step three.2parison ranging from Users with Dogs and Profiles in the place of Pets

step three.2parison ranging from Users with Dogs and Profiles in the place of Pets

Socio-market investigation and you may level of character photos demonstrated for all analysed profiles (letter = 2400) and individually to have Vienna (letter = 1200) and you can Tokyo (letter = 1200).

Of the 2400 investigated amateurmatch support profiles, 373 (15.5%) displayed at least one animal photo. In both cities, we found a positive correlation between the number of profile photos and the number of profile photos showing animals (Vienna: rs = 0.184; p = 0.008 | Tokyo: rs = 0.206; p = 0.009).

Comparison of the users who displayed animal photos on their profile and the users who did not do so resulted in the following significant differences (see Table 5 ). On the selected analysed dating app, significantly more women than men (p = 0.049) present animal photos on their profiles. Further, significantly more users in Vienna (p = 0.006), and significantly more older users (p = 0.019), have profiles with animal photos as compared with users in Tokyo and younger users. In addition, users who display an animal photo on their profile post, on average, display one more photo than users who do not do so (p < 0.001). No significant differences between heterosexual and homosexual users of the analysed app were identified (p = 0.639) (see Table 5 ).

Table 5

Socio-demographic data and amount of reputation images showed for everyone users that have animals (n = 373) and you will profiles instead dogs (n = 2027).

3.3. Prevalence and you may Classification out of Pet Presented into Pages

A much deeper function of the research was to decide how of a lot profiles demonstrated dogs and you can what types of creature have been showed. Generally, so much more pages when you look at the Vienna (211; 17.6%) reveal pet on the character than pages in the Tokyo (162; 13.5%) (? 2 (1) = eight.622; p = 0.006). All pages-we.e., 77.7% in Vienna and 76.5% inside Tokyo-shown the animal, or animals, into the a single character photos. Within the a smaller proportion away from times-i.elizabeth., twenty two.3% when you look at the Vienna and you can 23.5% from inside the Tokyo-the latest profiles got one or more photos indicating the animal, otherwise pets, inside their reputation.

3.step three.1. Demonstration from Pet in the 1st Character Pictures

Of the 373 pages deciding to become creature photographs, 73 (19.6%) displayed the newest animals to their basic profile photos. Right here, evaluation from users inside Vienna and Tokyo found significant distinctions since 65.9% pages when you look at the Vienna shown a dog into basic photo given that compared with 29.3% regarding profiles into the Tokyo (? 2 (1) = 8.610, p = 0.003). In addition, merely users in Vienna (several.2%) demonstrated ranch animals on the basic profile pictures. It lead to a big difference so you’re able to users in the Tokyo (? 2 (1) = cuatro.189, p = 0.041). We and additionally discovered that a lot more users inside Tokyo presented cats (forty.6%) and you will unique dogs (fifteen.6%) inside their very first reputation photographs than just users from inside the Vienna (kitties = dos.4%; amazing dogs = 0.0%) (cats: ? dos (1) = seven.819, p = 0.005; unique pets: ? dos (1) = 6.877, p = 0.009).

3.3.dos. Demonstration from Dogs in all Reputation Pictures (Including the First Profile Photo)

Figure 1 shows the percentages of various animal species shown on the analysed profiles. Again, comparison between the profiles in Vienna and Tokyo revealed significant differences here. Users in Tokyo were significantly more likely to show cats (35.8%) and small animals (6.8%) than users in Vienna (cats = 18.0%; small animals = 0.0%) (cats: ? 2 (1) = , p < 0.001; small animals: ? 2 (1) = , p < 0.001). The Viennese profiles included farm animal (10.9%) and horse (7.1%) photos significantly more often than the profiles in Tokyo (farm animals = 0.6%; horses = 1.2%) (farm animals: ? 2 (1) = , p < 0.001; horses: ? 2 (1) = 7.270, p = 0.007) (see Figure 1 ).

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