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This paper investigates how the notion of future is represented in a large corpus of Englishlanguage blogs related to climate change, with an overarching interest in exploring to what extent the perspectives of gloom-and-doom versus more positive perspectives of a sustainable society are represented. We address the following questions: 1) How are representations of the future expressed linguistically in public debates related to climate change? 2) What meanings do the representations convey? Our principal contribution is a set of nine meaning categories that characterise different representations of the future: the categories were derived by following a corpus-assisted discourse analysis approach. Within these categories, the large presence of characterisations related to sustainability, as well as frequent positive value-laden characterisations, are noteworthy. Representations reflect various perspectives of a future for humanity, for nature, and for countries as well as for economies. Further, we have found that when climate change is viewed as a threat, it is in relation to nature, humans and security, while it is seen as an opportunity for growth in business and industry. The results provide knowledge on how people conceive the possible impacts of global climate and environmental change within two broad perspectives of a "gloom-and-doom" versus a "bright" future. This may contribute to an improved basis for political decision making on measures in order to avoid dangerous consequences as well as to encourage engagement in the shift towards a low-carbon future.

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We present a method being developed to extract information about characters' emotions in films. It is suggested that this information can help describe higher levels of multimedia semantics relating to narrative structures. Our method extracts information from audio description that is provided for the visually-impaired with an increasing number of films. The method is based on a cognitive theory of emotions that links a character's emotional states to the events in their environment. In this paper the method is described along with some preliminary evaluation and discussions about the kinds of novel video retrieval and browsing applications it may support.

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