Image-mining: exploring the impact of video content on the success of crowdfunding

Zecong Ma () and Sergio Palacios ()
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Zecong Ma: St. Mary’s University
Sergio Palacios: St. Mary’s University

Journal of Marketing Analytics, 2021, vol. 9, issue 4, No 2, 265-285

Abstract: Abstract This study aims to better understand the role of visual content in the likelihood of supporting crowdfunding projects. We propose an image mining procedure for collecting, identifying, and classifying visual concepts. This procedure detects communities in the visual concepts’ network, allowing researchers to classify objects into contextual clusters for further inferences. In Study 1, we explored 11,264 video frames from 652 crowdfunding projects on Kickstarter.com using Clarifai’s image recognition tool. By the Louvain method of community detection, we identified 38 contextual clusters of visual concepts. From those, we found that the “workspace” cluster positively linked to crowdfunding projects’ success, while the “event” cluster negatively was related. In addition, in Study 2, we conducted an experiment to examine the impact of the two visual contexts on consumer investors’ intent to support crowdfunding projects and found evidence supporting our initial findings.

Keywords: Visual data; Image mining; Image data; Unstructured data; Crowdfunding (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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DOI: 10.1057/s41270-021-00133-8

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