A well-established finding in the simulation literature is that participants simulate the positive argument of negation soon after reading a negative sentence, prior to simulating a scene consistent with the negated sentence (Kaup, Ludtke, & Zwaan, 2006; Kaup, Yaxley, Madden, Zwaan, & Ludtke, 2007). One interpretation of this finding is that negation requires two steps to process: first represent what is being negated then "reject" that in favour of a representation of a negation-consistent state of affairs (Kaup et al., 2007). In this paper we argue that this finding with negative sentences could be a by-product of the dynamic way that language is interpreted relative to a common ground and not the way that negation is represented. We present a study based on Kaup et al. (2007) that tests the competing accounts. Our results suggest that some negative sentences are not processed in two steps, but provide support for the alternative, dynamic account.

When processing negative sentences without context, participants often represent states of the positive arguments. Why and when does this occur? Using visual world eyetracking, participants listened to positive and negative sentences in simple or cleft forms (e.g. [It is] Matt [who] hasn't shut his dad's window), while looking at scenes containing a target and a competitor (matches or mismatches the implied shape of the final noun). Results show that in the simple but not the cleft condition, there is a difference between negatives and positives: shortly after the verb, there is more looks to the competitor in the simple negatives than the positives. This suggests that the representation of the positive is not a mandatory first step of negation processing (as per rejection accounts). Rather results support the Question Under Discussion (QUD) accommodation account wherein both sentence content and contextual source of relevance are targets of incremental sentence processing.

L AUGHTER is a crucial signal for communication and managing interactions. Until now no consensual approach has emerged for classifying laughter. We propose a new framework for laughter analysis and classification, based on the pivotal assumption that laughter has propositional content. We propose an annotation scheme to classify the pragmatic functions of laughter taking into account the form, the laughable, the social, situational, and linguistic context. We apply the framework and taxonomy proposed in a multilingual corpus study (French, Mandarin Chinese and English), involving a variety of situational contexts. Our results give rise to novel generalizations about the range of meanings laughter exhibits, the placement of the laughable, and how placement and arousal relate to the functions of laughter. We have tested and refuted the validity of the commonly accepted assumption that laughter directly follows its laughable. In the concluding section, we discuss the implications our work has for spoken dialogue systems. We stress that laughter integration in spoken dialogue systems is not only crucial for emotional and affective computing aspects, but also for aspects related to natural language understanding and pragmatic reasoning. We formulate the emergent computational challenges for incorporating laughter in spoken dialogue systems.

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Smart cities link the city services, citizens, resource and infrastructures together and form the heart of the modern society. As a "smart" ecosystem, smart cities focus on sustainable growth, efficiency, productivity and environmentally friendly development. By comparing with the European Union, North America and other countries, smart cities in China are still in the preliminary stage. This study offers a comparative analysis of ten smart cities in China on the basis of an extensive database covering two time periods: 2005-2007 and 2008-2010. The unsupervised computational neural network self-organizing map (SOM) analysis is adopted to map out the various cities based on their performance. The demonstration effect and mutual influences between these ten smart cities are also discussed by using social network analysis. Based on the smart city performance and cluster network, current problems for smart city development in China were pointed out. Future research directions for smart city research are discussed at the end this paper.

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Understanding the import of laughter, has interested philosophers and literary scholars for millennia and, more recently, psychologists, biologists, neuroscientists, and linguists. However, the assumption has been that laughter lacks meaning akin to what words and phrases possess and that it does not contribute to the compositional construction of meaning. In this paper, we argue that, in fact, laughter (and other non-verbal social signals like smiling, sighing, frowning) has propositional content-it involves reference to external real world events, has stand alone meanings, and participates in semantic and pragmatic processes like repair, implicature, and irony. We show how to develop a formal semantic and pragmatic account of laughter embedded in a general theory of conversational interaction and emotional reasoning and show how to explain the wide, indeed in principle unbounded range of uses laughter exhibits. We show how our account can be extended to other non-verbal social signals like smiling, sighing, eye rolling, and frowning. Should laughter and its ilk be incorporated in the grammar? We suggest that they probably should be, if one assumes a conversationally-oriented view of grammar. But various open issues remain.

In a busy space, people encounter many other people with different viewpoints, but classic studies of perspective-taking examine only one agent at a time. This paper explores the issue of selectivity in visual perspective-taking (VPT) when different people are available to interact with. We consider the hypothesis that humanization impacts on VPT in four studies using virtual reality methods. Experiments 1 and 2 use the director task to show that for more humanized agents (an in-group member or a virtual human agent), participants were more likely to use VPT to achieve lower error rate. Experiments 3 and 4 used a two-agent social mental rotation task to show that participants are faster and more accurate to recognize items which are oriented towards a more humanized agent (an in-group member or a naturally moving agent). All results support the claim that humanization alters the propensity to engage in VPT in rich social contexts.