Project Description
Are you interested in artificial intelligence and entrepreneurship? Are you curious about how language shapes investment decisions in digital marketplaces? Are you concerned about whether entrepreneurs authentically represent their technological capabilities? Then this project is for you. Crowdfunding platforms like Kickstarter and Indiegogo have democratized venture financing, allowing everyday consumers to back entrepreneurial projects. Entrepreneurs increasingly use AI-related language in their pitches, claiming their products use terms like “machine learning,” “neural networks,” “intelligent algorithms” or “generative AI”. However, the ease of invoking AI terminology raises a critical question: does AI rhetoric genuinely signal technological innovation, or does it simply exploit hype to attract funding? Can everyday backers decipher genuine AI capabilities from exaggerated claims? Understanding how backers respond to AI rhetoric has important implications for platform governance, consumer protection, and entrepreneurial legitimacy. This project investigates how AI rhetoric in crowdfunding campaigns affects funding outcomes. Specifically, we will compare campaigns that employ AI-related language with those that do not, examining whether AI rhetoric increases funding success and backer engagement. Furthermore, we will explore whether the credibility of AI claims, indicated by factors such as the entrepreneur’s technical credentials, specificity of technical descriptions, or prior track record, moderates backers’ responses to AI rhetoric. Using data from Indiegogo and Kickstarter, student researchers will employ computational text analysis tools to systematically identify and categorize AI-related language across thousands of campaign descriptions. Students will gain hands-on experience with natural language processing techniques, learn to extract meaningful patterns from unstructured text data, and develop skills in designing empirical studies that connect linguistic features to economic outcomes.
Prerequisites
Students must have completed BUS 202 or its equivalent.
Special Comments
Project Information (subject to change)
Estimated Start Date: 6/8/2026
Estimated End Date: 7/31/2026
Estimated Project Duration: 8 weeks
Maximum Number of Students Sought: 2
Research Location: Remote
Travel Required? No (If “yes”: )
Contact Information: Bright Frimpong (email: bfrimpong@wlu.edu)