ThingMoji: User-Captured Cut-Outs For In-Stream Visual Communication
Live streaming has become increasingly popular, driven by the desire for direct and real-time interactions between streamers and viewers. However, current text-based interactions and pre-defined emojis limit expressiveness, especially when referring to specific stream moments. We propose ThingMoji, a type of user-captured cut-outs to enhance user expression and foster more effective communication between streamers and their audience in the comment section. ThingMojis are unique digital icons created by users by capturing snapshots and annotating specific areas at any point during the stream. We developed StreamThing, a live-streaming platform integrated with ThingMojis, to explore their use during object-focused live streaming contexts. In a user study with three in-the-wild deployments reveals the expressive use of ThingMojis in diverse live-streaming scenarios with rich visual contents. Our findings show that ThingMojis enable viewers to reference specific objects, express emotions, and create shared visual narratives. Streamers found ThingMojis valuable for facilitating on-the-fly communication around visual content and fostering playful interactions. The study also uncovered challenges in ThingMoji comprehension, issues for long-term uses of ThingMojis, and potential concerns regarding misuse. Based on these insights, we discussed new opportunities for supporting object-focused communication during live streaming environments.
Authors
- Piaohong Wang (ORCID: https://orcid.org/0009-0008-8393-7101)
- Md Aashikur Rahman Azim (ORCID: https://orcid.org/0000-0001-9744-8263)
- Qian Wan (ORCID: https://orcid.org/0000-0002-4250-8780)
- Erzhen Hu (ORCID: https://orcid.org/0000-0002-8248-8382)
- Seongkook Heo (ORCID: https://orcid.org/0000-0003-2004-4812)
- Changkong Zhou (ORCID: https://orcid.org/0000-0002-0140-2306)
- Zhicong Lu (ORCID: https://orcid.org/0000-0002-7761-6351)
- Yuhan Zeng
- Xingyi Hu (ORCID: https://orcid.org/0009-0009-4357-2029)
Institutions
- Hong Kong Polytechnic University (HK)
- George Mason University (US)
- City University of Hong Kong (HK)
- University of Virginia (US)
- Aalto University (FI)
Publication Details
- Journal
- Proceedings of the ACM on Human-Computer Interaction
- Published
- 2025-10-16
- DOI
- https://doi.org/10.1145/3757676
- Primary Topic
- Digital Communication and Language
- Type
- article
- Field-Weighted Citation Impact
- 0.00