Corpus-based Techniques Research Articles

Communicative Styles, Rapport, and Student Engagement: An Online Peer Mentoring Scheme

AbstractThis article investigates the communicative styles of three different peer mentors in the context of online language learning, and considers their effect on student engagement. A key objective is to show how an innovative corpus-based technique, keyword analysis, can be used as a first step towards identifying communicative styles. We view communicative style as a linguistic means by which rapport is managed amongst participants (Spencer-Oatey 2008). Our primary data include 685 forum posts, of which 273 (over 26,000 words) were by the mentors at the heart of our study. We show that the three mentors have different communicative styles: different rapport management orientations are achieved in different ways. Furthermore, we bring together multiple data sources, including participants’ posts and self-reported perception data. This allows us to find evidence on if and how communicative styles impact on student engagement and perception. We discovered that rapport enhancement aligns with increased active participation, especially if a self-effacement strategy is used, and positive student perception, but that the lack of such rapport does not automatically imply negative student perception.

A knowledge-based semantic framework for query expansion

Searching for relevant material that satisfies the information need of a user, within a large document collection is a critical activity for web search engines. Query Expansion techniques are widely used by search engines for the disambiguation of user’s information need and for improving the information retrieval (IR) performance. Knowledge-based, corpus-based and relevance feedback, are the main QE techniques, that employ different approaches for expanding the user query with synonyms of the search terms (word synonymy) in order to bring more relevant documents and for filtering documents that contain search terms but with a different meaning (also known as word polysemy problem) than the user intended. This work, surveys existing query expansion techniques, highlights their strengths and limitations and introduces a new method that combines the power of knowledge-based or corpus-based techniques with that of relevance feedback. Experimental evaluation on three information retrieval benchmark datasets shows that the application of knowledge or corpus-based query expansion techniques on the results of the relevance feedback step improves the information retrieval performance, with knowledge-based techniques providing significantly better results than their simple relevance feedback alternatives in all sets.

The Academic Literacies approach to scholarly writing: a view through the lens of the ESP/Genre approach

ABSTRACTI first briefly review two paradigms for scholarly writing, namely the English for Specific Purposes (ESP) and Academic Literacies (Ac Lits) approaches. ESP has traditionally been considered as the dominant paradigm and Ac Lits as somewhat on the margins of academic writing theory and practice. My aim in this article is to illustrate which areas and methodologies from ESP, especially corpus-based techniques, could usefully inform Ac Lits. The findings from corpus-based studies on the research article genre can reveal authorial voice, power relations, identity construction, as well as cross-cultural and cross-linguistic features, important issues raised in the Ac Lits literature. Corpus research has also been useful in revealing the academic values inscribed in text through recurrent lexico-grammatical patterns. Corpus linguistic techniques, at present largely absent from Ac Lits methodologies, could be considered to supplement the various ethnographic approaches associated with Ac Lits.

An exploratory account of the register of nursing textbooks

Abstract Given the pressing issues that affect nursing education (e.g. higher attrition and plagiarism rates), this study aims to obtain initial insight on whether nursing textbooks meet the demands of their context of situation. These demands could be listed as: construing biomedical knowledge, establishing a pattern of evidence-based nursing practice and promoting the values of person-centred care. For this analysis, I draw on aspects of parameters of context developed by Hasan (2004), Butt (2004) and Matthiessen (2015), and relate them to their semantic and lexicogrammatical realisation across different metafunctions using corpus-based techniques and detailed manual analysis of short extracts. The results may suggest that nursing textbooks may be meeting the demands of nursing as a research-based discipline but failing to model empathetic communication.

Investigating the participation of business librarians in academic program reviews using corpus-based methods

Prior research into the role of business librarians in academic program reviews has relied on surveys and interviews, revealing that librarians perceive that they are marginalized in the review process. Using a collection of program review documentation produced for the reviews of nine graduate programs offered at a Canadian business school, this study employs corpus-based techniques to obtain direct measures of librarian involvement. The findings provide objective confirmation that business librarians are not well integrated into program reviews overall, and that their contribution to the reviews of professional programs is even more limited than their contribution to the reviews of research-oriented programs. Based on best practices and missed opportunities observed as part of this study, seven strategies are suggested for integrating business librarians more fully in the program review process for the benefit of all program stakeholders.

Language and Quality Assurance: A Case Study Highlighting the Effects of Power, Resistance, and Countertactics in Academic Program Reviews

Quality assurance has been recognized as being important in higher education; however, there are numerous reports that it is challenging to engage faculty members in quality assurance processes in a meaningful way. A frequently cited reason for faculty members’ resistance is that they find the process to be authoritarian and non-collegial. This paper presents a case study which shows that changing the tone of the language used to communicate with academics about the institutional quality assurance process—from a bureaucratic and authoritative tone to a more collegial one—can serve as a countertactic to help mitigate the resistance of faculty members to this process. Using corpus-based techniques, we investigate the language used in documents to communicate with faculty members about quality assurance. We then demonstrate that, following a linguistic revision to introduce a more collegial tone to these communications, faculty members appear to be more willing to engage in the quality assurance process in a meaningful way.

Assessing EPAP lexical features: A corpus-based study

The features of specialised languages have been extensively described by scholars in the literature. Amongst them, Enrique Alcaraz’s work stands out as an exhaustive and comprehensive description of EPAP at all linguistic levels: lexical, syntactic, semantic and pragmatic. This research aims to provide a bottom-up assessment of his description on a lexical level through the implementation of corpus-based techniques on two specialised corpora of legal and telecommunications English. The results support Alcaraz’s portrayal as regards term usage, the relevance of sub-technical vocabulary, the peculiarities of Latin single and multi word terms in legal English and the significant presence and usage of abbreviations in telecommunications English.

Virtual Reading: The Prospero Project Redux

Virtual reading is proposed as a computational strategy for investigating the structure of literary texts. A computer ‘reads’ a text by moving a window N-words wide through the text from beginning to end and follows the trajectory that window traces through a high-dimensional semantic space computed for the language used in the text. That space is created by using contemporary corpus-based machine learning techniques. Virtual reading is compared and contrasted with a 40 year old proposal grounded in the symbolic computation systems of the mid-1970s. High-dimensional mathematical spaces are contrasted with the standard spatial imagery employed in literary criticism (inside and outside the text, etc.). The “manual” descriptive skills of experienced literary critics, however, are essential to virtual reading, both for purposes of calibration and adjustment of the model, and for motivating low-dimensional projection of results. Examples considered: Heart of Darkness, Much Ado About Nothing, Othello, The Winter’s Tale.

‘Us’ and ‘Them’: Early Quakers and the ‘Establishment’

The emergence of the early Quaker movement in England has been well documented. This paper focuses on Quakers’ confrontation with the establishment and with both Christian mainstream writers and other dissenting Christians. My discourse-analytic case study makes use of corpus-based techniques to uncover how Quakers and their adversaries spoke and wrote about themselves in relation to the other. I draw on theoretical studies within the field of pragmatics to show how these two groups unconsciously used markers of clusivity and stance. Results indicate a strong sense of Quaker separateness within seventeenth-century society, with implications for religious minorities today.

A corpus-based analysis of textbooks used in the orientation course for immigrants in Germany: Ideological and pedagogic implications

Abstract Contextualized within immigrants’ acquisition of specialized knowledge about the host country at the institutional level, this article examines a 64295-word corpus of textbooks written for participants of the orientation course in German politics, history and culture. Corpus-based techniques (“keyness,” collocation and qualitative examination of concordance lines) are deployed to explore the corpus. The findings reveal that the collocational patterns of the identified keywords construct particular world views vis-à-vis Germany. For instance, the keyword DDR [German Democratic Republic (GDR), aka East Germany] frequently co-occurs with negatively connoted lexis while collocates of the keywords denoting present-day Germany (e.g., Bundesrepublik Deutschland [Federal Republic of Germany] and Staat [nation, country, state]) facilitate the portrayal of Germany as a nurturing welfare state that is popular among foreigners. It is argued that such discursively-construed opposition between the “bad” GDR and the “good” Federal Republic of Germany helps to legitimize the German reunification. Furthermore, it is found that certain keywords (e.g., Sie [you], Kurs [course, class] and z.B. [e.g.]) are “metadiscourse resources” (Hyland, 2005). Their pedagogic effects are discussed in relation to the ideological implications of the research findings.

Sentiment analysis and the complex natural language

AbstractThere is huge amount of content produced online by amateur authors, covering a large variety of topics. Sentiment analysis (SA) extracts and aggregates users’ sentiments towards a target entity. Machine learning (ML) techniques are frequently used as the natural language data is in abundance and has definite patterns. ML techniques adapt to domain specific solution at high accuracy depending upon the feature set used. The lexicon-based techniques, using external dictionary, are independent of data to prevent overfitting but they miss context too in specialized domains. Corpus-based statistical techniques require large data to stabilize. Complex network based techniques are highly resourceful, preserving order, proximity, context and relationships. Recent applications developed incorporate the platform specific structural information i.e. meta-data. New sub-domains are introduced as influence analysis, bias analysis, and data leakage analysis. The nature of data is also evolving where transcribed customer-agent phone conversation are also used for sentiment analysis. This paper reviews sentiment analysis techniques and highlight the need to address natural language processing (NLP) specific open challenges. Without resolving the complex NLP challenges, ML techniques cannot make considerable advancements. The open issues and challenges in the area are discussed, stressing on the need of standard datasets and evaluation methodology. It also emphasized on the need of better language models that could capture context and proximity.

How do corpus-based techniques advance description and theory in English historical linguistics? An introduction to the special issue

How do corpus-based techniques advance description and theory in English historical linguistics? An introduction to the special issue

Patterns, Fixedness and Variability: Using PoS-grams to Find Phraseologies in the Language of Travel Journalism

As considerable attention has been paid in recent years to variability within fixed sequences (e.g. Biber, 2009; and Gray and Biber, 2013), this paper describes the use of a Corpus Linguistics technique, the Part-of-Speech-gram (usually abbreviated to PoS-gram), that allows potential variability across all slots, and is extremely effective for the discovery of phraseologies that might otherwise remain hidden. A PoS-gram is a string of Part-of-Speech categories (Stubbs, 2007) the tokens of which are strings of words that have been annotated with these PoS tags. Hence, in each slot of the PoS-gram, any word can occur as long as it belongs to the PoS category of that particular position. Despite the vast potential of this technique, it has up to now been largely underused.This paper will illustrate the utility of PoS-grams by way of analysis of a 450,000 token corpus composed of travel journalism texts from the BBC website. The PoS-grams extracted are compared with a database of PoS-grams obtained from the 100M token BNC. While a large number were found to be statistically significant, in-depth analysis was conducted on PoS-grams containing the inflected superlative adjective form AJS, a feature previously recognized as being central to tourism/travel-writing though without reference to corpus-based techniques (e.g. Dann, 1996).

Attitudes towards English in Norway: A corpus-based study of attitudinal expressions in newspaper discourse

AbstractThis article explores some dimensions of how the role of the English language in Norway has been discursively constructed in newspapers during recent years, based on the analysis of data from the five-year period 2008–2012. The analysis is conducted using a specialised corpus containing 3,743 newspaper articles which were subjected to corpus-based macro-analyses and techniques, as well as manual micro-level analyses and categorisation. The main focus of the analysis is on the manifestation of attitudes through various ways of expression, such as the occurrence of lexical sequences and conceptual metaphors related to language. The results show that even though positive perceptions of English were quite frequent in the data, the main part consisted of expressions where English is seen in a negative light. Hence, a fairly negative attitude towards the role of English is predominant, as illustrated by the most frequent conceptual metaphor,

Structural Similarities between Brain and Linguistic Data Provide Evidence of Semantic Relations in the Brain

This paper presents a new method of analysis by which structural similarities between brain data and linguistic data can be assessed at the semantic level. It shows how to measure the strength of these structural similarities and so determine the relatively better fit of the brain data with one semantic model over another. The first model is derived from WordNet, a lexical database of English compiled by language experts. The second is given by the corpus-based statistical technique of latent semantic analysis (LSA), which detects relations between words that are latent or hidden in text. The brain data are drawn from experiments in which statements about the geography of Europe were presented auditorily to participants who were asked to determine their truth or falsity while electroencephalographic (EEG) recordings were made. The theoretical framework for the analysis of the brain and semantic data derives from axiomatizations of theories such as the theory of differences in utility preference. Using brain-data samples from individual trials time-locked to the presentation of each word, ordinal relations of similarity differences are computed for the brain data and for the linguistic data. In each case those relations that are invariant with respect to the brain and linguistic data, and are correlated with sufficient statistical strength, amount to structural similarities between the brain and linguistic data. Results show that many more statistically significant structural similarities can be found between the brain data and the WordNet-derived data than the LSA-derived data. The work reported here is placed within the context of other recent studies of semantics and the brain. The main contribution of this paper is the new method it presents for the study of semantics and the brain and the focus it permits on networks of relations detected in brain data and represented by a semantic model.

Corpus-based analysis of domain-specific languages

As more domain-specific languages (DSLs) are designed and developed, the need to evaluate these languages becomes an essential part of the overall DSL life cycle. Corpus-based analysis can serve as an evaluation mechanism to identify characteristics of the language after it has been deployed by looking at how end-users employ it in practice. This analysis that is based on actual usage of the language brings a new perspective which can be considered by a language engineer when working toward improving the language. In this paper, we describe our utilization of corpus-based analysis techniques and exemplify them on the evaluation of the Puppet and ATL DSLs. We also outline an Eclipse plug-in, which is a generic corpus-based DSL analysis tool that can accommodate the evaluation of different DSLs.

The Efficacy of Corpus-based Pedagogical Techniques for Academic Writing

The utility of corpora as a writing tool has not yet been concretely established due to the emphasis of qualitative methods for data collection and the utilization of designs requiring a great deal of independent learning. The purpose of this study was to empirically evaluate corpus-based pedagogical techniques for writing that systematically guide student inquiry. This quasi-experimental study employed a switching-replications design with two classrooms of Korean high and middle school English teachers (N = 21). In the first phase of treatment, only participants of the experimental group were asked to check each noun using the corpus. In the second phase of treatment, the experimental and control groups were swapped and the procedure was repeated. Comparison of scores after each phase revealed no significant differences between the experimental and control groups. Although follow-up surveys revealed that most participants were able to recognize the potential of the corpus, the participants were unable to provide tangible examples of advantages. Overall, results suggest that a more highly scaffolded framework of training, which guides data collection and the development of a hypothesis, is needed to transition the learner into the role of an independent researcher.

“Yes, your honor!”: A corpus-based study of technical vocabulary in discipline-related movies and TV shows

Abstract Vocabulary is an essential element of every second/foreign language teaching and learning program. While the goal of language teaching programs is to focus on explicit vocabulary teaching to promote learning, “materials which provide visual and aural input such as movies may be conducive to incidental vocabulary learning.” ( Webb and Rodgers, 2009 , p. 412) The present study uses corpus-based techniques to investigate the extent to which watching discipline-related movies and TV shows in a second/foreign language may facilitate incidental learning of technical vocabulary. A corpus of 130,000 words was complied from movies/TV shows with legal content to track the frequency and vocabulary distribution of legal technical vocabulary items. The findings show that the majority of technical terms is encountered more than ten times in movies/shows, and that technical terms tend to co-occur together in particular segments of movies and episodes. The results suggest that the potential for incidental vocabulary learning through movies and TV shows with a legal content is high and that these media could also be used for teaching language patterns in an English for Specific Purposes (ESP) classroom with relevant focus. Hence, watching discipline specific TV shows and movies is beneficial for both incidental learning and explicit teaching.

A corpus-based look at short turns in university classroom interaction

AbstractThe aim of the present study is to explore the lexical content of short turns in university classroom discourse. Corpus-based techniques were applied to identify a large number of turns to analyze their lexical content in over two hundred university class sessions. The findings show that, although students take sixty per cent of the turns in our university classrooms, they use only twenty per cent of the total number of words. Consequently, students would produce short turns most of the times while teachers would engage in longer stretches of talk. The results also indicate that short turns generally mark intensive interactional sequences. More specifically, a closer look at the lexical items in these short turns and the functions they serve clearly show that while teachers offer support, elicit further elaboration or prompt reformulation, students mostly indicate agreement, understanding and involvement with these short turns. Considering the turn as a unit of analysis and its characteristic features such as turn-length and lexical variation, the findings of the lexical analysis of short turns suggest that participant roles can be well-defined in the classroom context.

Quality issues in Thesaurus building. A case study from the medical domain

To ensure the quality of a medical thesaurus is a non-trivial task, due to the inherent complexity of medical terminology. The peculiarities of the medical sublanguage and the subjectivism of lexicographers' choices complicate the thesaurus construction process. Our experience is based on the MorphoSaurus lexicon, the basis of a biomedical cross-language indexing and retrieval system. We describe two complementary maintenance approaches, viz. i) corpus-based error detection, and ii) thesaurus anomaly detection. These techniques were developed to detect so-called dynamic and static errors, which are committed by the lexicographers during the construction and maintenance process. Considering multilingual parallel corpora, the distribution of semantic identifiers should be similar whenever comparing related texts in different languages. In the first approach, those semantic identifiers are identified that exhibit greatest frequency variations when comparing text pairs. A manual review of these search results is supposed to spot content errors, which are subsequently classified and fixed by the lexicographers. The second approach analyses transaction-based anomalies, which are identified by interpreting the log of lexicographers' actions during thesaurus maintenance. This methodology highlights the four most common types of this kind of anomaly and evaluates the effectiveness of the corpus-based detection techniques. The overall quality improvement of the thesaurus was evaluated using the OHSUMED IR benchmark.