Despite the recent and ongoing progress in using text-mining tools to automatically analyze large text corpora, there remains significant potential to facilitate the study of social action in social science research. In this context, particularly the disambiguation (who is referred to in a text?) and specification (which demographic…

This paper considers the adoption of computational techniques within research designs modeled after the extended case method. Echoing calls to augment the power of contemporary researchers through the adoption of computational text analysis methods, we offer a framework for thinking about how such techniques can be integrated into…

One of the greatest impacts of corpus linguistics on language teaching has been in the recognition of the importance of collocation. A very influential guide for language teachers with regard to teaching collocation has been the Lexical Approach. Activities pointing students to rich collocational information in monolingual dictionaries, in texts…

This work is a contribution to the usefulness of climate-related authentic material for pedagogical purposes in Higher Education. The two case studies had the aim of raising environmental awareness of a sustainable future among university students, while encouraging them to explore language use and draw their own conclusions and considerations…

Coh-Metrix is among the broadest and most sophisticated automated textual assessment tools available today. Automated Evaluation of Text and Discourse with Coh-Metrix describes this computational tool, as well as the wide range of language and discourse measures it provides. Section I of the book focuses on the theoretical perspectives that led to…

The goal of this article is to preserve and distribute the information presented at the LASI (2014) workshop on Coh-Metrix, a theoretically grounded, computational linguistics facility that analyzes texts on multiple levels of language and discourse. The workshop focused on the utility of Coh-Metrix in discourse theory and educational practice. We…

Textual information mining is a challenging problem that has resulted in the creation of many different rule-based linguistic query languages. However, these languages generally are not optimized for the purpose of text mining. In other words, they usually consider queries as individuals and only return raw results for each query. Moreover they…

Within the landscape of educational data, textual natural language is an increasingly vast source of learning-centered interactions. In natural language dialogue, student contributions hold important information about knowledge and goals. Automatically modeling the dialogue act of these student utterances is crucial for scaling natural language…

Text analytics refers to the process of analyzing unstructured data from documented sources, including open-ended surveys, blogs, and other types of web dialog. Text analytics has enveloped the concept of text mining, an analysis approach influenced heavily from data mining. While text mining has been covered extensively in various computer…

Illustrates how Radial Basis Function (RBF) network techniques can be used to explore questions concerning authorship of historic documents. Demonstrates the utility and potential for using quantitative techniques to assist in the decision-making process in relatively subjective disciplines. Compares RBF neural network techniques with more…