Crowd-based Platforms

Permanent URI for this collection

Browse

Recent Submissions

Now showing 1 - 5 of 9
  • Item
    We Did Start the Fire: r/wallstreetbets, ‘Flash movements’ and the Gamestop Short-Squeeze
    ( 2022-01-04) Schou, Peter ; Bucher, Eliane ; Waldkirch, Matthias ; Grünwald, Eduard
    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.
  • Item
    Understanding the Success of Sharing Economy Startups: A Necessary Condition Analysis
    ( 2022-01-04) Bui, Q. Neo ; Bui, Son
    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.
  • Item
    The Influence of “Likes” on User Content Generation in Online Investment Communities
    ( 2022-01-04) Zhuo, Xiaolin ; Hong, Hong ; Xu, Dapeng ; Ye, Qiang
    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.
  • Item
    Social Media Moderations, User Ban, and Content Generation: Evidence from Zhihu
    ( 2022-01-04) Zhang, Xiaohui ; Wei, Zaiyan ; Du, Qianzhou ; Zhang, John
    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.
  • Item
    Investors’ Attention Allocation to Stock Analysis: The Role of Rating Deviation
    ( 2022-01-04) Jin, Yu ; Ye, Qiang ; Pu, Jingchuan
    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.