The unique aquatic nature of swimming makes it very difficult to use social or technical strategies to mitigate the tediousness of monotonous exercises. In this study, we propose MobyDick, a smartphone-based multi-pla...
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ISBN:
(纸本)9781450331432
The unique aquatic nature of swimming makes it very difficult to use social or technical strategies to mitigate the tediousness of monotonous exercises. In this study, we propose MobyDick, a smartphone-based multi-player exergame designed to be used while swimming, in which a team of swimmers collaborate to hunt down a virtual monster. In this paper, we present a novel, holistic game design that takes into account both human factors and technical challenges. Firstly, we perform a comparative analysis of a variety of wireless networking technologies in the aquatic environment and identify various technical constraints on wireless networking. Secondly, we develop a single phone-based inertial and barometric stroke activity recognition system to enable precise, real-time game inputs. Thirdly, we carefully devise a multi-player interaction mode viable in the underwater environment highly limiting the abilities of human communication. Finally, we prototype MobyDick on waterproof offthe- shelf Android phones, and deploy it to real swimming pool environments (n = 8). Our qualitative analysis of user interview data reveals certain unique aspects of multi-player swimming games. Copyright 2014 ACM.
Models of sentiment analysis in text require an understanding of what kinds of sentiment-bearing language are generally used to describe specific topics. Thus, fine-grained sentiment analysis requires both a topic lex...
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ISBN:
(纸本)9781450312301
Models of sentiment analysis in text require an understanding of what kinds of sentiment-bearing language are generally used to describe specific topics. Thus, fine-grained sentiment analysis requires both a topic lexicon and a sentiment lexicon, and an affective mapping between both. For instance, when one speaks disparagingly about a city (like London, say), what aspects of city does one generally focus on, and what words are used to disparage those aspects? As when we talk about the weather, our language obeys certain familiar patterns - what we might call clichés and stereotypes - when we talk about familiar topics. In this paper we describe the construction of an affective stereotype lexicon, that is, a lexicon of stereotypes and their most salient affective qualities. We show, via a demonstration system called MOODfinger, how this lexicon can be used to underpin the processes of affective query expansion and summarization in a system for retrieving and organizing news content from the web. Though we adopt a simple bipolar +/- view of sentiment, we show how this stereotype lexicon allows users to coin their own nuanced moods on demand. Copyright is held by the International World Wide web Conference Committee (IW3C2).
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