Tourism research from its inception to present day: Subject area, geography, and gender distributions.

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.

Data for Sochi 2014 Olympics discussion on social media.

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.

Inter-Coder Agreement in One-to-Many Classification: Fuzzy Kappa.

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.

Climate change impacts on forestry.

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.