In this contribution, we present a computational stylistic study and comparison of classic French literary texts based on a datadriven approach where discovering interesting linguistic patterns is done without any prior knowledge. We propose an objective measure capable of capturing and extracting meaningful stylistic syntactic patterns from a given author’s work. Our hypothesis is based on the...

Emotion is at the core of understanding ourselves and others, and the automatic expression and detection of emotion could enhance our experience with technologies. In this paper, we explore the use of computational linguistic tools to derive emotional features. Using 50 and 200 word samples of naturally-occurring blog texts, we find that some emotions are more discernible than others. In partic...

Metaphor has rarely been considered an important instrument in the study of specific-purpose texts, since it is traditionally linked with resources of a poetic nature. In addition to this, the lexicon of metaphor was deemed to be of little relevance to the student, as it is not specific to the area of study. However, studies are beginning to highlight the relevance of figurative language so as ...

We present an integrated approach for automating service providers’ compliance with data protection laws and regulations, business and technical requirements in cloud computing. The techniques we propose in particular include: natural-language analysis (of legislative and regulatory texts, and corporate security rulebooks) and extraction of enforceable rules, use of sticky policies, automated p...

Selecting discriminating terms in order to represent the contents of texts is a critical problem for many applications in Information Retrieval. Most of the Information Retrieval systems index documents based on individual words that are not specific enough to evidence the contents of texts. As a consequence, there has been a growing interest in developing techniques for automatic term extracti...

Kara Lynn Andersen, in her paper "Harry Potter and the Susceptible Child Audience," argues for a rethinking of assumptions of child audiences as passive readers and viewers through an analysis of the Harry Potter phenomenon. Andersen argues that instead of categorizing children as passive and homogenous subjects of analysis, they should instead be incorporated as participants in the discourse a...

Target-dependent sentiment analysis investigates the sentiment polarities on given target mentions from input texts. Different from sentence-level sentiment, it offers more fine-grained knowledge on each entity mention. While early work leveraged syntactic information, recent research has used neural representation learning to induce features automatically, thereby avoiding error propagation of...

Moral text processing was used as an ecologically valid method for assessing implicit and explicit moral understanding and development. The authors tested undergraduates, seminarians, and graduate students in political science and philosophy for recall of moral narratives and moral expository texts. Multivariate analyses of covariance using educational experience as an independent variable, age...

In our everyday life communication interaction among people leading to mutual learning and sharing of valuable knowledge, such as chat, messaging, comments, and posts on board etc. Also, social networking websites, search engines sharing huge data texts in websites. The text is nothing but the combination of characters. Therefore, analyzing and extracting information patterns from such data set...

Analogy is heavily used in written explanations, particularly in instructional texts. We introduce the concept of analogical dialogue acts (ADAs) which represent the roles utterances play in instructional analogies. We describe a catalog of such acts, based on ideas from structure-mapping theory. We focus on the operations that these acts lead to while understanding instructional texts, using t...