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Exploring Within-Gender Differences in Friendships Using an Online Social Network.
Pietro Pollo1, Tania A Reynolds2, Khandis R Blake3
1Evolution and Ecology Research Centre, School of Biological, Earth and Environmental Sciences, University of New South Wales, 5 Floor, Building E26, Kensington, NSW, 2052, Australia. pietro_pollo@hotmail.com.
People form friendships with similar individuals, a pattern called homophily. This study found age and body mass index (BMI) similarity are key in same-gender online friendships, especially for men.
Area of Science:
- Social Psychology
- Online Social Networks
- Evolutionary Psychology
Background:
- Homophily describes the tendency for individuals to associate with similar others.
- Previous friendship research often relies on self-reported data, lacking insights into actualized connection patterns.
- Online social networks offer large-scale data to study real-world social dynamics.
Purpose of the Study:
- To investigate the influence of gender, age, and body mass index (BMI) on same-gender online friendships.
- To analyze actualized friendship patterns using data from a large social network.
- To explore potential evolutionary underpinnings of observed homophily in friendships.
Main Methods:
- Analysis of connection data from a large Slovakian online social network (>400,000 users).
- Statistical assessment of age and BMI homophily in same-gender connections.
- Examination of friendship reciprocation based on BMI divergence, particularly among women.
Main Results:
- Age and BMI homophily were observed in both male and female same-gender connections, more pronounced in men.
- Women's same-gender connections were less likely to be reciprocated as their BMI varied.
- Findings suggest trait similarity plays a significant role in forming same-gender friendships.
Conclusions:
- Trait similarity, specifically age and BMI, is crucial for same-gender online friendships.
- Evolutionary factors related to competition may influence gender-specific patterns in friendship formation.
- Online social network data provides valuable insights into the mechanisms of homophily.
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