Prasad Balkundi

Organization and Human Resources, University of Buffalo

The Negative Side of the Social Ledger: A Meta-Analysis

SONIC Lab is proud to welcome Prasad Balkundi of the University of Buffalo. Dr. Balkundi will speak on Wednesday, April 18th, 2017 at 10 AM in Frances Searle Building, Room 1-483. Please contact Dr. Michael Schultz with any questions.

Abstract:

Despite a resurgence of research on negative ties in social networks, a comprehensive understanding of negative and positive has yet to be provided. Incorporating evidence from prior 163 independent samples we examine whether the initiation of positive and negative relationships (i.e., out-degree) or the reception of positive and negative relationships (i.e., in-degree) is more impactful to the focal employee’s effectiveness. Furthermore, to address the negative asymmetry hypothesis in social networks, we compare the relative importance of positive versus negative work relationships while holding the directionality constant. This meta-analytic review makes five contributions to theory on negative and positive social networks by (a) demonstrating the undermining impact of negative ties on performance and job attitudes; (b) providing information on the negative asymmetry hypothesis within social networks to reveal that negative ties occur less frequently than positive ties and that any asymmetry effects depend on the relative number of negative ties to positive ties in the context; (d) distinguishing between haters (senders of negative ties) and jerks (receivers of negative ties) to illustrate that haters have worse job attitudes than jerks, but the two do not differ on performance; and (e) providing positive and negative affect as antecedents to negative ties. Implications of these findings along with study limitations and future research directions are discussed.​

Gianluca Carnabuci

Organizational Behavior, ESMT Berlin

Good For One But Bad For Most? How Intra-Organizational Networks Impact Innovative Performance At The Inventor And Firm Level

SONIC Lab is proud to welcome Gianluca Carnabuci of ESMT Berlin. Dr. Carnabuci will speak on Wednesday, April 26th, 2017 at 10 AM in Frances Searle Building, Room 1-483. Please contact Dr. Michael Schultz with any questions.

Abstract:

Extant organizational research suggests that R&D scientists tend to be more productive (i.e., they generate more impactful innovations) when they occupy a central position within their organization’s intra-organizational collaboration network. Does this imply that an organization’s overall innovative performance would increase if the organization encouraged its R&D scientists to pursue more central network positions? We address this question using a multi-level panel dataset describing the evolving intra-organizational networks of 140 semiconductor firms, as well as the individual network position of each of their R&D scientists. We proceed in three steps. First, we confirm that network centrality does enhance scientists’ innovative performance within our empirical sample, even after controlling for unobserved individual- and organizational-level differences. Second, we simulate how the overall intra-organizational network of an organization would change if it enacted two distinct norms of collaboration, each encouraging scientists to increase their network centrality. We find that norms of “diffuse” collaboration increase network cohesion, whereas “star-centric” ones increase network centralization. Third, we study how these network-level properties affect innovative performance among our semiconductor firms. We find that network cohesion enhances organizational-level innovative performance only under conditions of high knowledge diversity, while network centralization always reduces it. These findings show that scientists’ pursuit of network centrality may have opposite performance effects at the individual- and organizational-level. A counterintuitive normative implication is that, under quite broad conditions, organizations would enhance their innovative performance by discouraging (rather than encouraging) their R&D personnel from increasing their centrality within the intra-organizational network.

N. Sadat Shami

Director, Center for Engagement and Social Analytics IBM

The Application of Social Analytics to Understand and Improve Organizational Outcomes

SONIC Lab is proud to welcome N. Sadat Shami of IBM. Dr. Shami will speak on Monday, February 26th, 2017 at 10 AM in Frances Searle Building, Room 1-483. Please contact Dr. Michael Schultz with any questions.

Abstract:

The increased adoption of social media in the enterprise provides an opportunity for organizations to receive real-time feedback from employees on organizational issues. Enterprise social media provides a platform for employees to express their thoughts and opinions on organizational programs, policies, and strategies through unstructured text in status updates, blogs, online community forums etc. Such textual data can be mined to generate insights about the employee experience. Research has shown that organizations that take into consideration employee feedback in organizational decision-making are more productive, and have employees that are more engaged with the organization. In this talk, he will first describe the design and use of Social Pulse – a tool to make sense of large- scale social media text generated by employees of an organization while preserving privacy. He will then describe how social media text mined by Social Pulse, combined with an organization’s hierarchical network structure can be used in statistical models to predict outcomes of interest to an organization, focusing on the particular case of employee engagement, and how it spreads in an organization.

Johan Ugander

Management Science & Engineering Stanford University

Ruffled Feathers: Trait inference beyond homophily

SONIC Lab is proud to welcome Johan Ugander of Stanford University. Dr. Ugander will speak on Tuesday, February 6th, 2017 at 10 AM in Frances Searle Building, Room 1-483. Please contact Dr. Michael Schultz with any questions.

Abstract:

The observation that individuals tend to be friends with people who are similar to themselves, commonly known as homophily, is a prominent and well-studied feature of social networks. While homophily describes a bias in attribute preferences for similar others, it gives limited attention to variability. In this work, we observe that attribute preferences can exhibit variation beyond what can be explained by models of homophily. We call this excess variation monophily to describe the presence of individuals with extreme preferences for a particular attribute possibly unrelated to their own attribute. We observe that monophily can induce a similarity among friends-of-friends on a network without requiring any similarity among friends. In order to independently simulate homophily and monophily in synthetic networks, we contribute a new model of social network structure that we call the overdispersed stochastic block model (oSBM), an extension of the classical stochastic block model. We use this model to demonstrate how homophily-based methods for predicting attributes on social networks based on friends, “the company you keep,” are fundamentally different from monophily-based methods based on friends- of-friends, “the company you’re kept in.” To illustrate the differences between homophily and monophily-based prediction we place particular focus on predicting gender, where homophily can be weak or nonexistent in practice. These findings offer an alternative perspective on network structure and attributes in general and prediction in particular, complicating the already difficult task of protecting privacy on social networks. This is joint work with Kristen Altenburger.

PDF version of the schedule:

SONIC Speaker Series 2017-2018

Esther Sackett

Kellogg School of Management, Northwestern University

Expertise Awareness in Multi-Organizational Collaboration: The Role of Goal Awareness

SONIC Lab is proud to welcome Esther Sackett of the Northwestern University. Dr. Sackett will speak on Thursday, December 7th, 2017 at 2 PM in Frances Searle Building, Room 1-483. Please contact Dr. Michael Schultz with any questions.

 Abstract:

Multistakeholder alliances typically have dual purposes that are often in tension – 1) pooling knowledge and resources toward a collaborative goal, and 2) engaging in knowledge transfer by leveraging knowledge and resources for each individual organization’s benefit. However, research has also demonstrated that these dual purposes are also quite intertwined, as members’ sustained engagement in the alliance over time depends on the perceived value of participation in terms of meeting their own organization’s needs. Inherent in the structure of multistakeholder alliances and their dual purposes is an implicit assumption: that the distributed expertise in a multistakeholder alliance is available for the pursuit of both collaborative goals and knowledge transfer. However, each of these goals may actually require access to different sets of expertise. Thus, a potentially overlooked mechanism for overcoming the challenges of balancing the dual purposes of multistakeholder alliances may reside in the relationships between the goals being pursued and the mechanisms for accessing the expertise needed to address them. Building on the framework of transactive memory systems, I use a qualitative approach to explore the factors that contribute to the development of expertise awareness, goal awareness, and the relationship between them in a multistakeholder alliance in the healthcare sector.

Demographics in Social Networks: Usage Differences, Content Spread, and Homophily

Abstract

 

How do demographic attributes affect network structure and content spread? In this talk, I’ll present attempts to address this question using a demographically annotated data set for 350K Twitter users in New York. For each user, their gender, age and race has been inferred from their profile picture using Face++. I’ll start by  showing that population-level differences in hashtag usage are intuitive, such as African Americans being more likely to use #blacklivesmatter, women more likely to use #makeup, and young people more likely to use #growingupwithsiblings. Taking ideas previously studied in the context of web search, we then look at  which demographic groups are generally first – or last – to use new hashtags. Here we find that, e.g., new music-related hashtags tend to originate from African American users, whereas new baseball hashtags come from white men. Looking at the topic of “algorithmic bias”, we show that the “what’s trending” tends to favor the majority group, potentially creating hurdles for minority content to benefit from system-induced feedback. Finally, I’ll show results resulted to racial link asymmetries, potentially indicating latent discrimination.

The work presented is joint work with Jisun An at QCRI, and several members of the Social Dynamics Lab (http://sdl.soc.cornell.edu/) at Cornell University, including Michael Macy, George Berry, Minsu Park and Chris Cameron. The research varies in terms of doneness from “medium well” to “rare”. More information on past projects at http://ingmarweber.de/publications/.

Biography

Ingmar Weber is a senior scientist in the Social Computing Group at the Qatar Computing Research Institute (QCRI) in Doha. He uses large amounts of online data to address research questions of societal relevance related to (i) lifestyle diseases, (ii) societal fragmentation, and (iii) international migration. He has published over 100 peer-reviewed articles (http://ingmarweber.de/publications/) and his work is frequently featured in popular press (https://www.google.com/search?tbm=nws&q=%22ingmar+weber%22). Since April 2016 he’s been selected as an ACM Distinguished Speaker.

How do Brokers Broker?

Tertius Gaudens, Tertius Iungens, and the Temporality of Structural Holes

Abstract

Organizational network research has demonstrated that multiple benefits accrue to people occupying brokerage positions. However, the extant literature offers scant evidence of the process postulated to drive such benefits –information brokerage– and therefore leaves unaddressed the question of brokers broker. We address this gap by examining the information-brokerage interactions in which actors engage. We argue that the information-brokerage strategies of brokers differ in three critical ways from those of actors embedded in denser network positions. First, brokers more often broker information via short-term interactions with colleagues outside their network of long-term relationships, a process we label “unembedded brokerage.” Second, when they engage in unembedded brokerage, brokers are more likely than are actors in dense network positions to intermediate the flow of information between the brokered parties, consistent with a tertius gaudens strategy. Conversely, and third, when they broker information via their network of long-term ties (embedded brokerage), brokers are more likely than are densely connected actors to facilitate a direct information exchange between the brokered parties, consistent with a tertius iungens strategy. Using a relational event model, we find support for our arguments in an empirical analysis of email communications among employees in a medium-sized, knowledge-intensive organization, as well as in a replication study. The theory and evidence we present advance a novel, temporal perspective on how brokers broker, which reconciles structural and process views of network brokerage. Our findings substantiate the notion of brokers as a dynamic force driving change in organizational networks, and they help to integrate within a unitary explanatory framework tertius iungens and tertius gaudens views of brokerage.

Biography

Eric Quintane is an associate professor of management at the School of Management, The University of Los Andes, Bogota, Colombia. He received his Ph.D. from the University of Melbourne (Australia). His research interests include dynamics of organizational networks, temporality of social processes, creativity and innovation.