Ego Network Structure Research Articles

Value implications of followers in social marketplaces: insights into ego network structures

PurposeIn social marketplaces, follower ego networks are integral social capital assets for online sellers. While previous research has underscored the positive impact of the follower number on seller performance, little attention has been given to the structure of follower networks and their value implications. This research investigates two structural properties of follower networks—network centralization and density—and examines their main and contingent effects on sellers’ sales performance.Design/methodology/approachA 13-month panel dataset of 1,150 sellers in Etsy, a social marketplace for handmade and vintage products, was collected and analyzed. A fixed effects model was adopted to validate the hypotheses on the main effect of centralization and density, as well as the moderating effects of two store attributes: store age and product diversification.FindingsWe find that both network centralization and density negatively impact sellers’ sales performance, and these effects vary across store age and product diversification levels. Specifically, the negative effect of network centralization is less pronounced for older stores than young ones, whereas the negative effect of density is more severe for stores with high product diversification.Originality/valueThis research contributes to social commerce research by highlighting the significance of network structure, alongside network size, in assessing the value of followers and offers practical guidance for sellers in social marketplaces seeking to optimize their follower networks.

How does ego-network structure affect innovation within industrial clusters? The moderating effect of ego-network density

ABSTRACT Considerable uncertainty remains about the optimum position in the ego–network structure to pursue innovation. We investigate how ego-network density moderates the effect of ego-network structure on two types of innovation. We sample 92 firms in cultural and creative industries and analyse our data using hierarchical regression analysis. We find that ego-network density positively moderates the effect of betweenness centrality and structural holes on exploratory innovation but negatively moderates the effect of closeness and degree centrality on exploratory innovation. Ego-network density also positively moderates the effect of betweenness centrality on exploitative innovation. The results provide new insight into the role of ego-network structure in promoting or jeopardising exploitative and exploratory innovation.

How do knowledge diversity and ego-network structures affect firms' sustainable innovation: evidence from alliance innovation networks of China's new energy industries

PurposeFacing the global public health emergency (GPHE), the conflict of cultural differences and the imbalance of vital resources such as knowledge among different organizations are becoming more severe, which affects the enthusiasm and sustainability of firms' innovation heavily. It is an urgent problem to be solved for firms how to make use of internal knowledge and external power to help firms' sustainable innovation (FSI). Thus, the purpose of this study is to deeply analyze how firms' internal knowledge diversity (KD) and external ego-network structures [ego-network density (ED) and honest brokers (HB)] affect FSI, as well as how the ego-network structures (ED and HB) moderate the relationship between KD and FSI based on the perspective of the ego network.Design/methodology/approachBased on the data of the alliance innovation networks of China's new energy industries in 2009–2019, this study uses the social network analysis method and negative binomial regression model to explore the effect of KD and ego-network structures (ED and HB) on FSI, as well as the moderating effects of ego-network structures (ED and HB) on the relationship between KD and FSI based on the perspective of ego network.FindingsThis study finds that KD, ED and HB can boost FSI. Moreover, ED plays a negative moderating role in the relationship between KD and FSI. However, the negative moderating effect of HB on the relationship between KD and FSI is not significant.Research limitations/implicationsThis study presents fresh empirical evidence and new insights for firms on how to make full use of firms' internal KD and external ego-network structures to facilitate FSI.Originality/valueFirst, this study not only enriches the research on the consequences of KD but also expands our understanding of the knowledge-based view to some extent. Second, this study not only enriches the motivation research of the FSI based on the perspective of ego-network in the context of the GPHE but also expands the application scope of social network theory and sustainable innovation' theory in part. Third, this paper is a new attempt to apply social network theory and knowledge-based view at the same time.

Journalists’ ego networks in Twitter: Invariant and distinctive structural features

Ego networks have proved to be a valuable tool for understanding the relationships that individuals establish with their peers, both in offline and online social networks. Particularly interesting are the cognitive constraints associated with the interactions between the ego and the members of their ego network, which limit individuals to maintain meaningful interactions with no more than 150 people, on average, and to arrange such relationships along concentric circles of decreasing engagement. In this work, we focus on the ego networks of journalists on Twitter, considering 17 different countries, and we investigate whether they feature the same characteristics observed for other relevant classes of Twitter users, like politicians and generic users. Our findings are that journalists are generally more active and interact with more people than generic users, regardless of their country. Their ego network structure is very aligned with reference models derived in anthropology and observed in general human ego networks. Remarkably, the similarity is even higher than the one of politicians and generic users ego networks. This may imply a greater cognitive involvement with Twitter for journalists than for other user categories. From a dynamic perspective, journalists have stable short-term relationships that do not change much over time. In the longer term, though, ego networks can be pretty dynamic, especially in the innermost circles. Moreover, the ego-alter ties of journalists are often information-driven, as they are mediated by hashtags both at their inception and during their lifetime. Finally, we found that relationships between journalists are assortative in popularity: journalists tend to engage with other journalists of similar popularity, in all layers but especially in their innermost ones. Instead, when journalists interact with generic users, this assortativity is only present in the innermost layers.

Aggressive or not aggressive: the different role of ego-network dynamics and density in the international network

PurposeThis study aims to explore the effect of competitive aggressiveness on firm performance and the moderating effect of firm 2019s ego-network structures in the international coopetition network.Design/methodology/approachFrom the perspective of strong cooperation of the global automobile industry in recent years, this study uses the global automobile firms in Factiva database as samples to test hypotheses using the least squares dummy variable (LSDV) model.FindingsThis study finds that there is different relationship between the number and variety of competitive actions and firm performance. In addition, ego-network structures have different coefficients for the number and variety of competitive actions.Originality/valueThe conclusions provide theoretical support and policy suggestions for firms to develop effective competitive strategies according to ego-network structures in the international coopetition network.

The academic wanderer: structure of collaboration network and relation with research performance

Thanks to the widespread availability of large-scale datasets on scholarly outputs, science itself has come under the microscope with the aim of capturing a quantitative understanding of its workings. In this study, we leverage well-established cognitive models coming from anthropology in order to characterise the personal network of collaborations between scientists, i.e., the network considered from the standpoint of each individual researcher (referred to as ego network), in terms of the cognitive investment they devote to the different collaborations. Building upon these models, we study the interplay between the structure of academic collaborations, academic performance, and academic mobility at different career stages. We take into account both purely academic mobility (i.e., the number of affiliation changes) and geographical mobility (i.e., physical relocations to different countries). For our investigation, we rely on a dataset comprising the geo-referenced publications of a group of 81,500 authors extracted from Scopus, one of the biggest repositories of academic knowledge. Our main finding is that there is a clear correlation between the structure of co-authorship ego networks and academic performance indices: the more one publishes and the higher their impact, the larger their collaboration network. However, we observe a capacity bound effect, whereby, beyond a certain point, higher performances become increasingly less correlated with large collaboration networks. We also find that international academic migrants are better at growing their networks than researchers that only migrate within the same country, but the latter seem to be better in exploiting their collaboration to achieve higher impact. High academic mobility does not appear to translate into better academic performance or larger collaboration networks. This shows a different finding with respect to related literature, where scientific productivity is seen as directly linked to mobility. Our results show that, when looking at impact of research, this is not necessarily the case.

Predicting Tie Strength with Ego Network Structures

Not all social media “friends” are close friends, but distinguishing them from mere acquaintances is an important task in marketing. The notion of a close friend is reflected in the metric tie strength, but the true tie strength is often unobserved in online social networks. With this research, we propose an approach that predicts real-world tie strength via online data measures of similarity, interaction, and network data. At its core, we assess ego network structures to predict tie strength, i.e., all first-degree connections and the interlinkage among them. Ego networks are easier to obtain than full networks, and researchers can process them more efficiently. We explain why bridging ego network positions could be associated with real-world tie strength and demonstrate the high discriminatory power of related network measures. In combination with measures of similarity and interaction, the precision of identifying all observed real-world strong ties is 45%. Finally, we empirically highlight the practical relevance of this finding by demonstrating that people react stronger to suggestions of a close friend compared to an acquaintance in a social advertisement experiment.

Egocentric network composition and structure relative to violence victimization among a sample of college students

Objective To use egocentric network analysis to understand how composition and structure of egonetworks relate to violence victimization among college students. Participants: 697 students from a large southeastern university completed online surveys. Methods: Hierarchical logistic regression analyses assessed the relationship between egocentric network variables and a history of violence victimization. Results: Being connected to others with a history of violence victimization increased a student’s odds of indicating their own history of physical, emotional, and sexual violence victimization. Having less dense egonetworks was related to sexual violence victimization, while being connected to less people of the same gender was related to emotional violence victimization. Conclusion: The way college students’ networks are composed and structured could help in understanding violence victimization in this population, and should be considered in prevention and reactionary efforts on campuses. These findings add to the current literature largely focused on individual-level risk factors related to violence.

Integrating relations and criminal background to identifying key individuals in crime networks

One of the most common methods used in the social network analysis of criminal groups is node importance evaluation, which focuses on the links between network members to identify likely crime suspects. Because such traditional node evaluators do not take full advantage of group members' individual criminal propensities, a new evaluator called the social network criminal suspect evaluator (SNCSE) is proposed. SNCSE incorporates members' individual criminal propensities into the node importance evaluation and employs a novel perspective based on concepts of human and social capital, an ego network structure, and an analogy between social interaction and field theory. SNCSE is applied to solve two real-world problems. Its effectiveness is compared with that of traditional evaluators. The results show that integrating criminal propensity into network analysis enables the more accurate identification of key suspects compared to alternative evaluators.

Where you are, what you want, and what you can do: The role of master statuses, personality traits, and social cognition in shaping ego network size, structure, and composition

AbstractEgo networks are thought to be influenced by the opportunities provided to associate with others given by our master statuses (e.g., race or sex), by the preferences individuals possess for interaction given our personality traits (e.g., extroverted or neurotic), and by the capacity to manage interactions on an ongoing basis given our cognitive ability to recall network information. However, prior research has been unable to examine all three classes of predictors concurrently. We rectify this deficiency in the literature by using a novel dataset of nearly 1000 respondents collected using controlled laboratory designs; using this dataset, we can simultaneously examine the impact of master statuses, personality traits, and social cognitive competencies on ego network size, structure (i.e., density), and composition (i.e., diversity). We find that all classes of predictors influence our ego networks, though in different ways, and point to new avenues for research into human sociability.

How does collaboration affect researchers’ positions in co-authorship networks?

Abstract Collaboration usually has a positive effect on researchers’ productivity: researchers have become increasingly collaborative, according to recent studies. Numerous studies have focused on enhancing research collaboration by recommendation technology and measuring the influence of researchers. However, few studies have investigated the effect of collaboration on the position of a researcher in the research social network. In this paper, we explore the relationships between collaboration and influence by social analytical methods, which are pertinent to analyzing the network structure and individual traits. We evaluate three aspects of the researchers’ influence: friendship paradox validation, social circle, and structure of a researcher's ego network. Furthermore, the ”six degrees of Bacon number” theory, generalized friendship paradox, and triadic closure theory are introduced to support our analysis. Experimental results show that collaboration can help researchers increase their influence to some extent.

Sacred Alters: The Effects of Ego Network Structure on Religious and Political Beliefs

Does who we know impact how strongly we believe? The claim seems reasonable, but research linking social network composition to political beliefs has produced conflicting results. We argue that methodological differences in measuring close ties can explain these inconsistencies and that work on the sacred umbrella provides a useful framework for moving forward. The sacred umbrella argues that when people close to you share your religious beliefs, you are shielded from doubt and uncertainty; perhaps the same mechanism also operates for political views. Using General Social Survey data, we find that religious or political discussion network heterogeneity predicts the strength of beliefs associated with one’s religion or political party, respectively. A religiously or politically homogenous network appears to strengthen certain values associated with the belief system.

Designing Informal Networks: Implications for Management Theory and Practice

Most of the existing research in the origins and evolution of social networks conceptualizes social ties as arising either from spontaneously occurring interactions (e.g., through friends of friends) or from strategic behavior carried out by network participants interested in creating beneficial ego-network structures (e.g., self-selection into brokerage positions). But despite the apparent contrast between these two views, it is possible to notice an irony of great theoretical importance: both deliberately downplay the possibility of having informal networks by organizational design, where social ties unfold based on an organizational “blueprint” delineating principles and creating conditions that might favor the emergence of desired social structures. The purpose of this symposium is to bring together scholars interested not only in exploring different ways in which the configuration of informal networks can be influenced by organization design, but also in understanding how the design of informal structures affects organizational functioning. Drawing on research on multiple areas, presentations will examine principles of organization design and social networks, note their relationship with one another, and explore their link with different types of organizational outcomes. Dysfunctional Turnover in a Corporate Merger: The Role of Job Continuity and Social Network Change Presenter: Neha Shah; Rutgers U. Presenter: Meredith Lauren Woehler; Vanderbilt U. Presenter: Theresa M. Floyd; U. of Montana Presenter: Joshua Marineau; North Dakota State U. Presenter: Wookje Sung; Hong Kong Baptist U. Presenter: Jesse Michael Fagan; U. of New Mexico Presenter: Giuseppe Labianca; U. of Kentucky Sourcing (in)Tangible Resources through (in)Formal ties: Insights from African Healthcare Presenter: Aline Gatignon; The Wharton School, U. of Pennsylvania Presenter: Julien Clement; Stanford U. Presenter: Luk Van Wassenhove; INSEAD Innovation and Stasis in Small-World Networks Presenter: Spiro Maroulis; Arizona State U. Presenter: Maxim Sytch; U. of Michigan A Quasi-Experiment on the Effects of Monetary Incentives on Informal Knowledge Sharing Presenter: Giuseppe Soda; Bocconi U. Presenter: Alessandro Iorio; Carnegie Mellon U. Presenter: Brandy Aven; Carnegie Mellon U.

Creativity and Networks: addressing the role of individual cognition.

The study of individual creativity has abundantly shed light on the advantages individuals derive from their relational capital. The debate has mostly investigated the kinds of ego-network structures and social ties, namely weak or strong ties, which provide information, support and other resources that individuals can tap into to increase their own creativity. Such a debate however has overlooked how individuals cognize their network, departing from a silent assumption that individuals know what relations they and other establish. Such an absence is particularly salient in light of mounting evidence of the incapacity of individuals to accurately cognize their network. What does that entail on the creativity of individuals? Does the accurate cognition of the social network positively influence individual creativity, as individuals know where to get what they need? The study seeks an answer by administering a questionnaire to and then interviewing all employees and supervisors of a small company in the media industry. Results show that the belief of being part of a cohesive network of advice seeking relationships positively influences individual creativity, and that accuracy of the network cognition decreases individual creativity. Taken together, our results show that creativity draws mostly on motivational and psychological aspects rather than a rational and calculative behavior. Our results contribute to the literatures of social network and creativity, and cognitive networks.

An exploration of the Facebook social networks of smokers and non-smokers.

BackgroundSocial networks influence health behavior, including tobacco use and cessation. To date, little is known about whether and how the networks of online smokers and non-smokers may differ, or the potential implications of such differences with regards to intervention efforts. Understanding how social networks vary by smoking status could inform public health efforts to accelerate cessation or slow the adoption of tobacco use.ObjectivesThese secondary analyses explore the structure of ego networks of both smokers and non-smokers collected as part of a randomized control trial conducted within Facebook.MethodsDuring the trial, a total of 14,010 individuals installed a Facebook smoking cessation app: 9,042 smokers who were randomized in the trial, an additional 2,881 smokers who did not meet full eligibility criteria, and 2,087 non-smokers. The ego network for all individuals was constructed out to second-degree connections. Four kinds of networks were constructed: friendship, family, photo, and group networks. From these networks we measured edges, isolates, density, mean betweenness, transitivity, and mean closeness. We also measured diameter, clustering, and modularity without ego and isolates. Logistic regressions were performed with smoking status as the response and network metrics as the primary independent variables and demographics and Facebook utilization metrics as covariates.ResultsThe four networks had different characteristics, indicated by different multicollinearity issues and by logistic regression output. Among Friendship networks, the odds of smoking were higher in networks with lower betweenness (p = 0.00), lower transitivity (p = 0.00), and larger diameter (p = 0.00). Among Family networks, the odds of smoking were higher in networks with more vertices (p = .01), less transitivity (p = .04), and fewer isolates (p = .01). Among Photo networks, none of the network metrics were predictive of smoking status. Among Group networks, the odds of smoking were higher when diameter was smaller (p = .04). Together, these findings suggested that compared to non-smokers, smokers in this sample had less connected, more dispersed Facebook Friendship networks; larger but more fractured Family networks with fewer isolates; more compact Group networks; and Photo networks that were similar in network structure to those of non-smokers.ConclusionsThis study illustrates the importance of examining structural differences in online social networks as a critical component for network-based interventions and lays the foundation for future research that examines the ways that social networks differ based on individual health behavior. Interventions that seek to target the behavior of individuals in the context of their social environment would be well served to understand social network structures of participants.

Attention Biases in Social Networks

This study examines how people connecting to brokers can receive high performance ratings in the workplace. Using survey data on communication networks among software engineers at a mobile service company, I find that independent of their ego network structure, individuals who pay more attention to brokers than to other communication partners receive higher performance ratings on project-based work than individuals who pay little (or no) attention to the brokers among their work colleagues. Although individuals should pay attention to brokers if they wish to receive higher performance ratings, I also find that people typically pay less attention to brokers than they do to other communication partners. The juxtaposition of these findings suggests that individuals have a systematic attention bias in social networks – that they do not normally allocate their attention in ways that benefit their performance ratings. I discuss the implications of these findings for research on attention and social networks in an organization.

Real estate business model innovation and the impact of ego network structure

PurposeThis paper aims to analyze how a real estate business model innovation developed in a real estate network, with a special focus on the relationship between ego network structure and the innovative development of the business model.Design/methodology/approachThe paper is a single case study of a Swedish real estate network of 38 actors. The data were collected at the individual actor level using multiple sources: 12 semi-structured in-depth interviews, 94 min of meetings and 28 written contracts. The empirical findings resulted in four propositions.FindingsThis study demonstrates that it was primarily the building user who was behind the innovative development of the real estate business model innovation, whereas the real estate company acted as a network hub and network resource coordinator. The ego network structures significantly affected the outcome.Practical implicationsReal estate companies should act as hubs, coordinating all the network actor resources the building user needs in the value-creation process. To be effective hubs, the representatives of real estate companies must create extensive personal and open ego networks to acquire central network positions.Originality/valueFew studies examine business model innovation, particularly in the real estate context. Though large real estate businesses usually operate in the networks of various actors, analyses based on the network perspective are also lacking. This case study builds a valuable understanding of how network processes in real estate networks can be used as tools to foster real estate business model innovation, which in turn can lead to more competitive real estate companies and building users.

EgoComp: A node-link-based technique for visual comparison of ego-networks

Analysis of ego-networks is a critical research problem when analyzing large-scale social networks, as an ego-network represents the social circle a person actually contacts with. One of the core tasks in ego-network analysis is visual comparison, which includes edge comparison and node comparison. Although various works have been done to support comparing normal networks and ego-networks, intuitive node comparison of two ego-networks is still challenging. In this article, we propose egoComp, an intuitive and expressive visualization technique, to analyze the node difference between two ego-networks. To preserve the latent structure of ego-network and lay emphasis on intuitiveness, our design is node-link-based (radial tree layout) and uses a side-by-side method to compare ego-networks. We design a novel storyflow-like graph layout to reveal the relationship of two ego-networks at the individual node level. Furthermore, three different layout algorithms, including origin, greedy, and assignment algorithms, are proposed to meet different user requirements. We demonstrate the effectiveness of our system through case studies and a user study and then discuss the limitations thoroughly as well as the possible solutions and potential future work.

Reaching and Acquiring Valuable Resources: The Entrepreneur's Use of Brokerage, Cohesion, and Embeddedness

Entrepreneurs have two key aims in managing their ego–networks: extending reach to valuable resources and facilitating resource acquisition. This study provides a synthesis of the brokerage, cohesion, and embeddedness literatures to develop and present a multilevel theoretical framework and analytical model that treat both aims jointly. It makes three contributions. First, it highlights a trade–off that entrepreneurs face in allocating their available networking time and energy while pursuing these two aims. Second, it explores the central role of two types of embeddedness—relational and structural—in resolving this trade–off. Third, it helps entrepreneurs decide when to embed a particular dyadic connection relationally or structurally. We show that entrepreneurs can better balance their dual aim by structurally embedding some ties rather than trying to relationally embed all. The resultant network is one that meshes characteristics of brokerage and cohesive ego–network structures.

Ego network structure in online social networks and its impact on information diffusion

In the last few years, Online Social Networks (OSNs) attracted the interest of a large number of researchers, thanks to their central role in the society. Through the analysis of OSNs, many social phenomena have been studied, such as the viral diffusion of information amongst people. What is still unclear is the relation between micro-level structural properties of OSNs (i.e. the properties of the personal networks of the users, also known as ego networks) and the emergence of such phenomena. A better knowledge of this relation could be essential for the creation of services for the Future Internet, such as highly personalised advertisements fitted on users’ needs and characteristics. In this paper, we contribute to bridge this gap by analysing the ego networks of a large sample of Facebook and Twitter users. We show that micro-level structural properties of OSNs are interestingly similar to those found in social networks formed offline. In particular, online ego networks show the same structure found offline, with social contacts arranged in layers with compatible size and composition. From the analysis of Twitter ego networks, we have been able to find a direct impact of tie strength and ego network circles on the diffusion of information in the network. Specifically, there is a high correlation between the frequency of direct contact between users and her friends in Twitter (a proxy for tie strength), and the frequency of retweets made by the users from tweets generated by their friends. We analysed the correlation for each ego network layer identified in Twitter, discovering their role in the diffusion of information.