Search results

This study attempts to evaluate the effect of the corpus-based inductive teaching approach with multiple academic corpora (PICA, CAEC and Oxford Corpus of Academic English) and conventional deductive teaching approach (i.e., multiple-choice items, filling the gap, matching and underlining) on learning academic collocations by Iranian advanced EFL learners (students learning English as a foreign language).

This is a quasi-experimental, quantitative and qualitative study.

The result showed the experimental group outperformed significantly compared with the control group. The experimental group also shared their perception of the advantages and disadvantages of the corpus-assisted language teaching approach.

Despite growing progress in language pedagogy, methodologies and language curriculum design, there are still many teachers who experience poor performance in their students' vocabulary, whether in comprehension or production. In Iran, for example, even though mandatory English education begins at the age of 13, which is junior and senior high school, students still have serious problems in language production and comprehension when they reach university levels.

This article presents two Brazilian Portuguese corpora collected from different media concerning public security issues in a specific location. The primary motivation is supporting analyses, so security authorities can make appropriate decisions about their actions.

The corpora were obtained through web scraping from a newspaper's website and tweets from a Brazilian metropolitan region. Natural language processing was applied considering: text cleaning, lemmatization, summarization, part-of-speech and dependencies parsing, named entities recognition, and topic modeling.

Several results were obtained based on the methodology used, highlighting some: an example of a summarization using an automated process; dependency parsing; the most common topics in each corpus; the forty named entities and the most common slogans were extracted, highlighting those linked to public security.

Some critical tasks were identified for the research perspective, related to the applied methodology: the treatment of noise from obtaining news on their source websites, passing through textual elements quite present in social network posts such as abbreviations, emojis/emoticons, and even writing errors; the treatment of subjectivity, to eliminate noise from irony and sarcasm; the search for authentic news of issues within the target domain. All these tasks aim to improve the process to enable interested authorities to perform accurate analyses.

The corpora dedicated to the public security domain enable several analyses, such as mining public opinion on security actions in a given location; understanding criminals' behaviors reported in the news or even on social networks and drawing their attitudes timeline; detecting movements that may cause damage to public property and people welfare through texts from social networks; extracting the history and repercussions of police actions, crossing news with records on social networks; among many other possibilities.

The work on behalf of the corpora reported in this text represents one of the first initiatives to create textual bases in Portuguese, dedicated to Brazil's specific public security domain.

By far, the corpus for the quotation extraction and quotation attribution tasks in Indonesian is still limited in quantity and depth. This study aims to develop an Indonesian corpus of public figure statements attributions and a baseline model for attribution extraction, so it will contribute to fostering research in information extraction for the Indonesian language.

The methodology is divided into corpus development and extraction model development. During corpus development, data were collected and annotated. The development of the extraction model entails feature extraction, the definition of the model architecture, parameter selection and configuration, model training and evaluation, as well as model selection.

The Indonesian corpus of public figure statements attribution achieved 90.06% agreement level between the annotator and experts and could serve as a gold standard corpus. Furthermore, the baseline model predicted most labels and achieved 82.026% F-score.

To the best of the authors’ knowledge, the resulting corpus is the first corpus for attribution of public figures’ statements in the Indonesian language, which makes it a significant step for research on attribution extraction in the language. The resulting corpus and the baseline model can be used as a benchmark for further research. Other researchers could follow the methods presented in this paper to develop a new corpus and baseline model for other languages.

This chapter studies communication during a longitudinal crisis by exploring the Irish airline Ryanair’s use of Twitter (now X) in early 2022 when the coronavirus disease 2019 (COVID-19) pandemic had already been affecting the airline industry for almost 2 years. It studies the airline’s approach to interacting with its passengers online and their reaction to its posts, at times, rather provocative posts. A corpus linguistic methodology is used to study tweets posted by and addressed to Ryanair between January and March 2022, a period that saw unprecedented peaks in COVID-19 infection numbers and the simultaneous lifting of travel restrictions. The analysis is based on the Ryanair 2022 Corpus which includes 27,089 tweets and more than half a million words. The findings of this case study show that Ryanair reappropriates instructing and adapting information on crisis-related topics as promotion and takes a political stance in its tweets to encourage consumer engagement. While the corporate tweets are successful in generating reactions online, the airline’s followers do not always perceive them in a positive manner. This case study makes an important contribution to crisis communication research as it shows how established communicative strategies, such as instructing and adapting information, may be reappropriated during a longitudinal crisis. At the same time, it demonstrates how these communicative strategies may – as a consequence – no longer be aligned with the core values of a legitimate organisation that is expected to act responsibly and ethically.

Our purpose is to reconnect memetics to information, a persistent and unclear association. Information can contribute across a span of memetic research. Its obscurity restricts conversations about “information flow,” the connections between “form” and “content,” as well as many other topics. As information is involved in cultural activity, its clarification could focus memetic theories and applications.

Our design captures theoretical nuance in memetics by considering a long standing conceptual issue in memetics: information. A systematic review of memetics is provided by making use of the term information across literature. We additionally provide a citation analysis and close readings of what “information” means within the corpus.

Our initial corpus is narrowed to 128 pivotal memetic publications. From these publications, we provide a citation analysis of memetic studies. Theoretical directions of memetics in the informational context are outlined and developed. We outline two main discussion spaces, survey theoretical interests and describe where and when information is important to memetic discussion. We also find that there are continuities in goals which connect Dawkins’s meme with internet meme studies.

To our knowledge, this is the broadest, most inclusive review of memetics conducted, making use of a unique approach to studying information-oriented discourse across a corpus. In doing so, we provide information researchers areas in which they might contribute theoretical clarity in diverse memetic approaches. Additionally, we borrow the notion of “conceptual troublemakers” to contribute a corpus collection strategy which might be valuable for future literature reviews with conceptual difficulties arising from interdisciplinary study.

The Annual Review of Comparative and International Education (ARCIE) represents a forum and an opportunity for scholars worldwide to discuss and examine trends and directions in comparative/international education, highlighting relevant developments in these fields, related to educational contexts, climates, and reforms in these contexts. Changes and reforms within these contexts and areas can have significant impacts on various education stakeholders, agents, and societies. Given the need to identify and prepare for these changes, the objective of this chapter is to discuss recent trends and directions in the field of Comparative and International Education (CIE). The method employed to identify these trends was a meta-analysis of the 23 chapters published in the 2020 edition of ARCIE. The 23 chapters composed the corpus of texts analyzed in this study, with the support of an online platform for corpora processing. Results of the analysis were contrasted with relevant literature in the field and suggest that (among the three main missions of universities) teaching and research received more attention than outreach/services, considering the corpus analyzed. In addition, teachers and students received more attention than administrative staff. Therefore, we conclude that more attention is necessary toward these aspects (outreach and administrative staff) in the pursuit of social justice and UN’s sustainable development goals (SDGs). Finally, the prevalence of topics related to language and sustainability suggests a need for more representativeness, in terms of regions and languages studied in the field of CIE.

The purpose of this paper is to propose a methodology for the enrichment and tailoring of a knowledge organization system (KOS), in order to support the information extraction (IE) task for the analysis of documents in the tourism domain. In particular, the KOS is used to develop a named entity recognition (NER) system.

A method to improve and customize an available thesaurus by leveraging documents related to the tourism in Italy is firstly presented. Then, the obtained thesaurus is used to create an annotated NER corpus, exploiting both distant supervision, deep learning and a light human supervision.

The study shows that a customized KOS can effectively support IE tasks when applied to documents belonging to the same domains and types used for its construction. Moreover, it is very useful to support and ease the annotation task using the proposed methodology, allowing to annotate a corpus with a fraction of the effort required for a manual annotation.

The paper explores an alternative use of a KOS, proposing an innovative NER corpus annotation methodology. Moreover, the KOS and the annotated NER data set will be made publicly available.

In times of crisis, such as the Covid-19 global pandemic, journalists who write about biomedical information must have the strategic aim to be clearly and easily understood by everyone. In this study, we assume that journalistic discourse could benefit from language redundancy to improve clarity and simplicity aimed at science popularization. The concept of language redundancy is theoretically discussed with the support of discourse analysis and information theory. The methodology adopted is a corpus-based qualitative approach. Two corpora samples with Brazilian Portuguese (BP) texts on Covid-19 were collected. One with texts from a monthly science digital magazine called Pesquisa FAPESP aimed at students and researchers for scientific information dissemination and the other with popular language texts from a news Portal G1 (Rede Globo) aimed at unspecified and/or non-specialized readers. The materials were filtered with two descriptors: “vaccine” and “test.” Preliminary analysis of examples from these materials revealed two categories of redundancy: paraphrastic and polysemic. Paraphrastic redundancy is based on concomitant language reformulation of words, sentences, text excerpts, or even larger units. Polysemic redundancy does not easily show material evidence, but is based on cognitively predictable semantic association in socio-cultural domains. Both kinds of redundancy contribute, each in their own way, to improving text readability for science popularization in Brazil.

The purpose of this study is to identify discourses of sustainability of community colleges and how they related to sustainability imaginaries.

This study used a combination of research strategies associated with corpus linguistics and critical discourse analysis. Data included 57 issues of Community College Journal, a professional magazine published by the American Association of Community Colleges, and 2,972 abstracts of dissertations about community colleges. Publication dates ranged from 2010 to 2020.

Community college discourse of sustainability coheres around six themes: careers and fields of study; curriculum and credentialing; campus ecological sustainability; administrative roles and processes; external organizations, partnerships and processes; and fiscal sustainability. There is little evidence of a sustainable living imaginary found.

The analysis is limited to a specific set of professional and academic texts about community colleges. Future researchers should explore discourses of sustainability in other contexts.

There has been no research associated with critical discourse analysis and corpus linguistics to explore community college discourses of sustainability, specifically in the field of community college leadership. The findings of this study situate the community college within contests over sustainability competencies in the practice of community college leadership development.

Research on disciplinary literacy in English has struggled with how to represent large-scale disciplinary communities and consider issues of justice and power. The purpose of this study is to offer insights into the disciplinary practice of a community of literary scholars.

Using statistical topic modeling augmented with complementary qualitative analysis and interpretive rhetorical analysis, the authors describe patterns in a corpus of 4,039 articles published in the year 2018 and drawn from 215 peer-reviewed literary journals, a corpus comprising 15.5 million words.

Analysis suggests that contemporary literary scholars collectively build knowledge that considers diverse matters of form, including literary and linguistic forms, literary works and other representational forms; criticality, including critical theories and critical concepts; and humanity, including humanistic themes, human institutions and people/places.

This manuscript offers detail about the nature of contemporary literary scholarship as evident through linguistic patterns in and across published works.