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The purpose of this paper is to generate awareness of and interest in the techniques used in computer-based corpus linguistics, focusing on their methodological implications for research in library and information science (LIS).

This methodology paper provides an overview of computer-based corpus linguistics, describes the main techniques used in this field, assesses its strengths and weaknesses, and presents examples to illustrate the value of corpus linguistics to LIS research.

Overall, corpus-based techniques are simple, yet powerful, and they support both quantitative and qualitative analyses. While corpus methods alone may not be sufficient for research in LIS, they can be used to complement and to help triangulate the findings of other methods. Corpus linguistics techniques also have the potential to be exploited more fully in LIS research that involves a higher degree of automation (e.g. recommender systems, knowledge discovery systems, and text mining).

Numerous LIS researchers have drawn attention to the lack of diversity in research methods used in this field, and suggested that approaches permitting mixed methods research are needed. If LIS researchers learn about the potential of computer-based corpus methods, they can diversify their approaches.

Over the past quarter century, corpus linguistics has established itself as one of the main methods used in the field of linguistics, but its potential has not yet been realized by researchers in LIS. Corpus linguistics tools are readily available and relatively straightforward to apply. By raising awareness about corpus linguistics, the author hopes to make these techniques available as additional tools in the LIS researcher’s methodological toolbox, thus broadening the range of methods applied in this field.

The purpose of this paper is to demonstrate the utility of corpus linguistics and digitised newspaper archives in management and organisational history.

The paper draws its inferences from Google NGram Viewer and five digitised historical newspaper databases – The Times of India, The Financial Times, The Economist, The New York Times and The Wall Street Journal – that contain prints from the nineteenth century.

The paper argues that corpus linguistics or the quantitative and qualitative analysis of large-scale real-world machine-readable text can be an important method of historical research in management studies, especially for discourse analysis. It shows how this method can be fruitfully used for research in management and organisational history, using term count and cluster analysis. In particular, historical databases of digitised newspapers serve as important corpora to understand the evolution of specific words and concepts. Corpus linguistics using newspaper archives can potentially serve as a method for periodisation and triangulation in corporate, analytically structured and serial histories and also foster cross-country comparisons in the evolution of management concepts.

The paper also shows the limitation of the research method and potential robustness checks while using the method.

Findings of this paper can stimulate new ways of conducting research in management history.

The paper for the first time introduces corpus linguistics as a research method in management history.

In this chapter, we explore uses of corpus linguistics within higher education research. Corpus linguistic approaches enable examination of large bodies of language data based on computing power. These bodies of data, or corpora, facilitate investigation of the meaning of words in context. The semiautomated nature of such investigation helps researchers to identify and interpret language patterns that might otherwise be inaccessible through manual analysis. We illustrate potential uses of corpus linguistic approaches through four short case studies by higher education researchers, spanning educational contexts, disciplines and genres. These case studies are underpinned by discussion of the development of corpus linguistics as a field of investigation, including existing open corpora and corpus analysis tools. We give a flavour of how corpus linguistic techniques, in isolation or as part of a wider research approach, can be particularly helpful to higher education researchers who wish to investigate language data and its context.

Computer corpus linguistics (CCL) is a scientific innovation that has facilitated the creation and analysis of large corpora in a systematic way by means of computer technology since the 1950s. This article provides an account of the CCL pioneers in general but particularly of those in Germany, the Netherlands, Sweden, and Switzerland. It is found that Germany and Sweden, due to more advantageous financing and weaker communities of generativists, had a faster adoption of CCL than the other two countries. A particular late adopter among the four was Switzerland, which did not take up CCL until foreign professors had been recruited.

The purpose of this paper is to examine the newspaper representations of the aggressive behaviour of social actors in political protests and explore the benefits of integrating corpus linguistics and cognitive approaches to a critical discourse analysis in analysing press reports.

This paper uses methods from corpus linguistics and theoretical constructs from cognitive linguistics to examine patterns of representation around Occupy Central, a recent political protest in Hong Kong, in two corpora of English-language newspaper articles published in China Daily and the South China Morning Post (SCMP).

An analysis of the ten most frequent collocates of the word police showed that the China Daily corpus articles typically index the presentation of police as vulnerable yet professional in their handling of violent protesters, whereas in SCMP, police officers are often presented as aggressors. The analysis subsequently considered three discursive strategies, namely structural configuration, framing and identification that are mediated through conceptualisations that representations in text evoke.

In the proposed integrated approach, quantitative investigations of corpus examples could be focussed and contextualised in such a way that particular linguistic instantiations in discourse which are proved statistically salient can be further analysed in relation to conceptual phenomena which serve specific ideological purposes.

Hopefully, the study could serve as the first ever attempt to adopt an integrative analytical framework in the study of aggression and conflict in news discourse.

The purpose of this study is to apply a corpus-assisted analysis of keywords and their collocations in the US presidential discourse from Clinton to Trump to discover the meanings of these words and the collocates they have. Keywords are salient words in a corpus whose frequency is unusually high (positive keywords) or low (negative keywords) in comparison with a reference corpus. Collocation is the co-occurrence of words.

To achieve this purpose, the investigation of keywords and collocations is generated by AntConc, a corpus processing software.

This analysis leads to shed light on the similarities and/or differences amongst the past four American presidents concerning their key topics. Keyword analysis through keyness makes it evident that Clinton and Obama, being Democrats, demonstrate a clear tendency to improve Americans’ life inside their social sphere. Obama surpasses Clinton as regard foreign affairs. Clinton and Obama’s infrequent subjects have to do with terrorism and immigration. This complies with their condensed focus on social and economic improvements. Bush, a republican, concentrates only on external issues. This is proven by his keywords signifying war against terrorism. Bush’s negative use of words marking cooperative actions conforms to his positive use of words indicating external war. Trump’s positive keywords are about exaggerated descriptions without a defined target. He also shows an unusual frequency in referring to his name and position. His words used with negative keyness refer to reforming programs and external issues. Collocations around each top content keyword clarify the word and harmonize with the presidential orientation negotiated by the keywords.

Limitations have to do with the issue of the accurate representation of the samples.

This research is original in its methodology of applying corpus linguistics tools in the analysis of presidential discourses.

Departing from the assumption that discourse is both socially constituted and constitutive, and that social reality is co-constructed by the institutions of mass communication, this chapter takes under scrutiny media representation of the recent refugee crisis in Europe. The objective behind it is to maximise the validity of the Media Proximization Approach (MPA), drawing on the insights from Critical Discourse Studies, cognitive linguistics and corpus linguistics, in explicating how the media can potentially impact on the salience of issues and thus on public perception of problems and threats along with measures to be taken to deal with them. Examining the data from Poland, a European Union member state from Central Europe, criticised for its anti-refugee stance and refusal to accept the assigned quotas of migrants, and, importantly, the country ‘experiencing’ migrant crisis without refugees, we look at the role of word co-occurrence patterns in the discursive representation of refugees and immigrants in Rzeczpospolita daily and Niezależna.pl, the Polish right-wing press. The analysis, of both quantitative and qualitative nature, focuses on lexical associations of two nouns, uchodźca ‘refugee’ and imigrant ‘immigrant’, and their role as epistemic, axiological and emotional proximization triggers in the process of mediated construction of crisis and European security.

Recent changes in the funding and governance of academic research in many OECD countries have altered established authority relationships governing research priorities and judgements. These shifts in the influence of a variety of groups and organisations over scientific choices and careers can be expected to affect the development of different kinds of intellectual innovations by changing the level of protected space they provide researchers and the flexibility of dominant intellectual standards governing the allocation of resources and evaluation of research outcomes. Variations in these features of public science systems influence scientists’ willingness to pursue unusual and risky projects over many years and help to explain cross-national differences in the rate and mode of development of four innovations in the physical, biological and human sciences.

This paper aims to develop a system, which would enable efficient management and exploitation of documentation in electronic form, related to mining projects, with information retrieval and information extraction (IE) features, using various language resources and natural language processing.

The system is designed to integrate textual, lexical, semantic and terminological resources, enabling advanced document search and extraction of information. These resources are integrated with a set of Web services and applications, for different user profiles and use-cases.

The use of the system is illustrated by examples demonstrating keyword search supported by Web query expansion services, search based on regular expressions, corpus search based on local grammars, followed by extraction of information based on this search and finally, search with lexical masks using domain and semantic markers.

The presented system is the first software solution for implementation of human language technology in management of documentation from the mining engineering domain, but it is also applicable to other engineering and non-engineering domains. The system is independent of the type of alphabet (Cyrillic and Latin), which makes it applicable to other languages of the Balkan region related to Serbian, and its support for morphological dictionaries can be applied in most morphologically complex languages, such as Slavic languages. Significant search improvements and the efficiency of IE are based on semantic networks and terminology dictionaries, with the support of local grammars.

This paper seeks to draw on the linguistic model of narrative recursion developed by Ochs and Capps and on data collected and analysed in previous research projects conducted by Shenton in order to synthesise a new framework that represents the information behaviour of children and young people.

The model of narrative recursion provides the basis of the framework proposed. However, additional, LIS‐specific details have been introduced to ensure that the reworked version represents the phenomenon of information behaviour pertaining to the young as appropriately as possible.

The individual elements within the Ochs and Capps model correspond closely to three phases typically associated with information behaviour – the emergence of an information need, information‐seeking action, and information use.

No claim is made that the model delineates all instances of information behaviour. It ignores cases where information is acquired incidentally, where no clear goal is involved in the activity and where no enhancement of the knowledge state results, even though information has been accessed.

The model is sufficiently simple to be employed in information literacy sessions with secondary school pupils. It could also be extended to provide an instructional tool and is useful in highlighting various points in youngsters' information‐related action where intermediaries may help.

Although the adoption of ideas and frameworks from other disciplines with the aim of increasing understanding of LIS phenomena is a growing trend, the paper forms one of the first attempts to apply to information behaviour an existing model associated with linguistics.