101 research outputs found
A high-speed wireless network used for telemedicine
Nowadays, there is growing interest in using telemedicine to provide
non-face-to-face healthcare for patients. The emergence and development
of WLAN (Wireless Local Area Network) technology, which supports
high-speed wireless communications within the existing Intranet that covers
the healthcare system, makes it possible to provide routine body check-ups for
patients who need long-term monitoring.
In this thesis, we present the design of a wireless telemedicine system using
WLAN technology. [Continues.
Investigating VTubing as a Reconstruction of Streamer Self-Presentation: Identity, Performance, and Gender
VTubers, or Virtual YouTubers, are live streamers who create streaming
content using animated 2D or 3D virtual avatars. In recent years, there has
been a significant increase in the number of VTuber creators and viewers across
the globe. This practise has drawn research attention into topics such as
viewers' engagement behaviors and perceptions, however, as animated avatars
offer more identity and performance flexibility than traditional live streaming
where one uses their own body, little research has focused on how this
flexibility influences how creators present themselves. This research thus
seeks to fill this gap by presenting results from a qualitative study of 16
Chinese-speaking VTubers' streaming practices. The data revealed that the
virtual avatars that were used while live streaming afforded creators
opportunities to present themselves using inflated presentations and resulted
in inclusive interactions with viewers. The results also unveiled the inflated,
and often sexualized, gender expressions of VTubers while they were situated in
misogynistic environments. The socio-technical facets of VTubing were found to
potentially reduce sexual harassment and sexism, whilst also raising
self-objectification concerns.Comment: Under review at ACM CSCW after a Major Revisio
Let's Play Together through Channels: Understanding the Practices and Experience of Danmaku Participation Game Players in China
Live streaming is becoming increasingly popular in recent years, as most
channels prioritize the delivery of engaging content to their viewers. Among
various live streaming channels, Danmaku participation game (DPG) has emerged
in China as a mixture of live streaming and online gaming, offering an
immersive gaming experience to players. Although prior research has explored
audience participation games (APGs) in North America and Europe, it primarily
focuses on discussing prototypes and lacks observation of players in natural
settings. Little is known about how players perceive DPGs and their player
experience. To fill the research gap, we observed a series of DPG channels and
conducted an interview-based study to gain insights into the practices and
experiences of DPG players. Our work reveals that DPGs can effectively
synergize live streaming and online games, amplifying both player engagement
and a profound sense of accomplishment to players
Malicious Selling Strategies During Livestream Shopping: A Case Study of Alibaba's Taobao and ByteDance's TikTok
Due to the limitations imposed by the COVID-19 pandemic, many users have
shifted their shopping patterns from offline to online. Livestream shopping has
become popular as one of the online shopping media. However, many streamers'
malicious selling behaviors have been reported. In this research, we sought to
explore streamers' malicious selling strategies and understand how viewers
perceive these strategies. First, we recorded 40 livestream shopping sessions
from two popular livestream platforms in China -- Taobao and TikTok (or
"Douyin" in Chinese). We identified four categories of malicious selling
strategies (i.e., Restrictive, Deceptive, Covert, and Asymmetric) and found
that platform designs enhanced these malicious selling strategies. Second,
through an interview study with 13 viewers, we provide a rich description of
viewers' awareness of malicious selling strategies and the challenges they
encountered while trying to overcome malicious selling. We conclude by
discussing the policy and design implications of countering malicious selling
A Survey on Watching Social Issue Videos among YouTube and TikTok Users
The openness and influence of video-sharing platforms (VSPs) such as YouTube
and TikTok attracted creators to share videos on various social issues.
Although social issue videos (SIVs) affect public opinions and breed
misinformation, how VSP users obtain information and interact with SIVs is
under-explored. This work surveyed 659 YouTube and 127 TikTok users to
understand the motives for consuming SIVs on VSPs. We found that VSP users are
primarily motivated by the information and entertainment gratifications to use
the platform. VSP users use SIVs for information-seeking purposes and find
YouTube and TikTok convenient to interact with SIVs. VSP users moderately watch
SIVs for entertainment and inactively engage in social interactions. SIV
consumption is associated with information and socialization gratifications of
the platform. VSP users appreciate the diversity of information and opinions
but would also do their own research and are concerned about the misinformation
and echo chamber problems
"It Felt Like Having a Second Mind": Investigating Human-AI Co-creativity in Prewriting with Large Language Models
Prewriting is the process of discovering and developing ideas before a first
draft, which requires divergent thinking and often implies unstructured
strategies such as diagramming, outlining, free-writing, etc. Although large
language models (LLMs) have been demonstrated to be useful for a variety of
tasks including creative writing, little is known about how users would
collaborate with LLMs to support prewriting. The preferred collaborative role
and initiative of LLMs during such a creativity process is also unclear. To
investigate human-LLM collaboration patterns and dynamics during prewriting, we
conducted a three-session qualitative study with 15 participants in two
creative tasks: story writing and slogan writing. The findings indicated that
during collaborative prewriting, there appears to be a three-stage iterative
Human-AI Co-creativity process that includes Ideation, Illumination, and
Implementation stages. This collaborative process champions the human in a
dominant role, in addition to mixed and shifting levels of initiative that
exist between humans and LLMs. This research also reports on collaboration
breakdowns that occur during this process, user perceptions of using existing
LLMs during Human-AI Co-creativity, and discusses design implications to
support this co-creativity process.Comment: Under review at CSCW after a Major Revisio
StoryChat: Designing a Narrative-Based Viewer Participation Tool for Live Streaming Chatrooms
Live streaming platforms and existing viewer participation tools enable users
to interact and engage with an online community, but the anonymity and scale of
chat usually result in the spread of negative comments. However, only a few
existing moderation tools investigate the influence of proactive moderation on
viewers' engagement and prosocial behavior. To address this, we developed
StoryChat, a narrative-based viewer participation tool that utilizes a dynamic
graphical plot to reflect chatroom negativity. We crafted the narrative through
a viewer-centered (N=65) iterative design process and evaluated the tool with
48 experienced viewers in a deployment study. We discovered that StoryChat
encouraged viewers to contribute prosocial comments, increased viewer
engagement, and fostered viewers' sense of community. Viewers reported a closer
connection between streamers and other viewers because of the narrative design,
suggesting that narrative-based viewer engagement tools have the potential to
encourage community engagement and prosocial behaviors
Building Credibility, Trust, and Safety on Video-Sharing Platforms
Video-sharing platforms (VSPs) such as YouTube, TikTok, and Twitch attract millions of users and have become influential information sources, especially among the young generation. Video creators and live streamers make videos to engage viewers and form online communities. VSP celebrities obtain monetary benefits through monetization programs and affiliated markets. However, there is a growing concern that user-generated videos are becoming a vehicle for spreading misinformation and controversial content. Creators may make inappropriate content for attention and financial benefits. Some other creators also face harassment and attack. This workshop seeks to bring together a group of HCI scholars to brainstorm technical and design solutions to improve the credibility, trust, and safety of VSPs. We aim to discuss and identify research directions for technology design, policy-making, and platform services for video-sharing platforms. © 2023 Owner/Author
The Labor of Fun: Understanding the Social Relationships between Gamers and Paid Gaming Teammates in China
Online video games support the development of social relationships through gameplay, however, gamers often cannot cultivate and maintain relationships based on social factors such as personality when using in-game matchmaking services. To address this, teammate matching sites external to games have emerged and enable gamers to offer to play games with others in exchange for payment. The affordances of these services are different from other existing gamer social sites, e.g., live streaming. Interviews were conducted with 16 dedicated users on Bixin, one of China’s largest paid teammate matching sites, to examine user motivations, practices, and perceptions. The interviews found that gamers selected paid teammates on Bixin using different criteria compared to in-game matchmaking services and emphasized the importance of real-life characteristics such as voice. To maintain connections, paid teammates often also extended communication to external communication services such as WeChat. Although most gamers expected to communicate with paid teammates as if they were friends, very few reported building real friendships with their matched counterparts
Privacy-preserving collaborative machine learning on genomic data using TensorFlow
Machine learning (ML) methods have been widely used in genomic studies.
However, genomic data are often held by different stakeholders (e.g. hospitals,
universities, and healthcare companies) who consider the data as sensitive
information, even though they desire to collaborate. To address this issue,
recent works have proposed solutions using Secure Multi-party Computation
(MPC), which train on the decentralized data in a way that the participants
could learn nothing from each other beyond the final trained model.
We design and implement several MPC-friendly ML primitives, including class
weight adjustment and parallelizable approximation of activation function. In
addition, we develop the solution as an extension to TF
Encrypted~\citep{dahl2018private}, enabling us to quickly experiment with
enhancements of both machine learning techniques and cryptographic protocols
while leveraging the advantages of TensorFlow's optimizations. Our
implementation compares favorably with state-of-the-art methods, winning first
place in Track IV of the iDASH2019 secure genome analysis competition.Comment: Description of the winning solution at Track IV of iDASH competition
2019, to be presented at the Trustworthy ML workshop co-located with ICLR202
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