Preliminary Conference Agenda

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Session Overview
Preliminary Papers 5: Preliminary Papers: Information Organization and Retrieval
Friday, 24/Mar/2017:
1:30pm - 3:00pm

Location: Changjiang Hall
Location: Third Floor Capacity: 60 Size: 80㎡

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Personalized Community Detection in Scholarly Network

Zheng Gao1, Xiaozhong Liu2

1indiana university bloomington, United States of America; 2indiana university bloomington, United States of America

Most graph clustering methods partition a network into communities based solely on the topology and structure of the network. Due to this, the means via which communities are detected on a network are insensitive to the preferences of a user who is searching the network with a specific, personalized information need. Such partition algorithms may be of diminished value for scholars exploring networks of research if these scholars possess prior preferences on what information they consider relevant. To better address this type of information seeking behavior, we introduce a personalized community detection algorithm that provides higher-resolution partitioning of areas of the network that are more relevant to

a provided seed query. This algorithm utilizes the divisive Girvan-Newman approach but incorporates a user’s personal preferences as a prior. We show that this personalized algorithm can produce a more fine-tuned partition of a scholarly network when compared to existing prior-insensitive approaches.

Understanding Young People’s We-Intention to Contribute in Danmaku Websites: Motivational, Social, and Subculture Influence

Yuxiang Zhao1, Xixian Peng2, Jian Tang3, Shijie Song4

1Nanjing University of Science and Technology, China, People's Republic of; 2Dept of Information Systems, National University of Singapore, Singapore; 3School of Information, Central University of Finance and Economics, China; 4Ford Motor Research & Engineering, Nanjing, China

Various social media have promoted the emergence and development of diverse subcultures among the young generation. ACG (Animation, Comic, and Game) is such an adolescent subculture which is fascinating to a group of young people, named Otaku. Danmaku video sharing website is an important social media for them to communicate, and reflects an obvious hedonic characteristic of usage. In this study, we propose a research model in the context of Danmaku websites. First, we include an important social driver, sense of virtual community (SOVC), to predict we-intention of participants. Second, we employ social presence theory and uses and gratifications theory to understand the formation of SOVC. In addition, we argue that when considering young people’s usage of innovative IT product, the degree of their identity within the subcultural involved in the product should also be included. Finally, a longitudinal field study is designed to test the research model and hypotheses.

Impact of Location-based Augmented Reality Games on People’s Information Behavior: A Case Study of Pokémon GO

Jin Ha Lee, Travis Windleharth, Jason Yip, Marc Schmalz

University of Washington, United States of America

Location-based augmented reality games that blend the real-world experience with virtual world gameplay are becoming increasingly popular. We aim to improve our understanding of how these new types of games will impact people’s information behaviors in both physical and virtual places, specifically investigating the case of Pokémon GO. We conducted over 100 hours of field observation of Pokémon GO players in numerous public places and also monitored over 200 online communities related to the game, in addition to conducting interviews of 30 players. Our key findings include observation of the emergence of ad-hoc information grounds in physical spaces where much of the information sharing occurred, as well as a crowdsourced data-driven approach in problem solving and information sharing in online environments. We discuss the common types of information sharing that occur in both of these environments in detail, and identify areas for future research.

#accessibilityFail: Exploring the Potential of Using Social Media Posts to Identify Accessibility Problems

Hanlin Li, Erin Brady

Indiana University-Purdue University Indianapolis, United States of America

Social media reports of accessibility problems can document accessibility issues encountered in situ. We analyzed 200 posts about discussions around accessibility and 166 posts that describe accessibility problems from Twitter and Instagram. Our findings show that people use existing platforms to have robust conversations to identify and communicate accessibility problems. We discuss the practical implications of using human work to facilitate remote accessibility evaluation combining real-life scenarios and design an experiment to investigate the feasibility of crowdsourcing to identify accessibility issues remotely.

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