. Therefore, we included ethnicity because a great dummy-coded covariate in the analyses (0 = White, step 1 = Any other cultural communities).
Of the twelve ANOVA evaluating linked to geographical region, simply a couple of was in fact tall (household members and you may positive emotion). Due to the fact variations just weren’t officially meaningful, i did not believe geographical part when you look at the subsequent analyses.
Overall performance
Frequency off term play with is obvious during the descriptive analytics (come across Desk step one) and you can through word-clouds. The definition of-affect strategy illustrates the absolute most widely used terms over the entire attempt plus in all the age range. The word-cloud system automatically excludes particular conditions, also blogs (a beneficial, and you can, the) and you may prepositions (in order to, that have, on). The remainder posts words is scaled in dimensions prior to the regularity, starting an user-friendly portrait of the most prevalent stuff conditions around the the fresh new try ( Wordle, 2014).
Figure step 1 shows the brand new 20 popular stuff words used in the complete shot. As can be seen, many commonly used terms and conditions was indeed like (appearing in the 67% from users), such free colombian dating sites as for example (appearing from inside the 62% out-of users), searching (lookin inside 55% of pages), and you may somebody (lookin in fifty% from profiles). Thus, the most popular terms and conditions was in fact similar across age groups.
Shape 2 suggests the next 31 most typical stuff terms within the the fresh new youngest and you may eldest age groups. By removing the initial 20 well-known content terminology across the shot, we teach heterogeneity regarding matchmaking users. Next 31 words towards the youngest age bracket, raised percentage conditions integrated rating (36% regarding pages in the youngest generation), wade (33% away from profiles regarding youngest age bracket), and you will really works (28% off users on youngest generation). In contrast, the latest oldest generation had large proportions out-of words particularly travel (31% away from users in the eldest generation), high (24% regarding profiles regarding the earliest age bracket), and you may relationship (19% out of users in the oldest age bracket).
Next 31 most typical terms from the youngest and you will eldest ages teams (shortly after subtracting the 20 most commonly known terms and conditions from Shape step 1).
Theory Assessment of age Variations in Code from inside the Relationship Profiles
To check on hypotheses, the fresh new percentage of terminology throughout the relationship character that suit for every single LIWC class offered as the dependent parameters into the regressions. I checked out ages and you can gender because separate variables in addition to modifying for site and you can ethnicity.
Theory 1: Old years will be from the increased percentage of terms and conditions about adopting the kinds: first-individual plural pronouns, members of the family, family relations, health, and you will positive emotion.
Conclusions mostly supported Hypothesis 1 (discover Dining table dos). Four of your own five regressions shown a significant head feeling getting years, in a manner that because chronilogical age of the fresh character blogger enhanced, the new portion of terms and conditions on category enhanced regarding following the categories: first-people plural, family members, health, and you may self-confident feelings. We located no tall years feeling on proportion of terms on the loved ones group.
good Gender: 0 (female) and step 1 (male). b Webpages: Both other sites was in fact dictomously coded as the step one and you will 0. c Ethnicity: 0 (White) and you can 1 (Cultural or racial minority).
a great Gender: 0 (female) and you will step one (male). b Website: The 2 other sites was in fact dictomously coded because 1 and you may 0. c Ethnicity: 0 (White) and you will step 1 (Cultural or racial fraction).
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