Theses and Dissertations from UMD

Permanent URI for this communityhttp://hdl.handle.net/1903/2

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM

More information is available at Theses and Dissertations at University of Maryland Libraries.

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Subject: search.filters.subject.Crowdsourcing

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Now showing 1 - 6 of 6
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    REVISITING SHAKESPEARE'S WORLD: OPTIMIZING DATA OUTCOMES AND INVESTIGATING CONTRIBUTOR DYNAMICS
    (2024) Wang, ZhiCheng; Van Hyning, Victoria; Library & Information Services; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    In this study, we present our work processing data output from Shakespeare's World (2015-2019), an early transcription project hosted on the Zooniverse online crowdsourcing platform. We refined the dataset to make it more amenable to low-code tools such as OpenRefine, enabling easier exploration and reuse. Utilizing the cleaned dataset, we also explored Shakespeare's World volunteers’ contribution patterns. By documenting our process of cleaning the outcome dataset, we provide steps and insights that may be useful for other transcription projects working with data derived from the Zooniverse platform. In addition to offering one plausible way to clean and analyze Zooniverse outcome data, our study also reveals the significant contributions from both anonymous and registered Shakespeare’s World volunteers; the challenges in maintaining participation over the project’s lifespan; and how the original aggregation protocol, which was designed specifically to combine multiple transcriptions by Shakespeare’s World volunteers, resulted in fewer successfully transcribed lines than expected. These findings have broader implications for project design, volunteer engagement, and data management practices in online crowdsourced transcription projects.
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    The People's Choice: PAIRing User-Centered Design With Crowdsourcing To Combat Misinformation on TikTok
    (2023) Grover, Saransh; Hassan, Naeemul; Library & Information Services; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Social Networking sites like Facebook, Twitter, YouTube, and TikTok have created a rampant increase in user-generated content online. Moderation and validation of misinformation on these platforms are still significant challenges. One approach to address misinformation on social media has been to crowdsource the validity of content through the platform users. However, research conducted on crowdsourced fact-checking has focused largely on traditional and text-based sources. In addition, it has yet to focus on user-centered design to understand how users of platforms would create tools to mitigate misinformation. This thesis addresses these knowledge gaps by understanding approaches to using crowdsourcing to combat misinformation on TikTok, the fastest-growing social networking site with over one billion monthly active users. By using TikTok as a case study, I conduct a thematic analysis of content on the platform to understand how users currently counter claims and misinformation and then conduct participatory design sessions with TikTok users to identify limitations, improvements, and potential solutions. Based on these findings, I present a set of design guidelines referred to as the PAIR approach that outline key considerations for a crowdsourcing platform combatting misinformation on a social networking site such as TikTok.
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    Social media crowdsourcing for rapid damage assessment following sudden-onset earthquakes
    (2021) Li, Lingyao; Baecher, Gregory; Bensi, Michelle; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Rapid appraisal of damages related to hazard events is important to first responders, government agencies, insurance industries, and other private and public organizations. While satellite monitoring, ground-based sensor systems, inspections, and other technologies provide data to inform post-disaster response, crowdsourcing through social media is an additional and novel data source. In this study, the use of social media data, principally Twitter postings, is investigated to make approximate but rapid early assessments of damages following earthquake disasters. The goal is to explore the potential utility of using social media data for rapid damage assessment after sudden-onset hazard events and to identify insights related to potential challenges. This study defines a text-based damage assessment scale for earthquake damages and then develops a text classification model for rapid damage assessment. The 2019 Ridgecrest, California earthquake sequence is mainly investigated as the case study. Results reveal that Twitter users rapidly responded to this sudden-onset event, and the damage estimation shows temporal and spatial characteristics. The generalization ability of the model is validated through the investigation of damage assessment for another five earthquake events. Although the accuracy remains a challenge compared to ground-based instrumental readings and inspections, the proposed damage assessment model features rapidity with large amounts of data at spatial densities that exceed those of conventional sensor networks.
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    EMPIRICAL INVESTIGATION OF USERS’ SUCCESSFUL STRATEGIES IN ONLINE PLATFORMS - EVIDENCE FROM CROWD-SOURCING AND SOCIAL MEDIA PLATFORMS
    (2021) Lysyakov, Mikhail; Viswanathan, Siva; Business and Management: Decision & Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    With the proliferation and constant growth of online platforms, there has been an increasing interest among academicians and practitioners to understand various aspects of these platforms, including the effective design of platforms, their governance and user engagement. This dissertation seeks to add to this stream of research by leveraging large-scale unstructured data and corresponding data analytics and econometric techniques to examine users’ strategies in online social media and crowdsourcing platforms and gain insights into factors that lead to successful outcomes. The first essay examines the content strategies of closely competing firms on Twitter with a focus on how the similarity/dissimilarity of their content strategies impacts their online outcomes. I find that firms that are more adept at leveraging higher-level social media affordances, such as interactivity, collaboration, and online contests to differentiate their content strategies experience better outcomes as compared to their closest rivals that only leverage the basic technological affordances of social media. The second essay examines successful strategies of users (designers) in a crowdsourcing platform wherein clients post contests to solicit design solutions for a monetary reward. This study uses state-of-the-art deep learning and image analysis techniques to examine the strategies of experienced and less-experienced designers in open contests where later-entrants can potentially leverage information spillovers from earlier design submissions within a contest. I find that while later-entrants typically leverage information spillovers from earlier submissions in a contest, only experienced designers who are able to integrate information from multiple highly-rated early submissions are more likely to be successful. The third essay examines users’ strategies in response to the introduction of an Artificial Intelligence system for logo design in an online crowdsourcing design platform. In analyzing what differentiates successful contestants from the others, I find that the successful contestants significantly increase focus (i.e., the number of re-submissions per contest) and increase the emotional content as well as the complexity of their designs, in response to the introduction of the AI system. Collectively, the findings from these studies add to our understanding of successful strategies in online platforms and provide valuable insights to theory and practice.
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    The Transformational Role of IT in Entrepreneurship: Crowdfunding and the Democratization of Access to Capital and Investment Opportunity
    (2014) Kim, Keongtae; Hann, Il-Horn; Viswanathan, Siva; Business and Management: Decision & Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    My dissertation examines the strategic impacts of IT-enabled platforms on entrepreneurial and innovation activities. Specifically, I explore the behaviors of both investors and entrepreneurs in online crowdfunding markets that have the potential to democratize access to capital and investment opportunities. In my first essay, I examine the role of experts in a crowdfunding market. While conventional wisdom considers a crowdfunding market as a mechanism to democratize decision making and reduce reliance on experts, I find that experts still play a pivotal role in these markets. In particular, I find that the early investments by experts serve as credible signals of quality for the crowd, and have a significant impact on the crowd's investment decisions. In my second essay, I analyze whether crowdfunding democratizes access to capital for entrepreneurs. I find that difficult access to credit from traditional sources induces entrepreneurs to rely more on crowdfunding as a viable alternative, while this effect varies across project types and across areas. In each essay, I analyze micro-level data from online crowdfunding markets with a variety of econometric methods. The results have important theoretical and practical implications for questions ranging from the design of online crowdfunding markets to competition between online and offline channels for funding and regional dynamics of crowdfunding.
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    INFORMATION TRANSPARENCY AND USER BEHAVIOR IN EMERGING ONLINE MARKETPLACES: EMPIRICAL STUDIES OF SOCIAL MEDIA AND OPEN INNOVATION MARKETS
    (2013) AL-HASAN, ABRAR; Viswanathan, Siva; Lucas, Hank; Business and Management: Decision & Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Web 2.0 and social media have significantly increased the amount of information available to users not only about firms and their offerings, but also about the activities of other individuals in their networks and markets. It is widely acknowledged that this increased availability of information is likely to influence a user's behavior and choices. However, there are very few systematic studies of how such increased information transparency influences user behavior in emerging marketplaces. My dissertation seeks to examine the impact of increased information transparency - particularly, information about other individuals - in two emerging platforms. The first essay in my dissertation compares online "social" marketing on Facebook with "non-social" marketing and examines their relative impacts on the likelihood of adoption, usage and diffusion of an "App". While social marketing - wherein a user gets to see which of her other friends have also "liked" the product being marketed- is one of the fastest growing online marketing formats, there are hardly any studies that have examined the value of the social aspect of such marketing. I find that social marketing is associated with increased app adoption, usage, and diffusion as compared to non-social marketing. The study also uncovers interesting tradeoffs between the effects of different types of "social" information on user behavior outcomes. The second essay examines the behavior of contestants in an open innovation design marketplace, wherein firms seek solutions from a crowd through an online contest. The study examines how the availability of information about other contestants as well as the availability of feedback information provided to others by the contest holder, impacts a focal contestant's behavior and outcomes. I find that contestants adopt different strategic behaviors that increase their odds of winning the contest under the different information-transparency regimes. The findings have interesting implications for the design of online contests and crowdsourcing markets. Overall, my dissertation provides a deeper understanding of how the visibility of different types of information in online platforms impacts individual behaviors and outcomes.