CS与社会学学术速递[1.10]
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cs.CYCS与社会学，共计5篇
【1】 Modeling International Mobility using Roaming Cell Phone Traces during COVID-19 Pandemic
标题：利用冠状病毒大流行期间漫游手机痕迹模拟国际流动性
链接：https://arxiv.org/abs/2201.02470
摘要：Most of the studies related to human mobility are focused on intra-country
mobility. However, there are many scenarios (e.g., spreading diseases,
migration) in which timely data on international commuters are vital. Mobile
phones represent a unique opportunity to monitor international mobility flows
in a timely manner and with proper spatial aggregation. This work proposes
using roaming data generated by mobile phones to model incoming and outgoing
international mobility. We use the gravity and radiation models to capture
mobility flows before and during the introduction of non-pharmaceutical
interventions. However, traditional models have some limitations: for instance,
mobility restrictions are not explicitly captured and may play a crucial role.
To overtake such limitations, we propose the COVID Gravity Model (CGM), namely
an extension of the traditional gravity model that is tailored for the pandemic
scenario. This proposed approach overtakes, in terms of accuracy, the
traditional models by 126.9% for incoming mobility and by 63.9% when modeling
outgoing mobility flows.
【2】 The Study of Peer Assessment Impact on Group Learning Activities
标题：同伴评价对小组学习活动的影响研究
链接：https://arxiv.org/abs/2201.02344
备注：Regular Research Paper Accepted by FECS'21 (The 17th Int'l Conf on Frontiers in Education: Computer Science and Computer Engineering)
摘要：Comparing with lecturer marked assessments, peer assessment is a more
comprehensive learning process and many of the associated problems have
occurred. In this research work, we study the peer-assessment impact on group
learning activities in order to provide a complete and systematic review,
increase the practice and quality of the peer assessment process. Pilot studies
were conducted and took the form of surveys, focus group interviews, and
questionnaires. Prelimi-nary surveys were conducted with 582 students and 276
responses were received, giving a response rate of 47.4%. The results show 37%
student will choose individual work over group work if given the choice. In the
case study, 82.1% of the total of 28 students have en-joyed working in a group
using Facebook as communication tools. 89.3% of the students can demonstrate
their skills through group-working and most importantly, 82.1% of them agree
that peer assess-ment is an impartial method of assessment with the help of
Facebook as proof of self-contribution. Our suggestions to make group work a
pleasant experience are by identifying and taking action against the
freeloader, giving credit to the deserving students, educating students on how
to give constructive feedback and making the assessment pro-cess transparent to
all.
【3】 From Textual Experiments to Experimental Texts: Expressive Repetition in "Artificial Intelligence Literature"
链接：https://arxiv.org/abs/2201.02303
备注：12 pages; to appear on SASS Studies, 2021 Winter. This is an English version; please consider citing the original paper in Chinese
摘要：Since the birth of artificial intelligence 70 years ago, attempts at literary
"creation" with computers are present in the course of technological
development, creating what one might call "artificial intelligence literature"
(AI literature). Evolving from "textual experiments" conducted by technologists
to "experimental texts" that explore the possibilities of conceptions of
literature, AI literature integrates primitive problems including machine
thinking, text generation, and machine creativity, which exhibits the two-way
interaction between social ideas and technology. In the early stage, the mutual
support between technological path and artistic ideas turned out to be a
failure, while AI-driven expressive repetitions are made probable in the
contemporary technological context, paving the way for the transformation of AI
literature from proof for technical possibilities to self-verification of
literary value.
【4】 Investigating Expectation Violations in Mobile Apps
标题：调查移动应用中的预期违规行为
链接：https://arxiv.org/abs/2201.02269
备注：32 pages, 4 figures, 8 tables
摘要：Information technology and software services are pervasive, occupying the
centre of most aspects of contemporary societies. This has given rise to
commonly expected norms and expectations around how such systems should work,
appropriate penalties for violating these expectations, and more importantly,
indicators of how to reduce the consequences of violations and sanctions.
Evidence for expectation violations and ensuing sanctions exists in a range of
portals used by individuals and groups to start new friendships, explore new
ideas, and provide feedback for products and services. Therein lies insights
that could lead to functional socio-technical systems, and general awareness
and anticipations of human actions (and interactions) when using information
technology and software services. However, limited previous work has examined
such artifacts to provide these understandings. To contribute to such
understandings and theoretical advancement we study expectation violations in
mobile apps, considered among the most engaging socio-technical systems. We
used content analysis and expectancy violation theory (EVT) and expectation
confirmation theory (ECT) to explore the evidence and nature of sanctions in
app reviews for a specific domain of apps. Our outcomes show that users respond
to expectation violation with sanctions when their app does not work as
anticipated, developers seem to target specific market niches when providing
services in an app domain, and users within an app domain respond with similar
sanctions. We contribute to the advancement of expectation violation theories,
and we provide practical insights for the mobile app community.
【5】 CitySurfaces: City-Scale Semantic Segmentation of Sidewalk Materials
标题：CitySurfaces：人行道材质的城市尺度语义分割
链接：https://arxiv.org/abs/2201.02260
备注：Sustainable Cities and Society journal (accepted); Model: this https URL
摘要：While designing sustainable and resilient urban built environment is
increasingly promoted around the world, significant data gaps have made
research on pressing sustainability issues challenging to carry out. Pavements
are known to have strong economic and environmental impacts; however, most
cities lack a spatial catalog of their surfaces due to the cost-prohibitive and
time-consuming nature of data collection. Recent advancements in computer
vision, together with the availability of street-level images, provide new
opportunities for cities to extract large-scale built environment data with
lower implementation costs and higher accuracy. In this paper, we propose
CitySurfaces, an active learning-based framework that leverages computer vision
techniques for classifying sidewalk materials using widely available
street-level images. We trained the framework on images from New York City and
Boston and the evaluation results show a 90.5% mIoU score. Furthermore, we
evaluated the framework using images from six different cities, demonstrating
that it can be applied to regions with distinct urban fabrics, even outside the
domain of the training data. CitySurfaces can provide researchers and city
agencies with a low-cost, accurate, and extensible method to collect sidewalk
material data which plays a critical role in addressing major sustainability
issues, including climate change and surface water management.
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