Call for Papers and Abstracts for our Workshop at the 13th ACM Web Science Conference

Call for Papers and Abstracts:  



The Near Future of Work: Supporting Digital and Remote Collaboration in COVID and Beyond 

A Workshop at the 13th ACM Web Science Conference (WebSci 2021) 

June 21st or June 22nd 


The COVID-19 pandemic has provided us an opportunity to participate in a global “beta-test” of web-only-based remote work. The workshop will reflect on the changing nature of work, identify factors that explain these changes, and how we can learn from the “new” normal to prepare for a better “next” normal. By doing so this workshop seeks to facilitate multidisciplinary dialog as well as theory and research examining challenges and opportunities stemming from digital and remote work on the Web. Topics relevant to this workshop include, but are not limited to: remote work, virtual teaming, enterprise social media (ESM), computer-supported cooperative work, digital platforms, human-AI teaming, work in the gig economy, crowdsourced labor, work-life balance in the digital age, the well-being of remote workers, and workplace communication technology. We especially welcome findings of remote work and digital collaboration that are relevant in the aftermath of COVID-19 (but not necessarily relying on COVID-19 related data). 


Important Dates:  


  • Full papers – Submission deadline: April 23rd, Camera-ready papers: May 16th 
  • Abstracts for lightning talks – Submission deadline: May 17th  


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5 presentations at #SIOP21?!?! What a blast!

We had a blast presenting at The 36th Society for Industrial and Organizational Psychology (SIOP) Annual Conference #SIOP21! Congratulations to our grad student Brennan Antone and lab director Noshir Contractor for a successful presentation and panel. We also want to give a HUGE SHOUTOUT to our colleagues Leslie DeChurch, Suzanne Bell, and all our team from ATLAS and Teams Lab — Great posters, presentations, and panel overall!

A complete list of our presentation’s citations can be found below: 
Antone, B., DeChurch, L.A., Morton, D., Bell, S., & Contractor, N. (2021, April 15-17). A Network-Based Method to Recommend Optimal Team Compositions for Space Exploration [Conference Presentation]The 36th Society for Industrial and Organizational Psychology (SIOP) Annual Conference, Virtual.
Contractor, N. (2021, April 15-17). The Future of Team Composition: Robots, Cyber Teams and Decision-Support Systems [Panelist]. The 36th Society for Industrial and Organizational Psychology (SIOP) Annual Conference, Virtual.
Contractor, N. (2021, April 15-17). Human–Agent Teams Will Revolutionize the Future of Work: Implications for Industrial-Organizational Psychology [Panelist]. The 36th Society for Industrial and Organizational Psychology (SIOP) Annual Conference, Virtual.
Chackoria, J.J., Nyberg, B.B., Vasquez, M., Bell, S.T., DeChurch, L.A., Contractor, N., Gushin, V., & Vinokhodova, A. (2021, April 15-17). Perceived Similarity Predicts Viable Relationships and Team Performance [Poster Presentation]. The 36th Society for Industrial and Organizational Psychology (SIOP) Annual Conference, Virtual.
Johnson, M., Gokhman, I., DeChurch, L.A., Bell, S.T., Contractor, N. (2021, April 15-17). Talking About Mars: Team Communication Dynamics and Decision Quality in Space Crews [Poster Presentation]. The 36th Society for Industrial and Organizational Psychology (SIOP) Annual Conference, Virtual.
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SONIC Faculty Affiliate will also attend #Networks2021

Excited to share that our SONIC Faculty Affiliate Moses Boudourides has 4 abstracts accepted at #Networks2021! Congratulations to authors Mark McGown, Maryam Khalili, Yasmin Abdelghaffar, and Moses Boudourides.


For more info about Networks 2021, click here.

For more info about our abstracts, please see below:


Networks of Co-Occurring Proper Nouns in Anne Frank’s Diary

Authors: Moses Boudourides and Mark McGown


This work aimed to examine Anne Frank’s ‘The Diary of a Young Girl’ (Bantam Books 1994) from the perspective of network science. Data was first collected from The Internet Archive as a raw text file, and sentiment as well as proper nouns were extracted using the NLTK and spaCy libraries in Python. The relationships of sententially co-occurring proper nouns in the overall text were then compiled and analyzed using the NetworkX library in Python. Community partitioning, assortativity analysis, ego-centric subgraphs, cliques, and centrality indices of the networks of proper nouns were studied in order to discover the structural entanglement and clustering of co-occurrent terms. Communities were discovered amongst these proper nouns that showed correlation with the relationships between them. Significant shifts in sentiment both between community partitions as well as temporally were found. The role of each proper noun was found to correlate with its relative ranking in specific measures of centrality. This analysis suggested that data science and network analysis are adept tools at aggregating meaning from text documents. The findings of this project would be of interest to scholars of the humanities and digital humanities, data scientists studying text mining and text analytics, social scientists and psychologists working on biographical narrative interpretive methods, and historians of WWII intellectual and social events.

Networks of affect in COVID19 positive subreddit posts

Authors: Moses Boudourides and Maryam Khalili


Our aim is to explore from both data- and network-analytic point of view the dynamics of affect developing in posts in the COVID19positive subreddit. We have been collecting threads of discussions on this subreddit from the date that they have started appearing on March 14 until October 2020. From these discussions, using standard techniques of NLP of POS tagging, we were able to extract verbs in stemmed form. Based on the essential principles of linguistics, we were partitioning verbs into four socio-linguistic categories: action, doxastic, emotive and sensory verbs. Our research hypothesis is that the strongly affective features of the discourse developed in social media around the current COVID19 pandemic entail an increasing use of verbs in the categories that we are focusing. Moreover, these verbs appear to co-occur in sentences the sentimental (analytic) score of which tends to increase as the current situation happens to aggravate even more. For this reason, we are studying temporal (longitudinal) networks of sententially co-occurring verbs in the COVID19positive subreddit in order to trace the discursive ways in which feelings, concerns, opinions and emotions are embroiled, discussed and unfold the experiential narrative of the pandemic inside social media.

The Role of Media Susceptibility in a Model of Influence on the Ideology of Actors in Social Networks

Authors: Moses Boudourides and Yasmin Abdelghaffar


We are considering here a model of social influence based on interactions between people and media. In particular, we are considering a bounded-confidence model, which consists of media and non-media actors being nodes of a directed graph such that each node was assigned an ideology, as a real valued number in a given interval. At each time-step, the ideologies of non-media nodes would be updated based on their interactions with other media and non-media nodes. The concept of media susceptibility is introduced, a parameter that controls how much influence a node receives from media and from other non-media nodes, with the extremes being that nodes are either not influenced by media, or not influenced by other non-media nodes. Using the number of steady states as a metric for the polarization of the network, we have demonstrated that the more individuals relied on media, the greater the polarization effect within the network.

Mixing and Segregation of Authors’ Gender, “Culture” and Open Access in Publications on Digital Humanities from 2000 to 2020

Authors: Moses Boudourides


The aim of this contribution is to stress the significance of measuring the inhering structural mixing that exists in heterogeneous networks. I will do this over a bibliographic dataset extracted from the Web of Science (WoS), which consists of publications in the topic of Digital Humanities (DH) from 2000 to 2020. The basic methodological orientation in my study is focusing on temporal (longitudinal) bipartite hypergraphs with vertices being various fields (columns) extracted from a bibliographical dataset. Working on the co-authorship network (but also on other dual networks, like the co-publication network, the co-research-area network and the word-net of keywords in the publications abstracts), I intend to determine the way and the extent of how homophily/assortativity/segregation or mixing/disassortativity/desegragation of certain attributes (like authors’ gender, publications’ research areas and Open Access type) are structuring the patterns of academic publishing on Digital Humanities.

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Welcome to SONIC, Megan & Brian!

SONIC is excited to introduce Megan Chan and Brian Bogert. Megan and Brian are joining SONIC as a first-year Ph.D. student in the Industrial Engineering and Management Sciences (IEMS) program this coming Fall.

Megan Chan received her Bachelor of Science in Industiral Engineering from California Polytechnic University, San Luis Obispo. Upon graduation, she worked as a technology consultant at Protiviti, where she provided enterprise software implementation technical and advisory services. Her research interests include organizational communication, optimization, network analysis, and data science. Outside of work, she loves picking up new skills. She enjoys dance (ballet, contemporary, hip hop) and martial arts. She is passionate about sustainability, diversity, equity, and inclusion, and she is striving to be an ally, a mentor, and a leader wherever she can.

Brian Bogert will be receiving his Bachelor’s from Virginia Polytechnic Institute & State University. As a double major in Industrial & Systems Engineering and Political Science, Brian is a huge proponent of interdisciplinary studies. He is especially interested in the science behind teams and how it relates to the public sector. One dream he has is to incorporate decision analysis and operations research to improve efficiency within the federal bureaucracy. Outside of school, he loves listening to music, watching baseball, and looking up random facts about roller coasters or whatever else he feels like searching.

Both Megan and Brian are excited to start their journey in Academia with SONIC — and we’re very excited to have them on board!

SONIC would also like to wish our SONIC Alumni the best of luck with their new careers! 

Balint Neray recently concluded his post-doctoral position at SONIC in February. At SONIC, Balint worked on several projects, including the Social Influence, Family Planning in Kenya, as well as the Hierarchical Multidimensional Network-based Approach for Multi-Competitor Product Design. Balint’s work focuses on the analysis of ego-centric networks and how it is essential in understanding various social phenomena. After SONIC, Balint is joining Facebook as a Research Scientist

Last month, Kyosuke Tanaka successfully defended his dissertation. At SONIC, Kyosuke heads the 6DoS (6 Degrees of Separation) Project and worked on Threadless and the SCALE Project. Kyosuke’s work focuses on understanding how and why people perceive, activate, and leverage their social contacts. After SONIC, Kyosuke is joining the Department of Management at Aarhus University for a 3-year postdoc on a project titled Patterns of Interaction: Emergence and Consequences

The SONIC Research Group thanks Balint and Kyosuke for all of their hard work during their time at SONIC and wishes them all the best in their career!

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Accepted to Networks 2021!!!

Excited to share that we have 3 abstracts accepted at #Networks2021! Congratulations to authors Kyosuke Tanaka, Xiangheng Chen, Aida Baimenova, Neelam Modi, Alina Lungeanu, Leslie DeChurch, and Noshir Contractor 👏


For more info about Networks 2021, click here

For more info about our abstracts, please see below: 

Knowing is not Enough: How Network Awareness and Acuity are Associated

Authors: Kyosuke Tanaka, Leslie DeChurch, and Noshir Contractor


Network research has shown that accurate awareness of a social network brings network advantages (e.g., informal power, faster promotion, and higher performance) to members in groups and organizations. This is because it assumes that those who accurately perceive ties among others within their social network (i.e., high network awareness) can also navigate the social world with more precision, which we call network acuity. However, it is unclear whether this assumption holds true or it is the other way around—network acuity impacts network awareness.

Here, we tested this assumption using cross-lag panel modeling on longitudinal network data from a laboratory experiment where 405 participants (57% female) who were in 23 pre-existing networks engaged in five rounds of a three-minute network routing task. The network routing task was developed based on the notion of Milgram’s small-world experiment where participants within a group select a fixed number of contacts and route messages via these contacts to get them to the target person. We measured network acuity as an individual-level metric of the proportion of times the individual used the shortest path contact toward the target person per round. Each group was randomly assigned to either a workload available condition or non-available condition. In the workload available condition, participants were able to access their contacts’ workload (the number of messages waiting in their inbox to be routed). We hypothesize that the availability of this information impacts how they perceive and use their contacts. We also asked participants to report their perceptions of whom others chose as their contacts to route messages in each round. We measured network awareness based on their accuracy of the actual routing network. Additionally, we collected self-report surveys about their pre-existing social network ties within their group as well as their individual characteristics (e.g., the Big Five personality traits, self-monitoring, and cognitive ability).

Our results show that in contrast to the aforementioned intuition, high network acuity positively predicts network awareness instead of the other way around. This suggests that effective navigation of their social networks by individuals shapes their accurate awareness of the network. We also find that women and those who are popular in the pre-existing social network tend to be higher on both network awareness and acuity. In other words, both dispositional (gender) and positional (popular in the network) characteristics play a vital role in accurate perceptions and navigation of the network. Further, high conscientiousness and cognitive ability are associated with high network awareness, while high self-monitoring is related to high network acuity. Taken together, our findings suggest that knowing the network structure accurately is not enough for people to effectively navigate the network as needed, especially under pressure.


Network Routing Task Performance among Space Crew with Mission Support in Space Multiteam Systems

Authors: Kyosuke Tanaka, Xiangheng Chen, Aida Baimenova, Leslie DeChurch, and Noshir Contractor


In long-distance space missions, communication delays (CD) between space crews and ground mission control (MC) become longer as crews get farther away from earth, thereby setting a higher demand for effective information sharing under resource constraints. Due to “bandwidth constraints,” space crews and mission support need to leverage their indirect contacts (i.e., contacts’ contacts) to route information optimally. The lack of awareness of one’s network contacts could result in failure of information sharing, contributing to the risk of accidents during space missions. However, what factors play a role in predicting such awareness has not yet been studied.

Here, we introduce the concept of network acuity to characterize the individual’s ability to effectively use the network awareness as needed. It is measured by the extent to which an individual can identify the direct contact who is on the shortest path to their indirect, destination contact. We collected data from NASA’s Human Exploration Research Analog (HERA), Campaigns 3, 4, and 5, and Russia’s Nezemnyy Eksperimental’nyy Kompleks (NEK) SIRIUS-18/19, using Project RED Relay—a web-based simulation portal that enables space crews and MC to engage in network routing as part of a multiteam system (MTS) task. Each participant was instructed to choose only 2 direct contacts among 11 others (simulating bandwidth constraints) and aim for routing information to destinations with which they were only indirectly connected via the fewest steps. In total, we analyzed 97, 12-member network sessions (81, 4-crew-8-MC sessions for HERA and 16, 6-crew-6-MC sessions for NEK), each assigned with different CD  conditions (180-second, 60-second, or zero for HERA and 30-second or zero for NEK).

Our results show that factors, such as CD and the Big Five personality traits, can impact an individual’s network acuity. We found that the network acuity of space crews is significantly higher than that of MC in both NEK and HERA Campaigns 4 and 5, but not Campaign 3. Further, we found a negative relationship between the network acuity and CD in MC members, but such a relationship is not significant among space crews. In addition, our study of the HERA and NEK data shows that space crews’ network acuity was negatively associated with conscientiousness in both Campaigns 3 and 4, whereas it was positively associated with traits of openness to experience, agreeableness, and neuroticism in Campaign 4, but not in Campaign 3. Overall, our results demonstrate the need to consider key personality characteristics in selecting space crews to maximize network acuity. This will be key in mitigating failures in information sharing within multiteam systems (MTS) and the associated risks. We anticipate our study to be a starting point for more research into determining the optimal level of the Big Five personality traits in terms of information sharing, as well as identifying more factors impacting network acuity within MTS under different CD conditions.


Hard to recruit but worth trying: Searching for cross-boundary collaborations in science

Authors: Neelam Modi, Alina Lungeanu, Leslie DeChurch, and Noshir Contractor


“We hail individual geniuses, but success in science comes through collaboration.” (Farrar, 2017)

Research that looks back on collaboration that produced the greatest scientific breakthroughs highlights boundary-crossing collaboration. By boundaries, we mean disciplines, organizations, cultures, professions, and demographics. Although collaboration has long been important in science, the rapid specialization of knowledge across domains is making collaboration essential. This is especially true in biomedical research.

The National Institutes of Health (NIH) makes substantial investments to encourage cross-boundary team science in biomedicine. This research project focuses on an exemplar support mechanism, the NIH’s Clinical and Translational Science Award (CTSA) Program. With a $500 million annual budget, the CTSA Program is designed to facilitate collaborations between the “(laboratory) bench and the (clinical) bedside” as well as streamline multi-site studies. In particular, the CTSA’s Pilot Grant program, which provides seed funding to hundreds of teams each year, seeks to incentivize new cross-boundary teams that bring together basic scientists and clinical researchers, junior faculty and experienced mentors, and researchers from different departments or institutions.

While cross-boundary collaboration in team science has demonstrated benefits, research also suggests they are unlikely to form, and when they do, are prone to coordination costs. Our study seeks to advance the Science of Science by understanding the assembly of cross-boundary teams who conduct clinical and translational science. We leverage both social network theories and research on groups and teams to answer two research questions: (RQ1) Do funding investments shift team composition in favor of cross-boundary collaboration? and (RQ2)

Which cross-boundary combinations are the most effective?

To answer these research questions, we use archival data about researchers submitting proposals to one Midwestern University CTSA’s Pilot Grant Program between the years of 2014 and 2019. We examine 432 proposal submissions in total, of which 323 were team proposals (having 2 or more researchers). This results in 288 researchers listed as Co-PIs on team proposals, of whom 243 did not have their proposals awarded, 7 had both awarded and un-awarded proposals, and 38 had awarded proposals. We extract demographics, education and employment information, and organization and department affiliation from the university’s internal database. Additionally, we use publication data from the Web of Science database to construct bibliometric information (including publications, co-authorship and co-citation relations) for the entire population of researchers who submitted grant proposals.

We use Exponential Random Graph Models to assess factors influencing the assembly and success of grant proposal teams. Preliminary results show that in general cross-boundary collaboration are not likely among teams submitting proposals, but cross-disciplinary collaborations are more likely among the team proposals that were successful. Thus, even though cross-boundary collaboration is widely promoted, researchers are more likely to consort within their own demographics. However, in order to be successful, scientists would benefit by collaborating with different disciplines.


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