Textual and Visual Cues in Online Deal-Sharing: How Brands, Prices, and Images Drive User Engagement
(A2026-133157)

AUTHORS

Yiyuan (Ava) Liu, Department of Business, Accounting & Economics, Otterbein University; Boshuo Guo, the University of Leeds

ABSTRACT

This research investigates how textual and visual cues influence user engagement on community-based deal-sharing platforms. Focusing on Dealmoon.com, a multilingual U.S.-headquartered deal aggregator, we collected 22 days of data in October 2025, yielding about 18,000 deal listings from roughly 300 brands, and modeled a random sample of approximately 2,000 listings. Using text mining, sentiment analysis, and computer-vision–based image analytics, we quantify promotional text features, price cues, brand prominence, and visual design attributes. Results show that concise text, salient promotional markers, higher prices, and multi-item assortments enhance engagement. Visual brand prominence, lifestyle imagery, and more varied community sentiment further stimulate user conversation. These findings highlight the importance of balancing information clarity, visual salience, and social discourse in driving engagement on image-rich, multilingual deal-sharing platforms.