We first examined descriptive statistics when it comes to proportions of terms folks of different ages found in their dating pages. We additionally produced illustrative numbers portraying the absolute most words that are common.
We then looked to theory evaluation utilizing ordinary minimum squares regression. The result variables in this scholarly research had been the proportion of terms suitable each one of the 12 groups within the LIWC analyses. The LIWC categories had been all favorably skewed because of the amount of zero values (in other words., participant failed to utilize any terms within the category). We went each analysis with a square-root transformation (used to deal with non-normality in previous studies utilising the LIWC; DeAndrea, Shaw & Levine, 2010; Hirsh & Peterson, 2009). The pattern of findings had been comparable after using the transformations. For simplicity of interpretation, findings are presented utilizing the untransformed LIWC category data. The separate variable had been age, treated as a variable that is continuous. We additionally included sex.
Initially, we ran the regressions such as the Age Г— Gender discussion term. One interaction that is significant based in the group of good feeling, so that ladies had greater mean proportions of good feeling terms than guys after all many years, with females showing a somewhat steeper linear enhance as we grow older than males. Hence, we didn’t range from the relationship term for Age Г— Gender into the models reported right right here.
We examined prospective differences by internet site, geographic area, and ethnicity utilizing t-tests and analysis of variance (ANOVA) for the LIWC category percentages.