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Researchers have attempted to measure the success of crowdfunding campaigns using a variety of determinants, such as the descriptions of the crowdfunding campaigns, the amount of funding goals, and crowdfunding project characteristics. Although many successful determinants have been reported in the literature, it remains unclear whether the cover p...
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Online medical crowdfunding (OMC) has attracted massive attention and participation in China. Despite its goal to lift the financial burden caused by expensive medical expenditure, little has been done to evaluate its impact on healthcare inequality. We examine the social consequences of OMC based on a large random sample extracted from one of the...
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... Recently, the ability of deep neural networks to recognize complex patterns from multimodal data has been valued by researchers. More and more studies have attempted to use deep learning-based frameworks to extract key information from multimodal crowdfunding data in pre-launch crowdfunding success prediction (Cheng et al., 2019;Zhang et al., 2021). Such methods rely less on human knowledge and seek to identify critical patterns in numerous features through complicated neural networks. ...
... Cheng et al. (2019) used the pretrained VGG-16 model as an encoder to extract information from images in crowdfunding projects, which significantly improved the performance compared to the previous models. On the basis of utilizing pre-trained computer vision models to extract image information, Zhang et al. (2021) further employed the pre-trained Neural Image Assessment (NIMA) model to obtain fine-grained artistic features of the project images, which provides additional information for the model. Recently, researchers integrated cutting-edge techniques, such as the crossattention mechanism (Tang et al., 2022) and graph convolutional module (Cai et al., 2024) into the deep neural network framework. ...
... Welldefined fine-grained features are able to highlight the factors identified by humans that significantly influence the target within a specific context. A unique study conducted by Zhang et al. (2021) examined the impact of fine-grained image features, the aesthetics of an image, on potential donors. The authors employed a pre-trained NIMA model to grade artistic scores for the product images and incorporate graded scores for the pre-launch prediction models. ...
... Therefore, a project creator's portrait photo may enhance potential backers' confidence in funding the project. However, Zhang et al. (2021) argue that while facial images might draw attention, they do not necessarily guarantee crowdfunding success. ...
This study investigates how project-specific factors, the project creator, and campaign signals influence crowdfunding success in France. Analysing 424 projects from the KissKissBankBank platform, the research employs Generalised Linear Models to identify significant success factors. The findings reveal that signals such as publications, geographical location, project category, the creator’s past experience, the number of backers, and the funds raised positively affect campaign success. Contrary to our research hypotheses, signals related to factors such as video, the length of the project description, fundraising duration, and goal amount negatively impact success. Additionally, signals related to factors such as comments, readability of the project description, facial trust, and gender were found to be insignificant. This study provides valuable insights for young entrepreneurs, helping them identify crucial signals for crafting effective crowdfunding strategies, thereby enhancing the likelihood of their campaign success. It also serves as a resource for potential backers, enabling them to make informed investment choices before committing to crowdfunding projects.
... Multimodal gender identification seeks to determine an individual's gender through various modalities such as text, images, and videos linked to them [90,89,101,77]. Social media provides these multimodal resources for profiling each user. LMMs have come forward as zero-shot predictors for gender identification using social media content. ...
Recent research has shed light on the capabilities of Large Multimodal Models (LMMs) across various general vision and language tasks. The performance of LMMs in specialized domains, such as social media, which integrates text, images, videos, and sometimes audio, remains an area of active interest. Effective analysis of such content requires models to interpret the complex interactions between different communication modalities and their influence on the conveyed message. This paper explores GPT-4V(ision)’s performance in social multimedia analysis. We evaluate GPT-4V across five representative tasks: sentiment analysis, hate speech detection, fake news identification, demographic inference, and political ideology detection. Our approach includes a preliminary quantitative analysis for each task using existing benchmark datasets, followed by a review of the results and a selection of qualitative samples to demonstrate GPT-4V’s performance in multimodal social media content analysis. GPT-4V shows effectiveness in these tasks, exhibiting capabilities like joint image-text understanding, contextual and cultural awareness, and commonsense knowledge application. However, challenges persist, including struggles with multilingual social multimedia comprehension and difficulty in adapting to the latest social media trends. It also sometimes generates incorrect information about evolving knowledge of celebrities and politicians. This preliminary study aims to inform further research across disciplines, particularly in computational social science and social media studies. The findings highlight the potential of LMMs to enhance our understanding of social media content and its users through multimodal analysis. All images and prompts used in this study will be available at https://github.com/VIStA-H/GPT-4V_Social_Media .
Disclaimer: This paper contains some examples of offensive social media content. Reader discretion is advised.
... Additionally, most crowdfunding platforms charge fees. For instance, GoFundMe charges a 2.9% transaction fee plus $0.30 per donation, while Kickstarter charges a 5% fee on the total funds raised for successful campaigns and a payment processing fee of 3% plus $0.20 per pledge for U.S. residents [4]. There are also numerous fraudulent or unsuccessful campaigns. ...
There has been a rapid development of crowdfunding as the most efficient method of gathering funds for different goals, such as business and commercial projects or ideas and inventions, education enhancement, healthcare institutions, and social needs. However, despite its efficiency, traditional CS present severe issues related to their vulnerabilities, becoming the primary reason for giving hackers and malicious users access to investors' and project initiators' personal and financial data. These problems can be solved in this paper by introducing blockchain and federated learning to enhance the security and decentralization of transactions. As options to the centralized cloud storage, the authors suggest applying decentralized file sharing methods such as Inter-Planetary File System (IPFS).This paper focuses on the model of the blockchain crowdfunding with the help of the proof-of-model framework with the use of the Ethereum Smart Contracts (ESC) for the automated release of the funds on the achievement of milestones that might be observed when designing and launching the efficient blockchain crowdfunding environment.
... Additionally, it's important to note that most crowdfunding platforms charge fees. For instance, GoFundMe takes a 2.9% fee from the transaction amount plus $0, while Kickstarter charges $30 per donation and applies a payment processing fee of 3-5% of the total funding amount [4]. While there has been an increase in successful campaigns, there are also numerous fake or unsuccessful ones. ...
Crowdfunding is a great way of financing across industries and is widely used in the entrepreneurial world, education, health, and social causes. However, traditional crowdfunding is not devoid of certain problems such as data breaches and scams related to the undertaken projects. This paper aims to increase the security and transparency of crowdfunding, where blockchain and federated learning can be implemented. Contributor data are given private treatment in operations that involve Secure Multi-Party Computation (SMPC) to preserve anonymity and secure the transaction. Using the concept of smart contact-based crowdfunding in this paper, the author has analyzed the available literature, to gain an understanding of how to unlock the disbursement of funds based on specific milestones assisted by smart contracts on the Ethereum platform. The paper offers a wide framework of reference that points out the best practices and potential flaws of the envisaged blockchain crowdfunding ecosystem used in the paper.
... Additionally, it's important to note that most crowdfunding platforms charge fees. For instance, GoFundMe takes a 2.9% fee from the transaction amount plus $0, while Kickstarter charges $30 per donation and applies a payment processing fee of 3-5% of the total funding amount [4]. While there has been an increase in successful campaigns, there are also numerous fake or unsuccessful ones. ...
Crowdfunding is a great way of financing across industries and is widely used in the entrepreneurial world, education, health, and social causes. However, traditional crowdfunding is not devoid of certain problems such as data breaches and scams related to the undertaken projects. This paper aims to increase the security and transparency of crowdfunding, where blockchain and federated learning can be implemented. Contributor data are given private treatment in operations that involve Secure Multi-Party Computation (SMPC) to preserve anonymity and secure the transaction. Using the concept of smart contact-based crowdfunding in this paper, the author has analyzed the available literature, to gain an understanding of how to unlock the disbursement of funds based on specific milestones assisted by smart contracts on the Ethereum platform. The paper offers a wide framework of reference that points out the best practices and potential flaws of the envisaged blockchain crowdfunding ecosystem used in the paper.
... Crowdfunding can be implemented through various crowdfunding platforms, but the objectives vary depending on the type of project being funded. For example, campaigns launched on the GoFundMe platform are intended for charitable projects, whereas campaigns launched on the Kickstarter platform are exclusively for entrepreneurial (commercial) activities (Zhang et al., 2021). According to Bone and Baeck (2016), crowdfunding generally involves raising funds for a specific project rather than for an organization, with fundraisers clearly defining how much funding is needed for a project and how the money will be spent. ...
Crowdfunding is currently one of the funding options for charitable non‐profit projects created by non‐governmental organizations (NGOs). This paper aims to analyse the charity projects created by NGOs and individuals on crowdfunding platforms and then compare them with commercial crowdfunding, emphasizing the success factors of charity campaigns. The data is from the crowdfunding portal StartLab from 2015 to 2022. The main methods are comparison, descriptive and correlation analysis concerning project categories and seasonality. From the investigation results, it can be concluded that charity projects are more successful in conducting crowdfunding campaigns than commercial projects. For practitioners, it might be of interest that the length of the campaign and seasonality significantly influence the project's success. In the case of Slovakia, it is recommended to set a shorter campaign and run it from October to December.
... Moradi and Badrinarayanan (2021) analyzed data from CF projects and showed the brand prominence, language style, and narrative length as drivers for funding success. Zhang et al. (2021) success, different crowdfunding models, and the selection of subdivided determinants impact the relationships between antecedents and CF success. Findings revealed project-and creator-related factors, while these factors had inconsistent associations with CF success because of different measurements. ...
... The quality of the images also has a significant and positive impact on donors' participation. Image features such as the single image quality of a cover image significantly enhance the performance of success prediction (Zhang et al., 2021). ...
... Numerous studies support that images may impact CF success. Image features, for instance, the aesthetic and technical score of the cover image, significantly improve the prediction performance in the past research and the study of Zhang et al. (2021). Hou et al. (2019) explore the characteristics of title images of projects on the CF search page and reveal that aesthetic attributes of images predict emotions such as sadness and contentment, which consequently affect CF projects' performance including the number of backers and amount of fundraising. ...
... In the context of DBC platforms, motivation plays a significant role as it influences donors' participation in crowdfunding platforms (Bretschneider & Leimeister, 2017). While the process and functioning of DBC platforms are similar to other types of crowdfunding platforms, past studies have indicated that the success rate of DBC platforms is meager (Courtney et al., 2017;Zhang et al., 2020aZhang et al., , 2020b. Wang et al. (2019) point out that in 2014, China launched the first DBC platform to support the public cause. ...
The COVID-19 pandemic has impacted the financial well-being of people and the world’s economy. Crowdfunding is a prominent contributor to this pandemic's adverse effects. Donations on crowdfunding platforms have received attention; however, repeated donations, especially during COVID-19, need to be studied. This study aims to understand the role of reward-based gamification as a tool for understanding repeated donation behaviour on crowdfunding platforms during COVID-19. The study uses the self-determination theory to propose the conceptual framework and uses cross sectional data from 514 donors using survey based instruments. This study aims to understand the role of social relatedness with donors’ intrinsic motivation to make repeated donations. Similarly, it tries to establish the role of social relatedness and engagement with repeated donation behaviour. The study uses reward-based gamification as moderating variables, and the model controls the experience of donating on crowdfunding platforms. The results confirm the relationship between social relatedness impacting a donor’s intrinsic motivation and engagement in crowdfunding platform activities leading to repeated donation behaviour. The study further establishes that reward-based gamification moderates the relationship between intrinsic motivation and repeated donation behaviour. The results reveal that the experience of donating impacts the users' repeated donations. The study presents new insights on the role of gamification in inducing repeated donations on crowdfunding platforms during COVID-19.
... Although a traditional donation route is still present, a growing number of online donations in recent years has been particularly noticeable (Liu et al., 2017). Out of many available platforms, crowdfunding websites such as GoFundMe have been pioneers of promoting donations on online platforms raising more than $5 billion since 2010 (Zhang et al., 2020). Although several studies use U.S.-based platforms as research domains, the scholarly attention has not been limited to the U.S. only. ...
This study examines the internal and external factors affecting behavioral intention of online donation and word-of-mouth via crowdfunding sites. The conflicting findings from the literature provided rationales and several key variables for this study. To investigate the key variables, the authors conducted an online survey. The result confirmed that social identification, involvement, credibility of platforms, and attitudes toward online donation positively predict intention to donate online. In addition, social identification, involvement, and crowdfunding site features had predictive power on the intention of word-of-mouth. Theoretical and practical implications for public relations and communication practitioners are provided in the discussion.
