This article explores the portability of a coreference resolver across a variety of eight text genres. Besides newspaper text, we also include administrative texts, autocues, texts used for external communication, instructive texts, wikipedia texts, medical texts and unedited new media texts. Three sets of experiments were conducted. First, we investigated each text genre individually, and stud...

Task difficulty across different macro-genres continues to remain among less attended areas in second language development studies. This study examined the correlation between task difficulty across the descriptive, narrative, argumentative, and expository macro-genres. The three components of task difficulty (i.e., code complexity, cognitive complexity, and communicative stress) were also comp...

Academic writing, including in English as an Academic Lingua Franca, has become a central feature for the majority of European university students. Despite a large body of research, we find that conceptualisations of student writing still tend to assume a direct link to expert academic genres, which are often explicitly evoked as models. Within a genre analytic paradigm, however, the importance...

Machine translation (MT) has been both praised and criticized since the 1930’s when it was first introduced. Today, MT − much improved since then, is a vital tool for the human translator, although not without its problems. One important unresolved issue is the success of MT for different text types. In the present study, we compare the performance of German-English machine translation in four ...

This study proposes an index of representativeness for analyzing the characteristics of academic paper categories. Many textual indices have been proposed in the field of computational stylistics, but all of the previous indices are limited in that they (a) focus only on the styles of the texts; (b) return an absolute value for every text, and (c) are based on the number of tokens. In this stud...

This paper proposes a method for classifying movie genres by only looking at text reviews. The data used are from Large Movie Review Dataset v1.0 [4] and IMDb. This paper compared a K-nearest neighbors (KNN) model and a multilayer perceptron (MLP) that uses tf-idf as input features. The paper also discusses different evaluation metrics used when doing multi-label classification. For the data us...

Understanding the textual distinction between spokenness-informality and writtenness-formality serves many purposes. It can facilitate text mining, improve parser accuracy, offer better appraisals of student writing, and may also facilitate better interpretations of experimental data. Previous studies of such textual variation (e.g., Biber, 1988, Louwerse et al., 2004) have failed to produce a ...

Formality is an important dimension of language style. Texts of different genres tend to have different degrees of formality. F-score (formality-score) is a most popular measure for formality to differ genres. It uses a method of combining proportions of words of different types, with nouns, adjectives, articles and prepositions as positive elements, and adverbs, verbs and interjections as nega...

This paper describes a phrase-based machine translation approach to normalize Dutch user-generated content (UGC). We compiled a corpus of three different social media genres (text messages, message board posts and tweets) to have a sample of this recent domain. We describe the various characteristics of this noisy text material and explain how it has been manually normalized using newly develop...