@article {zevin2023gravity, title = {Gravity Spy: Lessons Learned and a Path Forward}, journal = {European Physical Journal Plus}, volume = {139}, year = {2024}, month = {01/2024}, pages = {Article 100}, abstract = {

The Gravity Spy project aims to uncover the origins of glitches, transient bursts of noise that hamper analysis of gravitational-wave data. By using both the work of citizen-science volunteers and machine-learning algorithms, the Gravity Spy project enables reliable classification of glitches. Citizen science and machine learning are intrinsically coupled within the Gravity Spy framework, with machine-learning classifications providing a rapid first-pass classification of the dataset and enabling tiered volunteer training, and volunteer-based classifications verifying the machine classifications, bolstering the machine-learning training set and identifying new morphological classes of glitches. These classifications are now routinely used in studies characterizing the performance of the LIGO gravitational-wave detectors. Providing the volunteers with a training framework that teaches them to classify a wide range of glitches, as well as additional tools to aid their investigations of interesting glitches, empowers them to make discoveries of new classes of glitches. This demonstrates that, when giving suitable support, volunteers can go beyond simple classification tasks to identify new features in data at a level comparable to domain experts. The Gravity Spy project is now providing volunteers with more complicated data that includes auxiliary monitors of the detector to identify the root cause of glitches.

}, doi = {10.1140/epjp/s13360-023-04795-4}, author = {Michael Zevin and Corey B. Jackson and Zoheyr Doctor and Yunan Wu and Carsten {\O}sterlund and L. Clifton Johnson and Christopher P. L. Berry and Kevin Crowston and Scott B. Coughlin and Vicky Kalogera and Sharan Banagiri and Derek Davis and Jane Glanzer and Renzhi Hao and Aggelos K. Katsaggelos and Oli Patane and Jennifer Sanchez and Joshua Smith and Siddharth Soni and Laura Trouille and Marissa Walker and Irina Aerith and Wilfried Domainko and Victor-Georges Baranowski and Gerhard Niklasch and Barbara T{\'e}gl{\'a}s} } @proceedings {2018, title = {The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning}, year = {2020}, type = {Working paper}, address = {Wailea, HI}, abstract = {

Machine learning (ML) constitute an algorithmic phenomenon with some distinctive characteristics (e.g., being trained, probabilistic). Our understanding of such systems is limited when it comes to how these unique characteristics play out in organizational settings and what challenges different groups of users will face in working with them. We explore how people developing or using an ML system come to understand its capabilities and challenges. We draw on the social construction of technology tradition to frame our analysis of interviews and discussion board posts involving designers and users of a ML-supported citizen-science crowdsourcing project named Gravity Spy. Our findings reveal some of the challenges facing different relevant social groups. We find that groups with less interaction with the technology have their understanding. We find that the type of understandings achieved by groups having less interaction with the technology is shaped by outside influences rather than the specifics of the system and its role in the project. Notable, some users mistake human input for ML input. This initial understanding of how different participants understand and engage with ML point to challenges that need to be overcome to help participants deal with the opaque position ML often hold in a work system.

}, doi = {10.24251/HICSS.2020.719 }, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/Social_Construction_of_ML_in_GS_HICCS2020.pdf}, author = {Mahboobeh Harandi and Kevin Crowston and Corey Jackson and Carsten {\O}sterlund} } @article {2020, title = {GitLab: Work where you want, when you want}, journal = {Journal of Organizational Design}, volume = {9}, year = {2020}, month = {2020/11/16}, pages = {23}, abstract = {

GitLab is a software company that works {\textquotedblleft}all remote{\textquotedblright} at the scale of more than 1000 employees located in more than 60 countries. GitLab has no physical office and its employees can work from anywhere they choose. Any step of the organizational life of a GitLab employee (e.g., hiring, onboarding and firing) is performed remotely, except for a yearly companywide gathering. GitLab strongly relies on asynchronous coordination, allowing employees to work anytime they want. After highlighting some of the main practices implemented by GitLab to effectively work all remotely and asynchronously, I asked renowned organizational scientists their thoughts on this interesting case and to question the generalizability of the all remote asynchronous model. Understanding whether and under what conditions this model can succeed can be of guidance for organizational designers that are now considering different remote models in response of the COVID-19 shock and its aftermath.

}, isbn = {2245-408X}, doi = {10.1186/s41469-020-00087-8}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/s41469-020-00087-8.pdf}, author = {Choudhury, Prithwiraj and Crowston, Kevin and Dahlander, Linus and Minervini, Marco S. and Raghuram, Sumita} } @article {9999, title = {Gamers, citizen scientists, and data: Exploring participant contributions in two games with a purpose}, journal = {Computers in Human Behavior}, volume = {68}, year = {2017}, pages = {254{\textendash}268}, abstract = {

Two key problems for crowd-sourcing systems are motivating contributions from participants and ensuring the quality of these contributions. Games have been suggested as a motivational approach to encourage contribution, but attracting participation through game play rather than intrinsic interest raises concerns about the quality of the contributions provided. These concerns are particularly important in the context of citizen science projects, when the contributions are data to be used for scientific research. To assess the validity of concerns about the effects of gaming on data quality, we compare the quality of data obtained from two citizen science games, one a {\textquotedblleft}gamified{\textquotedblright} version of a species classification task and one a fantasy game that used the classification task only as a way to advance in the game play. Surprisingly, though we did observe cheating in the fantasy game, data quality (i.e., classification accuracy) from participants in the two games was not significantly different. As well, data from short-time contributors was also at a usable level of accuracy. Finally, learning did not seem to affect data quality in our context. These findings suggest that various approaches to gamification can be useful for motivating contributions to citizen science projects.

}, doi = {10.1016/j.chb.2016.11.035}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/chb2016.pdf}, author = {Nathan Prestopnik and Kevin Crowston and Wang, Jun} } @article {2017, title = {Gravity Spy: Humans, machines and the future of citizen science}, year = {2017}, address = {Portland, OR}, abstract = {Gravity Spy is a citizen science project that draws on the contributions of both humans and machines to achieve its scientific goals. The system supports the Laser Interferometer Gravitational Observatory (LIGO) by classifying {\textquotedblleft}glitches{\textquotedblright} that interfere with observations. The system makes three advances on the current state of the art: explicit training for new volunteers, synergy between machine and human classification and support for discovery of new classes of glitch. As well, it provides a platform for human-centred computing research on motivation, learning and collaboration. The system has been launched and is currently in operation.}, doi = {10.1145/3022198.3026329}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/cpa137-crowstonA.pdf}, author = {Kevin Crowston and The Gravity Spy Team} } @article {657, title = {Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science}, journal = {Classical and Quantum Gravity}, volume = {34}, year = {2017}, pages = {064003}, type = {Journal Article}, doi = {10.1088/1361-6382/aa5cea}, author = {Michael Zevin and Scott Coughlin and Sara Bahaadini and Emre Besler and Neda Rohani and Sarah Allen and Miriam Cabero and Kevin Crowston and Aggelos Katsaggelos and Shane Larson and Tae Kyoung Lee and Chris Lintott and Tyson Littenberg and Andrew Lundgren and Carsten Oesterlund and Joshua Smith and Laura Trouille and Vicky Kalogera} } @proceedings {9999, title = {{\textquotedblleft}Guess what! You{\textquoteright}re the first to see this event{\textquotedblright}: Increasing Contribution to Online Production Communities}, year = {2016}, abstract = {

In this paper, we describe the results of an online field experiment examining the impacts of messaging about task novelty on the volume of volunteers{\textquoteright} contributions to an online citizen science project. Encouraging volunteers to provide a little more content as they work is an attractive strategy to increase the community{\textquoteright}s output. Prior research found that an important motivation for participation in online citizen science is the wonder of being the first person to observe a particular image. To appeal to this motivation, a pop-up message was added to an online citizen science project that alerted volunteers when they were the first to annotate a particular image. Our analysis reveals that new volunteers who saw these messages increased the volume of annotations they contributed. The results of our study suggest an additional strategy to increase the amount of work volunteers contribute to online communities and citizen science projects specifically.

}, doi = {10.1145/2957276.2957284}, author = {Corey Brian Jackson and Kevin Crowston and Gabriel Mugar and Carsten {\O}sterlund} } @article {9998, title = {Group maintenance in technology-supported distributed teams}, journal = {Information \& Management}, volume = {51}, year = {2014}, month = {4/2014}, pages = {297-309}, abstract = {In this paper we investigate group maintenance behavior in community-based Free/Libre Open Source Software (FLOSS) development teams. Adopting a sociolinguistic perspective, we conceptualize group maintenance behavior as interpersonal communication tactics{\textemdash}specifically, social presence and politeness tactics{\textemdash}that help maintain relationships among group members. Developer email messages were collected from two FLOSS projects with different development status and content-analyzed to identify frequently-used group maintenance tactics. We then compared the two projects on the group maintenance tactics used, finding differences that reflect changes in the project work practices. Our work contributes theoretically to FLOSS research and has practical implications for FLOSS practitioners. }, doi = {10.1016/j.im.2014.02.001}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/Group_maintenance\%20paper_part\%20I_20140122_final.pdf}, author = {Kangning Wei and Kevin Crowston and Li, Na and Heckman, Robert} } @proceedings {2012, title = {Goals and tasks: Two typologies of citizen science projects}, year = {2012}, month = {1/2012}, address = {Wailea, HI}, abstract = {

Citizen science is a form of research collaboration involving members of the public in scientific research projects to address real-world problems. Often organized as a virtual collaboration, these projects are a type of open movement, with collective goals addressed through open participation in research tasks. We conducted a survey of citizen science projects to elicit multiple aspects of project design and operation. We then clustered projects based on the tasks performed by participants and on the project{\textquoteright}s stated goals. The clustering results group projects that show similarities along other dimensions, suggesting useful divisions of the projects.

}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/hicss-45-final.pdf}, author = {Wiggins, Andrea and Kevin Crowston} } @conference {2011, title = {Gaming for (citizen) science: Exploring motivation and data quality in the context of crowdsourced science through the design and evaluation of a social-computational system}, booktitle = {{\textquotedblleft}Computing for Citizen Science{\textquotedblright} workshop at the IEEE eScience Conference}, year = {2011}, month = {12/2011}, address = {Stockholm, Sweden}, abstract = {In this paper, an ongoing design research project is described. Citizen Sort, currently under development, is a web-based social-computational system designed to support a citizen science task, the taxonomic classification of various insect, animal, and plant species. In addition to supporting this natural science objective, the Citizen Sort platform will also support information science research goals on the nature of motivation for social-computation and citizen science. In particular, this research program addresses the use of games to motivate participation in social-computational citizen science, and explores the effects of system design on motivation and data quality. A design science approach, where IT artifacts are developed to solve problems and answer research questions is described. Research questions, progress on Citizen Sort planning and implementation, and key challenges are discussed.}, keywords = {Citizen Science, data quality, Design, Design Science, Games, Gaming, Motivation, Participation, Social Computational Systems}, url = {http://itee.uq.edu.au/~eresearch/workshops/compcitsci2011/index.html}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/gamingforcitizenscience_ver6.pdf}, author = {Nathan Prestopnik and Kevin Crowston} } @proceedings {Scialdone:2009, title = {Group Maintenance Behaviours of Core and Peripheral Members of Free/Libre Open Source Software Teams}, year = {2009}, address = {Skövde, Sweden, 3-6 June}, abstract = {Group Maintenance is pro-social, discretionary, and relation-building behavior that occurs between members of groups in order to maintain reciprocal trust and cooperation. This paper considers how Free/libre Open Source Software (FLOSS) teams demonstrate such behaviors within the context of e-mail, as this is the primary medium through which such teams communicate. We compare group maintenance behaviors between both core and peripheral members of these groups, as well as behaviors between a group that remains producing software today and one which has since dissolved. Our findings indicate that negative politeness tactics (those which show respect for the autonomy of others) may be the most instrumental group maintenance behaviors that contribute to a FLOSS group{\textquoteleft}s ability to survive and continue software production. }, keywords = {FLOSS, Group Maintenance}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/34finalmjs.pdf}, author = {Scialdone, Michael J. and Heckman, Robert and Kevin Crowston}, editor = {Boldyreff, Cornelia and Kevin Crowston and Lundell, Bj{\"o}rn and Wasserman, Tony} } @proceedings {Scialdone:2008, title = {Group Maintenance in Technology-Supported Distributed Teams}, year = {2008}, address = {Anaheim, CA, 9-13 August}, abstract = {Are geographically-distributed teams which exhibit high levels of group maintenance between members successful? We answer this through content analysis of emails from two Free/Libre Open Source Software (FLOSS) teams. Our results illustrate that the groups utilize low levels of organizational citizenship behaviors and high levels of positive politeness actions.}, keywords = {FLOSS, Group Maintenance}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/GroupMaintenance.pdf}, author = {Scialdone, Michael J. and Li, Na and James Howison and Heckman, Robert and Kevin Crowston} } @proceedings {Roussinov:2001a, title = {Genre based navigation on the Web}, year = {2001}, publisher = {IEEE}, address = {Maui, HI, January}, abstract = {We report on our ongoing study of using the genre of Web pages to facilitate information exploration. By genre, we mean socially recognized regularities of form and purpose in documents (e.g., a letter, a memo, a research paper). Our study had three phases. First, through a user study, we identified genres which most/least frequently meet searchers{\textquoteright} information needs. We found that certain genres are better suited for certain types of needs. We identified five (5) major groups of document genres that might be used in an interactive search tool that would allow genrebased navigation. We tried to balance the following dual objectives: 1) each group should be recognizable by a computer algorithm as easily as possible 2) each group has a better chance of satisfying particular types of information needs. Finally, we developed a novel user interface for a web searching that allows genre-based navigation through three major functionalities: 1) limiting search to specified genres 2) visualizing the hierarchy of genres discovered in the search results and 3) accepting user feedback on the relevancy of the specified genres.}, isbn = {0-7695-0981-9 }, doi = {10.1109/HICSS.2001.926478}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/09814013.pdf}, author = {Roussinov, Dmitri and Kevin Crowston and Nilan, Michael and Kwa{\'s}nik, Barbara H. and Xiaozhong Liu and Cai, J.} }