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In this work we presented an ENEAGRID approach toward Parallel Text Mining of Big Data in massive cultural Textual Corpora. ENEAGRID provides computation, storage resources and services for Text Mining Communities in a ubiquitous and remote way. ENEA distributed e-Infrastructure and cloud services enable the management of research process in Economic-Social Sciences, Digital Humanities and Cybersecurity, providing technology solutions and tools to academic departments and research institutes. With these research activity ENEA opens to collaborations with other Research Communities interested in Parallel Text Mining of Massive Volume of Text Data (PB &TB-sized corpora) in e-Humanities, Heritage Science, Social Sciences, Big Data, Web Mining, Business Intelligence, Open Source Intelligence, Artificial Intelligence, etc

After showing the advantages of formulating lexical structures with variable elements in terms of symbolic objects (), the Authors propose to introduce the information which determine their building in the analysis of elementary units ( ). It is worth noting that, dealing with symbolic data, the observed textual units disappear by the collapsing procedure. In order to visualize forms, an analysis on elementary data, introducing the external information on the complex structure they belong, has been proposed. This analysis can be usefully performed complementary to the symbolic objects analysis, because it enables to analyze the dependence relations of the forms on the contextual information in which they have been used. In order to enrich the analysis of textual data, it is possible to introduce other external information, related to the fragments where the forms appear. In doing that by a double partial analysis, we represent on low-dimensional spaces the relational structure existing between the two sets of information introduced. Forms and fragments can be represented as supplementary points, in order to study the role they played in those relations. An application dealing with a very large of lexical structures with variable elements, extracted from the Italian newspaper “La Repubblica” during the Nineties, has been performed, in order to show the relation between years and contextual information in the different identified context, and the single forms mainly involved.

interference” and the influence of “translation universals”. However, the characteristics of what was termed “translationese” have been identified and studied only sporadically through the systematic quantitative analysis of text corpora. The present study is specifically focussed on Italian and is aimed at investigating the language features of a corpus of newspaper articles collected ad-hoc and compared and contrasted with a similar corpus of newspaper articles originally written in Italian. The analysis was conducted according to the principles of corpus linguistics by means of dedicated text analysis software (Taltac2 in particular and TreeTagger). The lexicometric data provided by the software supply the starting material to investigate the lexical features of translated Italian, regardless of the subject matter dealt with in the articles. The results obtained from empirical evidence provides more insight into the linguistic traits of newspaper articles translated into Italian.

The paper aims at showing the advantages of formulating lexical structures with variable elements (LSVE) in terms of symbolic objects (OS). The proposal main consequence is the collapse of the huge information usually present in a text into matrices of complex data. Thus, it is possible to use statistical tools in order to analyse the underlying properties of lexical structures by taking into account their different component distributions. Describing lexical structures with variable elements as symbolic data improves the effort of text mining by putting in a strict relation the knowledge extraction and the statistical analysis steps. The study of such lexical structures is performed by applying a factorial analysis on complex data. An application deals with a very large corpus extracted from Italian newspaper “La Repubblica” during the Nineties. In this study, we analyse the relations among the different components of some lexical structures with variable elements and the temporal evolution of some peculiar semantic traits, related to geographical-historical-political contexts.

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