Deep Mining of Custom Declarations for Commercial Goods

Stefanovskyi

Advances in Linguistics and Communication Studies

Nowadays, most of the digital content is generated within techno-social systems like Facebook or Twitter where people are connected to other people and to artefacts such as documents and concepts. These networks provide rich context for understanding the role of particular nodes. It is widely agreed that one of the most important principles in the philosophy of language is Frege's context principle, which states that words have meaning only in the context of a sentence. This chapter puts forward the hypothesis that semantics of the content of techno-social systems should be also analysed in the context of the whole system. The hypothesis is substantiated by the introduction of a method for formal modelling and mining of techno-social systems and is corroborated by a discussion on the nature of meaning in philosophy. In addition we provide an overview of recent trends in knowledge production and management within the context of our hypothesis.

Semantics of Techno-Social Spaces

Stefanovskyi

Advances in Linguistics and Communication Studies

Spreading Activation Connectivity Based Approach to Network Clustering

Advances in Wireless Technologies and Telecommunication

Vinogradov

et al. 2018

Techno-social systems generate data, which are rather different, than data, traditionally studied in social network analysis and other fields. In massive social networks agents simultaneously participate in several contexts, in different communities. Network models of many real data from techno-social systems reflect various dimensionalities and rationales of actor's actions and interactions. The data are inherently multidimensional, where “everything is deeply intertwingled”. The multidimensional nature of Big Data and the emergence of typical network characteristics in Big Data, makes it reasonable to address the challenges of structure detection in network models, including a) development of novel methods for local overlapping clustering with outliers, b) with near linear performance, c) preferably combined with the computation of the structural importance of nodes. In this chapter the spreading connectivity based clustering method is introduced. The viability of the approach and its advantages are demonstrated on the data from the largest European social network VK.

Semantics of Social Media

International Journal of End-User Computing and Development

2018

Self Cite

The presented article is focused on the comprehensive study of the issues connected with text processing on social media. First and foremost, the standpoint of the so-called ordinary language philosophy is examined. It holds the view of the meaningfulness of words in sentences as being primarily determined by the ways in which they were put to use in the practical activity and the role they played in a broader context of the lifestyle. The contemporary lifestyle is inherent in social media with its virtual discourse which is determined not only by the words used but also by the relationships between the actors that generate the content. Second, the linguistic aspects of this issue are discussed. The modeling covering the structure of social media as well as users' texts are examined with regard to computational approaches to the broadening of the context concept in Frege's contextual principle. The examples of successful mining of such model both for traditional linguistic tasks and for the use in information filtering are provided. However, it is necessary to know how to broaden and narrow down the context. This aspect is examined by the example of clustering of the largest European social network VK