Crowd-based Platforms
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ItemWe Did Start the Fire: r/wallstreetbets, ‘Flash movements’ and the Gamestop Short-Squeeze( 2022-01-04)In January 2021, Wall Street suddenly faced a challenge from an online community, r/wallstreetbets, which organized a large group of small investors in betting against Wall Street hedge funds. In an instant, the online community came to resemble a social movement nature that brought them comparisons to Occupy Wall Street. To improve understanding of this phenomenon, we studied the Wallstreetbets movement relying on a mixed-methods research design, which combines an unsupervised topic model with in-depth qualitative coding. Our findings outline how Wallstreetbets became a ‘flash movement’, a movement that we define as arising swiftly without former planning or design, through the imbrication of social activities and affordances and constraints of online communities. Our study contributes to (1) the recent interest in spontaneous action in social movements; (2) how social media affordances and constraints affect social movements, and (3) extends methodologies for studying digital social movements.
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ItemUnderstanding the Success of Sharing Economy Startups: A Necessary Condition Analysis( 2022-01-04)Sharing economy businesses such as Uber and AirBnB have disrupted the traditional business models and drawn considerable attention from researchers. While many sharing economy startups are found, a majority of them go unnoticed and fail to reach a critical mass for survival. Prior studies have mostly focused on consumer engagement as success factors for sharing economy businesses. Yet, there is a scarcity of research on success factors at the entry level of sharing economy businesses, namely, the fundraising rounds. This study uses a Necessary Condition Analysis (NCA) on 99 sharing economy startups to explore how human capital, innovativeness, and entrepreneurial footprint impact their fundraising success. Our findings show a large necessary effect for human capital and entrepreneurial footprint, and a medium effect for innovativeness on fundraising success. Additionally, firms only need a range of 30% to 40% level of three factors to achieve at least 40% level of fundraising success.
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ItemThe Influence of “Likes” on User Content Generation in Online Investment Communities( 2022-01-04)Investors increasingly rely on investment advice in online investment communities (OICs). This study analyzes the influence of the “ likes” function on the content generation in OICs. Based on the data collected from Seeking Alpha, we perform a series of analyses from the perspectives of both authors and readers. From the angle of authors, we find that authors express the logic of the articles more seriously by increasing the use of negative words, and reducing the frequency of writing articles. The reader-level analyses show that “likes” and “comments” are complementary to each other, and readers do not reduce their “comments” after the introduction of the “likes” function. In general, the launch of the new function affects the content generated by both authors and readers. Our study can enrich the research on user-generated content (UGC) and provide helpful suggestions to OIC managers in motivating users to make feedbacks and contributions in such communities.
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ItemSocial Media Moderations, User Ban, and Content Generation: Evidence from Zhihu( 2022-01-04)Social media platforms have evolved as major outlets for many entities to distribute and consume information. The content on social media sites, however, are often considered inaccurate, misleading, or even harmful. To deal with such challenges, the platforms have developed rules and guidelines to moderate and regulate the content on their sites. In this study, we explore user banning as a moderation strategy that restricts, suspends, or bans a user who the platform deems as violating community rules from further participation on the platform for a predetermined period of time. We examine the impact of such moderation strategy using data from a major Q&A platform. Our analyses indicate that user banning increases a user’s contribution after the platform lifts the ban. The magnitude of the impact, however, depends on the user’s engagement level with the platform. We find that the increase in contributions is smaller for a more engaged user. Additionally, we find that the quality of the user-generated content (UGC) decreases after the user ban is lifted. Our research is among the first to empirically evaluate the effectiveness of platform moderations. The findings have important implications for platform owners in managing the content on their sites.
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ItemInvestors’ Attention Allocation to Stock Analysis: The Role of Rating Deviation( 2022-01-04)Stock analysis is important for investors. However, little is known about how investors allocate their attention to different analyses. In the last two decades, online investment communities (OICs) have proliferated. In this study, we use investors’ online activities (i.e., comment and like) and amateur stock analysis in Seeking Alpha to explore how investors allocate their attention among different analyses by examining the effects of stock rating deviation on their attention. We measure the stock rating deviation of one analysis by comparing its stock rating with the previous rating for the same stock. The results show that the analyses with stock ratings that are more deviated from the existing ratings tend to receive more comments and likes from investors, indicating that rating deviation from the consensus positively impacts investor attention to stock analysis. In addition, the deviation’s negativity and the stock volatility strengthen the impact of rating deviation on investor attention. However, analysts’ busyness status negatively moderates this impact.
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ItemDynamic Voice Clones Elicit Consumer Trust( 2022-01-04)Platforms today are experimenting with many novel personalization technologies. We explore one such technology here, voice-based conversational agents, with a focus on consumer trust. We consider the joint role of two key design / implementation choices, namely i) disclosing an agent’s autonomous nature to the user, and ii) aesthetic personalization, in the form of user voice cloning. We report on a set of controlled experiments based on the investment game, evaluating how these design choices affect subjects’ willingness to participate in the game against an autonomous, AI-enabled partner. We find no evidence that disclosure affects trust. However, we find that the greatest level of trust is elicited when a voice-based agent employs a clone of the subject’s voice. Mechanism explorations based on post-experiment survey responses indicate that voice-cloning induces trust by eliciting a perception of homophily; the voice-clone induces subjects to personify the agent and picture it as demographically similar.
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ItemDisaster Management Through Digital Platforms: Online Crowdfunding Communities Respond to the COVID-19 Pandemic( 2022-01-04)We study how digital crowdfunding platforms can help replenish the sudden economic deficiencies that accompany a global crisis. Specifically, we examine whether public schools, which suffered severe setbacks during the COVID-19 crisis, were able to generate support from online fundraising communities. We study how the shutdown of schools and the shift to online learning in the United States affected private fundraising on the DonorsChoose.org platform. We find evidence that, after the exogenous shock caused by stay-at-home orders, donations to schools increased and the increased level of concern moves toward high-need schools. Moreover, we find a shift in donation patterns, wherein donors swiftly adapted to renewed priorities and redistributed their resources to immediate needs around digital learning infrastructure. Our findings reveal the pivotal role digital platforms can play in facilitating community resilience during times of crisis.
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ItemCrowdfunding Project Success for Game Developers: Evidence from Kickstarter and Steam( 2022-01-04)Crowdfunding has revolutionized business investor connection in many industries, one of which is game development. Traditionally, triple-A game developers and publishers were able to monopolize the industry, but with the emergence of crowdfunding platforms, smaller game development teams and companies have a way of competing with large corporations by attracting funds. However, Kickstarter reports show that two-third of game funding projects fail to meet their goals. This study develops and empirically examines a theoretical model to predict video game’s crowdfunding success to address this gap. We collect data on video game projects that were initiated on Kickstarter and were later released on the Steam platform. Our analysis of more than 7000 reward tiers for 1967 projects reveals that reward type (free game copy, in-game perks, accessories, artworks, and involvement), and reward description length positively influence funding success, while the number of reward tiers and funding period negatively impact funding success.
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ItemIntroduction to the Minitrack on Crowd-based Platforms( 2022-01-04)