Various applications are developed today on top of microblogging services like Twitter. In order to engineer Web applications which operate on microblogging data, there is a need for appropriate filtering techniques to identify messages. In this paper, we focus on detecting Twitter messages (tweets) that report on social events. We introduce a filtering pipeline that exploits textual features and n-grams to classify messages into event related and non-event related tweets. We analyze the impact of preprocessing techniques, achieving accuracies higher than 80%. Further, we present a strategy to automate labeling of training data, since our proposed filtering pipeline requires training data. When testing on our dataset, this semi-automated method achieves an accuracy of 79% and results comparable to the manual labeling approach.

The economy is subject to changes. It is characterized by the uneven nature of expanded reproduction: periods of increased production and consumption are combined with recessions and crises; new development trajectories emerge. The cyclical nature of economic development means that the main indicators and parameters of this process are wave-like. Interest in cyclical fluctuations is increasing, especially during crises. Each cycle has its own development and technological structure. New technologies and innovations spread during the upward wave of the subsequent cycle. During the downward wave, the development of the technological structure is slowing down, facing economic and social constraints caused by market limits and insufficient production efficiency. Previously dominant technologies and institutions become exhausted. It creates conditions for the development of new leading technologies, a new technological order and new social institutions. Thus, crises stimulate technological development. The article discusses Kitchin, Juglar, Kuznets, Kondratyev cycles and their regularities. The indicators used for tracking economic cycles, their turning points whose dynamics coincides with cyclical fluctuations of the economy are as follows: GDP growth rate; unemployment rate; consumer price index; investment growth rate; industrial production growth rate; gross saving growth rate; refinancing rate.

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The article aims to describe structural changes in the agrarian sector of Irkutsk region caused by the government support for small businesses, simplified procedures for farm registering, accounting for property and production results, and taxation, which contributed to the development of peasant farming. The government support is required, but it can change the structure of areas and gross grain crops since peasant farms increase quantitative indicators rather than improve quality parameters (yield, productivity). This is especially true for the animal husbandry sector. With changes in government policies and decreasing government support, it will be difficult for individual farms to exist, since they lag behind collective farms in terms of maneuverability, financial capabilities, production and credit resources, which can cause new structural changes in a benefit for agricultural holdings. The government policy aimed at preserving the traditional way of life of the rural population should stimulate both the development of rural areas and agricultural production, and prevent the disintegration of collective farms that have competitive advantages

This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 4.0 Unported License, permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Financing is a type for cash support. Financial resources of the enterprise, which are directed to its development, are formed at the expense of depreciation deductions, profits received from all types of economic and financial activities, additional share contributions of participants in partnerships, funds received from issuing bonds, funds mobilized through issuing and placing shares in joint-stock companies of public and non-public types, long-term bank loans and other types of credits. There are situations, when enterprises do not possess own resources for its development and especially for innovations implementation, and the attraction of borrowed funds is limited by a high-risk degree of investments in production. Forms and methods of entrepreneurship financing are very diverse. Each of the forms used has certain advantages and disadvantages. Therefore, any investment project should have a thorough assessment for the consequences of using various alternative schemes and forms of financing. The article describes the main peculiarities of organization of production processes, depending on industry-specific enterprises. The main advantages of using the credit form of financing for production processes in modern economic conditions are revealed. There is a generalized classification of loan types provided to business entities, and peculiarity analysis of loans use in financing production processes. The paper provides a generalized algorithm for crediting production processes in the Russian Federation at the present stage of development.