Modeling homophily in dynamic networks with application to HIV molecular surveillance
0
Citation
33
Reference
10
Related Paper
Abstract:
Abstract Background Efforts to control the HIV epidemic can benefit from knowledge of the relationships between the characteristics of people who have transmitted HIV and those who became infected by them. Investigation of this relationship is facilitated by the use of HIV genetic linkage analyses, which allows inference about possible transmission events among people with HIV infection. Two persons with HIV (PWH) are considered linked if the genetic distance between their HIV sequences is less than a given threshold, which implies proximity in a transmission network. The tendency of pairs of nodes (in our case PWH) that share (or differ in) certain attributes to be linked is denoted homophily. Below, we describe a novel approach to modeling homophily with application to analyses of HIV viral genetic sequences from clinical series of participants followed in San Diego. Over the 22-year period of follow-up, increases in cluster size results from HIV transmissions to new people from those already in the cluster–either directly or through intermediaries. Methods Our analytical approach makes use of a logistic model to describe homophily with regard to demographic, clinical, and behavioral characteristics–that is we investigate whether similarities (or differences) between PWH in these characteristics are associated with their sequences being linked. To investigate the performance of our methods, we conducted on a simulation study for which data sets were generated in a way that reproduced the structure of the observed database. Results Our results demonstrated strong positive homophily associated with hispanic ethnicity, and strong negative homophily, with birth year difference. The second result implies that the larger the difference between the age of a newly-infected PWH and the average age for an available cluster, the lower the odds of a newly infected person joining that cluster. We did not observe homophily associated with prior diagnosis of sexually transmitted diseases. Our simulation studies demonstrated the validity of our approach for modeling homophily, by showing that the estimates it produced matched the specified values of the statistical network generating model. Conclusions Our novel methods provide a simple and flexible statistical network-based approach for modeling the growth of viral (or other microbial) genetic clusters from linkage to new infections based on genetic distance.Keywords:
Homophily
In this paper, we extend existing work on latent attribute inference by leveraging the principle of homophily: we evaluate the inference accuracy gained by augmenting the user features with features derived from the Twitter profiles and postings of her friends. We consider three attributes which have varying degrees of assortativity: gender, age, and political affiliation. Our approach yields a significant and robust increase in accuracy for both age and political affiliation, indicating that our approach boosts performance for attributes with moderate to high assortativity. Furthermore, different neighborhood subsets yielded optimal performance for different attributes, suggesting that different subsamples of the user's neighborhood characterize different aspects of the user herself. Finally, inferences using only the features of a user's neighbors outperformed those based on the user's features alone. This suggests that the neighborhood context alone carries substantial information about the user.
Homophily
Assortativity
Instant messaging
Cite
Citations (311)
The purpose of this study is to analyze the impact of homophily on diffusion over social networks. An agent-based simulation model is developed to serve as the experimental ground for this analysis. Diffusion dynamics of a nonsticky innovation is investigated by varying homophily levels in the social network depicted in the model as the primary control variable. First of all, the results show that homophily is self-reinforcing. Second, starting from a nonhomophilous network, early increases in the level of homophily have a positive effect on the extent of diffusion, whereas further increases have a negative impact. Finally, several local minima and maxima are observed in the relation between the homophily level and the extent of diffusion. Our analysis focuses on node properties such as connectedness and average degrees in order to explain the observed regular relationship between homophily and diffusion. We argue that (i) homophily increases the connectedness of different status groups separately and (ii) increasing levels of homophily decreases the marginal importance of a single homophilous tie by increasing the sources of valuable information. Future research involves investigating the coevolution of social behavior and networks by allowing the adopted innovation to lead to value homophily, exploration of different diffusion initiation types, and different adoption heuristics.
Homophily
Social Connectedness
Social network (sociolinguistics)
Cite
Citations (40)
This research studied homophily of network ties in distributed teams in both task-related instrumental networks and non-task related expressive networks. Homophily of network ties was examined in terms of demographic and social characteristics, including gender, race, geographic location, and group assignment. Social network data were collected from 32 students enrolled in a distance learning class from two universities. MQAP regression analysis showed that homophily in gender and in race had no significant impact on the development of either instrumental or expressive ties. In instrumental networks, both homophily in group assignment and in location had significant impact on the development of network ties. In expressive networks, homophily in location had significant impact on the development of network ties, but the impact of homophily in group membership was only marginally significant. Further analysis of bonding ties with people of the same group and bridging ties with people from different groups showed that bonding social capital can exert significant influence on performance.
Homophily
Social network (sociolinguistics)
Network Formation
Social Network Analysis
Cite
Citations (183)
Homophily
Social network (sociolinguistics)
Cite
Citations (18)
Homophily is a well-known phenomenon in social networks, which is the tendency for individuals with similar characteristics to connect with each other. However, it is still unclear how homophily affects information diffusion. In this paper, we analyze the effect of homophily on information diffusion dynamics through theoretical analysis and numerical simulations. To this end, we consider the information diffusion process on a modular network consisting of two types of nodes with different diffusion properties: agitators and skeptists. In this setting, homophily is represented as the localization of agitators towards a specific community within a network. The analysis reveals that homophily has a significant effect on information diffusion dynamics. Although community structure (i.e., the connectivity between communities) has little or no effect on prevalence rate and diffusion speed without homophily, it affects them with homophily. Especially in networks with strongly separated communities, homophily facilitates local diffusion and inhibits global diffusion.
Homophily
Social network (sociolinguistics)
Social Network Analysis
Cite
Citations (1)
There is continuing debate over the effect of homophily, which is the tendency for individuals to socialize with similar people, on behavior diffusion. We aimed to clarify this relationship from a social network perspective, using the agent-based modeling approach. The results demonstrate that homophily promoted the diffusion of behaviors that people had a strong propensity to adopt, but had a prohibitive effect when the adoption propensity was weak. When the adoption propensity was moderate, the effect was promotive at first and then became prohibitive. Moreover, we identified 3 types of homophily—status, value, and mixed (status–value)—and found that mixed homophily was most effective for behavior diffusion, followed by value homophily and then status homophily. These findings highlight the importance of behavior classes and homophily type in the relationship between homophily and behavior diffusion, and call for a serious consideration of both factors when empirically studying the related issues.
Homophily
Value (mathematics)
Cite
Citations (2)
Practitioners and scholars have often warned against the negative social consequences of homophily. We consider the implications of homophily for the efficacy of organizational learning. In doing so, we highlight conditions under which homophily may enhance, rather than undermine, a firm’s ability to recombine and exploit individuals’ diverse knowledge. Employing a computational model, we identify two distinct pathways via which homophily influences the interactions between individuals in the organization, which we call the segregating and integrating effects of homophily. While homophily segregates individuals into homophilous social clusters, it also integrates individuals across a firm’s structural units (e.g., teams, divisions, departments). These two competing effects of homophily adjust the firm’s formal structure to drive effective recombination and diffusion of knowledge within the firm. We discuss why this positive role of homophily is more likely to exist in firms than in other social contexts.
Homophily
Cite
Citations (0)
Homophily has been a widely recognized dominant factor in offline social network connection, which refers to one's propensity to seek interactions with others of similar status or values. Existing studies regarding homophily factors have been limited mostly to offline sociodemographic characteristics, such as race, gender, religion, education and occupation, which may not necessarily manifest homophily in online social network. Some researchers dabble in online social network, but they extract homophily characteristics from static user profile or link data, which has not incorporated the dynamic process of social network. To better understand the key factors in the establishment of online relationship, we explore a large data set on Twitter, which contains all initiated links by 1453 organizational Twitter users over three months. An initiated link refers to organization following a user who is currently not a follower of the organization. We crawl data on a daily basis and monitor whether the initiated one-way link ends up with a two-way relationship. Based on the established homophily theory, we define two online homophily factors: achieved status homophily (estimated by the gap of the followers count), value homophily (measured by the overlap ratio of common followee, Pearson correlation, and Cosine similarity between two users' tweets, respectively). We find that both homophily factors play a key role in the formation of online reciprocal relationship, and the effect of status homophily is larger for superior followee (one who has more followers than the corresponding organization) than for inferior followee (one who has less followers than the corresponding organization). Our finding not only extends the offline "individual- individual" homophily theory to the new online "organization- individual" relationship, but also provides Twitter users insight into extending their social network by strategically targeting followee.
Homophily
Similarity (geometry)
Social network (sociolinguistics)
Value (mathematics)
Cite
Citations (5)
Purpose This empirical study aims to analyse the talent spotters' perception of their tendency to be homophilic in the talent identification process and their stance on it. Besides, this article examines the type of homophily and the homophily attributes involved. Design/methodology/approach Based on a qualitative design, 37 middle and senior line managers, working for two Argentine conglomerates in six Latin American countries, participated in the study. Data were collected through semi-structured interviews. Findings Homophily was perceived by most of talent spotters, who judged it as natural, while it was not perceived by a small group of the interviewees. In addition, among those who recognized its presence, another group advocated the homophilic advantages, while a final one admitted the presence of homophily and its negative implications. In addition, a variety of homophily attributes were identified; most of them within the value category. We posit that if homophily attributes are, at the same time, components of high potential models, homophily will constitute a functional bias to the talent identification process. Originality/value This is the first study that explores the talent spotters' perception of their homophily bias as well as the diversity of homophily attributes present in the talent identification process. This research highlights the relevance of the homophily attributes' analysis, taking into account its alignment to the potential model in order to improve the talent identification process.
Homophily
Identification
Value (mathematics)
Relevance
Cite
Citations (6)
본 연구는 소비자들의 브랜드 선호도가 소셜 네트워크 형성 동종애(homophily) 형성 기반이 될 수 있는지에 대한 실증적 고찰을 목표로 한다. 사회학의 주요 이론 중 하나인 동종애(Homophily)에 의하면, 비슷한 인구 통계학적 기반 및 성향을 공유하는 소비자들은 동종의 소셜 네트워크를 형성할 확률이 높은 것으로 알려져 있다. 반면에, 마케팅 영역에서는 브랜드가 얼마나 소비자들의 자아, 가치관, 성향을 반영하는지에 대한 역방향 인과 관계에 대한 고찰이 중심이 되어, 어떻게 소비 성향이 소셜 네트워크 형성에 기여하는 지에 대한 연구는 미흡한 상황이다. 유사한 기저 가치관을 공유하는 것이 소셜 네트워크 형성에 주요 동인이라 하면, 소비자들의 가치관이 반영된 브랜드를 동시에 선호하는 사람들 사이의 유대감 형성의 확률 또한 현저히 높을 것이다. 이러한 가정을 입증하기 위하여, 본 연구에서는 미국 내 고등학교 현장연구를 통하여 학생들 간의 브랜드 선호도 및 소셜 네트워크를 측정하였다. 인구 통계학 요인을 포함한 다양한 동종애 기반들을 통제한 상황에서 본 연구는 브랜드 선호도와 소셜 네트워크 형성의 유의미한 관계를 확인할 수 있었다. 브랜드 카테고리에 대한 추가적인 연구는 유의미한 브랜드 선호도와 소셜네트워크 형성의 관계가 패션, 음악 카테고리일 때 더 현저함을 보여주었다. 이와 같은 결과들을 통해 본 연구는 다양한 소셜네트워크 상에서 이루어지는 소비자들의 행동에 대한 이해도 및 플랫폼 상의 네트워크 형성에 대한 근원적 이해를 제고하는 기반을 마련하였다.
Homophily
Social network (sociolinguistics)
Cite
Citations (0)