Birds of a Feather: Homophily in Social Networks

By M. McPherson, Lynn Smith-Lovin, J. Cook. 2001

18,546 citations recorded by the source corpus.

Subfields: Sociology and Political Science

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In Sociology and Political Science

Citations in the corpus

Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “…focused than others depending on their demographics (e.g., women tend to be more focused toward their top friends); while others indicate that how users interact depends on the type of relation they share (Burke et al., 2013) and on shared characteristics (i.e., homophily) (McPherson et al., 2001).”
Racial categories in machine learning (2018, background): “race may be operationalized using network representations of society. Homophily, the phenomenon that similar people are more likely to be socially connected, is a robustly studied and conﬁrmed result [37], and the problem of bridging between isolated niches has been posed as a general social problem”
Revisiting Heterophily For Graph Neural Networks (2022, background): “GNNs are built on the homophily assumption [35]: connected nodes tend to share similar attributes with each other [14], which offers additional information besides node features.”
Promoting Social Inclusion in Educational Settings: Challenges and Opportunities (2019, background): “Although friendships are frequently formed based on shared social identities, such as gender and ethnicity, similar interests also increase friendship formation (McPherson et al., 2001).”
Structure and evolution of global cluster networks: evidence from the aerospace industry (2016, background): “7 geography is the notion of homophily – similarity breeds connections (McPherson et al., 2001).”
Homophily, Structure, and Content Augmented Network Representation Learning (2016, background): “In this paper, to fill this gap, we propose a new NRL algorithm, called HSCA (Homophily, Structure, and Content Augmented network representation learning), that effectively learns a latent network representation using all three information sources.”
Hip and trendy: Characterizing emerging trends on Twitter (2011, neutral): “Beyondthehigherlikelihood ofconnectionsandties,peoplelivinginthesamegeographic areaaremoresimilar(McPhersonetal.,2001),andlikelyto shareinterestsandinformationneeds(Yardi&boyd,2010).”
Estimating peer effects in networks with peer encouragement designs (2016, background): “There are many causes of correlated behaviors in networks that make it difficult to identify peer effects, including selective tie formation [i.e., homophily (7)], unobserved correlated external causes, and prior peer effects (4, 8, 9).”
The dynamics of interfirm networks along the industry life cycle: The case of the global video game industry, 1987–2007 (2013, background): “Sociologists refer to the term homophily for explaining the tendency of social groups to form around actors that have similar tastes, preferences, ethnic background or social status (McPherson et al., 2001).”
Planetary-scale views on a large instant-messaging network (2008, neutral): “(a) Number of logins per user.”
Discretion Within Constraint: Homophily and Structure in a Formal Organization (2012, neutral): “Introduction Social interactions are notoriously homophilous (McPherson et al. 2001).”
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs (2020, background): “[21] Miller McPherson, Lynn Smith-Lovin, and James M Cook.”
Exposure to opposing views on social media can increase political polarization (2018, background): “Despite initial optimism that social media might enable people to consume more heterogeneous sources of information about current events, there is growing concern that such forums exacerbate political polarization because of social network homophily, or the well-documented tendency of people to form”
An expanded servicescape perspective (2011, background): “We encourage researchers to explore the extent to which a customer’s perceived similarity among unknown customers and employees breeds connections (McPherson et al., 2001) and acts as a moderator that encourages “birds of a feather to flock together” in particular consumption settings.”