Tag Archives: audio analytics

How Does AI-Generated Voice Affect Online Video Creation? Evidence from TikTok

Zhang, Xiaoke, Mi Zhou, Gene Moo Lee “How Does AI-Generated Voice Affect Online Video Creation? Evidence from TikTok”, Working Paper.

  • Presentations: INFORMS DS (2022), UBC (2022), WITS (2022), Yonsei (2023), POSTECH (2023), ISMS MKSC (2023), CSWIM (2023), KrAIS Summer (2023), Dalhousie (2023), CIST (2023), Temple (2024), Santa Clara U (2024), Wisconsin Milwaukee (2024)
  • Best Student Paper Nomination at CIST 2023
  • API sponsored by Ensemble Data
  • SSRN version: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4676705

The rising demand for online video content has fostered one of the fastest-growing markets as evidenced by the growing popularity of platforms like TikTok. In response to the challenges of video creation, these platforms are increasingly incorporating artificial intelligence (AI) to support creators in their video creation process. However, little is known about how AI integration influences online content creation. Our paper aims to address this gap by investigating the impact of AI-generated voice on video creators’ productivity and creative patterns. Using a comprehensive dataset of 554,252 videos from 4,691 TikTok creators, we conduct multimodal analyses of the video data to detect the adoption of AI voice and to quantify video characteristics. We then estimate the adoption effects using a stacked difference-in-differences model coupled with propensity score matching. Our results suggest that AI voice adoption significantly increases creator productivity. Moreover, we find that the use of AI voice enhances video novelty across image, audio, and text modalities, suggesting its role in reducing workload on routine tasks and fostering creative exploration. Lastly, our study also uncovers a disinhibition effect, where creators tend to conceal their identities with the AI voice and exert more negative sentiments because of diminished social image concerns. Our paper provides the first empirical evidence of how AI reshapes online video creation, providing important implications for creators, platforms, and policymakers in the creator economy.

When Does Congruence Matter for Pre-roll Video Ads? The Effect of Multimodal, Ad-Content Congruence on the Ad Completion

Park, Sungho, Gene Moo Lee, Donghyuk Shin, Sang-Pil Han. “When Does Congruence Matter for Pre-roll Video Ads? The Effect of Multimodal, Ad-Content Congruence on the Ad Completion“, Working Paper [Last update: Jan 29, 2023]

  • Previous title: Targeting Pre-Roll Ads using Video Analytics
  • Funded by Sauder Exploratory Research Grant 2020
  • Presented at Southern Methodist University (2020), University of Washington (2020), INFORMS (2020), AIMLBA (2020), WITS (2020), HKUST (2021), Maryland (2021), American University (2021), National University of Singapore (2021), Arizona (2022), George Mason (2022), KAIST (2022), Hanyang (2022), Kyung Hee (2022), McGill (2022)
  • Research assistants: Raymond Situ, Miguel Valarao

Pre-roll video ads are gaining industry traction because the audience may be willing to watch an ad for a few seconds, if not the entire ad, before the desired content video is shown. Conversely, a popular skippable type of pre-roll video ads, which enables viewers to skip an ad in a few seconds, creates opportunity costs for advertisers and online video platforms when the ad is skipped. Against this backdrop, we employ a video analytics framework to extract multimodal features from ad and content videos, including auditory signals and thematic visual information, and probe into the effect of ad-content congruence at each modality using a random matching experiment conducted by a major video advertising platform. The present study challenges the widely held view that ads that match content are more likely to be viewed than those that do not, and investigates the conditions under which congruence may or may not work. Our results indicate that non-thematic auditory signal congruence between the ad and content is essential in explaining viewers’ ad completion, while thematic visual congruence is only effective if the viewer has sufficient attentional and cognitive capacity to recognize such congruence. The findings suggest that thematic videos demand more cognitive processing power than auditory signals for viewers to perceive ad-content congruence, leading to decreased ad viewing. Overall, these findings have significant theoretical and practical implications for understanding whether and when viewers construct congruence in the context of pre-roll video ads and how advertisers might target their pre-roll video ads successfully.