As illustrated in Robert Putnam’s renowned book “Bowling Alone: The Collapse and Revival of American Community,” Americans have become increasingly isolated over the decades, often spending leisure time alone without social gatherings. During the COVID-19 pandemic, this issue of isolation was exacerbated, calling further attention to the public health crisis of loneliness and isolation in the United States.
To help encourage in-person gatherings, Event-Based Social Networks (EBSNs), such as Meetup.com and Facebook Events, have become an increasingly vital tool for facilitating these occasions based on shared interests — ranging from farmers’ markets to game nights. To maximize the effectiveness of EBSNs, a group of Mason faculty members with interests in community engagement, machine learning, and geographical data analysis wanted to take a closer look at how these arranged local gatherings fluctuated depending on community and group characteristics. They were able to undertake this analysis following the approval of their 4-VA@Mason Collaborative Research Grant proposal entitled “AI for AI: Toward Community-level Human-AI Collaborations in Local Meetups.”
Led by Myeong Lee, Mason’s Assistant Professor of Information Science and the Director of the Community Informatics Lab, the researchers also included former College of Science faculty members Olga Gkountouna, who assisted with machine learning model development, and Ron Mahabir who provided insight on geographical data analysis. Amr Hilal of Virginia Tech helped with data analytics from a machine learning perspective.
While it is known that EBSN users’ participation in Meetup events are influenced by group organizers’ promotions and event frequency, the effects of ecological factors, such as the number of similar groups surrounding a Meetup group, had not been previously studied. The goals of the project were to quantitatively examine how EBSN groups’ ecological features shape the performances of Meetup groups within that organizational ecology. They also wanted to create baseline benchmarks for how state-of-the art AI technologies can predict Meetup groups’ success.
To do so, the team conducted two studies of Meetup data for 500 cities in the US, extracting factors pertaining to “Meetup niches,” which considers similar groups surrounding a Meetup location.
The results revealed intriguing patterns, one of which was that if a Meetup group’s description resembles other groups 
in their geographical area, it tends to attract more participants. In a second finding, the team implemented three advanced machine learning models to predict the success of local Meetup groups, finding that the performances of these prediction models vary across different categories and cities, with some outperforming the state-of-the-art models.
“Overall, our research during the 4-VA project period will provide a basis for understanding human-AI collaboration at the community level by revealing how various factors shape and predict the success of local groups,” says Lee.
Lee credits the success of their findings to a strong team of student researchers, including graduate students Julia Hsin-Ping Hsu who worked on developing deep learning models and ecological features and Ishana Shinde who assisted in calculating community-level features. Undergraduates Victoria Gonzales focused on descriptive statistics of variables; Joel Adeniji managed visualization; and Nnamdi Ojibe handled data cleaning and geographical data aggregation.
The group is now disseminating their findings in the field – one study was published at the International Conference on Communities and Technologies (C&T), and the other is under submission to a premier journal. Lee is planning to write an external NSF grant using the preliminary results from the research, proposing the curation of Meetup-based social gathering data with the promising community-level ecological factors.
“The 4-VA@Mason grant significantly helped me and my team jump-start the project and develop the research studies,” says Lee. “What’s more, it allowed the team to connect with researchers outside of Mason to discuss additional meaningful community-based topics, thus broadening our future possibilities.”
Graduate student Muhammad Umair (left), who gathered and processed fMRI and firing rate data for the research, won first place at the College of Engineering and Computing Innovation Week at Mason with a poster titled ‘Subject and Task Fingerprint using Dynamic Reconstruction from fMRI Time-series Data’.
This dilemma had been on the mind of Margaret Weiss, Associate Professor of Special Education at Mason who has long researched co-teaching and pre-service teacher preparation. She saw an acute need to develop and then test a hybrid professional learning series to prepare general and special education teachers in secondary inclusive classrooms to implement effective co-teaching practices.
Rodgers, an Associate Professor at VCU, would be the perfect collaborator. Rogers specializes in inclusive classrooms, co-teaching, learning disabilities, single-case design methods, collaboration, and classroom observation. As VCU is a partner in the 4-VA network, Weiss was able to invite Rodgers to join her in a 4-VA proposal as a co-principal investigator, which was subsequently greenlighted by the 4-VA@Mason Advisory Board.
To look closer at this phenomenon, Byunghwan Son in Mason’s Global Affairs Program was interested in creating an intellectual space where systematic research on contemporary Asian and Asian American studies subjects could be nurtured and fostered. To do so, he turned to a 4-VA@Mason Collaborative Research Grant for funding to build on data he had already collected between 2019-2021. His objective was to conduct additional interviews necessary to glean a more in-depth understanding of the cross-ethnic and -racial nature of K-pop. Son’s plan was to coordinate faculty at Mason and UVA to recruit and advise graduate and undergraduate students to conduct the work, providing rich research opportunities. These opportunities would include collecting, cleaning, and coding interview data of K-pop fans in North America.
The concept is being led by Kelly Schrum, a professor in Mason’s Higher Education Program in the College of Humanities and Social Sciences. Schrum has brought together a group of faculty members, undergraduate, and graduate students to put the plan into action. In addition, representatives from ADVANCE, the Office of Undergraduate Admissions, and the First-Gen+ Center will also play a role in the project.
welcomes them to Mason. Students will see a virtual panel where they will find questions and answers from current students and be invited to add their voice to the conversation. Encouraging words from the First Gen+ Center will appear on the screen, such as “You are the first, but you won’t be the last.”
With the preliminary findings, faculty and student researchers then designed and organized a Fall 2022 workshop titled “Renewal and Resilience: A Community of Student Activists,” which featured student activists fighting for food security, prison reform, racial justice, voting rights, LGBTQ rights, and gun control at Mason, Virginia Tech, and Virginia Commonwealth University. Following the student activist panel, Castle presented “Regenerating the Self,” encouraging participants to assess their well-being with the help of a self-care workbook. Participants were also encouraged to create their own maintenance plans to help in times of stress. Lisa Porter concluded the program by sharing an interview with Crimson Solano, a community leader of Harrisonburg-based Comité Salvadoreño Paisanos Unidos, a pro-immigrant policy advocate group.