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This paper uses text data mining to identify long-term developments in tourism academic research from the perspectives of thematic focus, geography, and gender of tourism authorship. Abstracts of papers published in the period of 1970-2017 in high-ranking tourist journals were extracted from the Scopus database and served as data source for the analysis. Fourteen subject areas were identified using the Latent Dirichlet Allocation (LDA) text mining approach. LDA integrated with GIS information allowed to obtain geography distribution and trends of scholarly output, while probabilistic methods of gender identification based on social network data mining were used to track gender dynamics with sufficient confidence. The findings indicate that, while all 14 topics have been prominent from the inception of tourism studies to the present day, the geography of scholarship has notably expanded and the share of female authorship has increased through time and currently almost equals that of male authorship.

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Presented data is related to the research article "Sochi 2014 Olympics on Twitter: Perspectives of Hosts and Guests" [2].  The data were collected through regular API Twitter search for five months windowing 2014 Sochi Olympic Games and further used for cluster analysis and analysis of the sentiment on the Games. The main dataset contains 616 thousand tweets, rigorously cleaned and filtered to remove irrelevant content. To comply with the Twitter API user agreement, the dataset presented in this article includes only generalized daily data with all information contained in individual tweets removed. The proposed use of the dataset is academic research of changing discussion on the topics related to Mega-events in conjunction with political events.

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Content analysis involves classification of textual, visual, or audio data. The inter-coder agreement is estimated by making two or more coders to classify the same data units, with subsequent comparison of their results. The existing methods of agreement estimation, e.g., Cohen's kappa, require that coders place each unit of content into one and only one category (one-to-one coding) from the pre-established set of categories. However, in certain data domains (e.g., maps, photographs, databases of texts and images), this requirement seems overly restrictive. The restriction could be lifted, provided that there is a measure to calculate the inter-coder agreement in the one-to-many protocol. Building on the existing approaches to one-to-many coding in geography and biomedicine, such measure, fuzzy kappa, which is an extension of Cohen's kappa, is proposed. It is argued that the measure is especially compatible with data from certain domains, when holistic reasoning of human coders is utilized in order to describe the data and access the meaning of communication.

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Fire has been the dominant disturbance in boreal America since the Pleistocene, resulting in a spatial mosaic in which the most fire occurs in the continental northwest. Spatial variation in snowshoe hare (Lepus americanus) density reflects the fire mosaic. Because fire initiates secondary forest succession, a fire mosaic creates variation in the abundance of early successional plants that snowshoe hares eat in winter, leading to geographic variation in hare density. We hypothesize that fire is the template for a geographic mosaic of natural selection: where fire is greatest and hares are most abundant, hare browsing has most strongly selected juvenile-phase woody plants for defense. We tested the hypothesis at multiple spatial scales using Alaska birch (Betula neoalaskana) and white birch (Betula papyrifera). We also examined five alternative hypotheses for geographic variation in antibrowsing defense. The fire-hare-defense hypothesis was supported at transcontinental, regional, and local scales; alternative hypotheses were rejected. Our results link transcontinental variation in species interactions to an abiotic environmental driver, fire. Intakes of defense toxins by Alaskan hares exceed those by Wisconsin hares, suggesting that the proposed selection mosaic may coincide with a geographic mosaic of coevolution.

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Changing temperature and precipitation pattern and increasing concentrations of atmospheric CO(2) are likely to drive significant modifications in natural and modified forests. Our review is focused on recent publications that discuss the changes in commercial forestry, excluding the ecosystem functions of forests and nontimber forest products. We concentrate on potential direct and indirect impacts of climate change on forest industry, the projections of future trends in commercial forestry, the possible role of biofuels, and changes in supply and demand.

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