The ecology of management concepts

How does the popularity of a concept depend on how it contrasts with and complements existing concepts? We argue that being similar to existing concepts, being located in a popular domain, and being combined with similar existing concepts are important for gaining attention early on but less important and even negative for sustaining popularity. To examine this question, we focus on the rise and fall of management concepts. We analyze data on the rise and fall of keywords in the Harvard Business Review between 1922 and 2010. Multiple tests confirm our hypotheses. The implication is that lessons learned from studies of popular concepts can be misleading as guides for how to make novel concepts popular

An author keyword analysis for mapping Sport Sciences

[EN] Scientific production has increased exponentially in recent years. It is necessary to find methodological strategies for understanding holistic or macro views of the major research trends developed in specific fields. Data mining is a useful technique to address this task. In particular, our study presents a global analysis of the information generated during last decades in the Sport Sciences Category (SSC) included in the Web of Science database. An analysis of the frequency of appearance and the dynamics of the Author Keywords (AKs) has been made for the last thirty years. Likewise, the network of co-occurrences established between words and the survival time of new words that have appeared since 2001 has also been analysed. One of the main findings of our research is the identification of six large thematic clusters in the SSC. There are also two major terms that coexist ('REHABILITATION' and 'EXERCISE') and show a high frequency of appearance, as well as a key behaviour in the calculated co-occurrence networks. Another significant finding is that AKs are mostly accepted in the SSC since there has been high percentage of new terms during 2001-2006, although they have a low survival period. These results support a multidisciplinary perspective within the Sport Sciences field of study and a colonization of the field by rehabilitation according to our AK analysis.González-Moreno, L.; García-Massó, X.; Pardo-Ibáñez, A.; Peset Mancebo, MF.; Devis Devis, J. (2018). An author keyword analysis for mapping Sport Sciences. PLoS ONE. 13(8). https://doi.org/10.1371/journal.pone.0201435S13

Research on Keywords Variations in Linguistics Based on TF-IDF and N-gram

The rapid development of natural language processing (NLP) holds great promise for bridging the divide among languages. One of its main innovative applications is to use broad data to explore the historical trend of a subject. However, since Saussure pioneered modern linguistics, there is relatively inadequate research work done in the linguistic research on the field\u27s variations to comprehensively reveal the linguistic trends. To trace the changes in linguistic research hotspots, we use a dataset of more than 30,000 linguistics-related literature with their titles from the Web of Science and apply NLP techniques to the data consisting of their keywords and publication years. It is found that the co-occurrence relationship between keywords, NGRAM, and their relationship with years can effectively present changes in linguistic research themes. This research is supposed to provide further insights and new methods that can be applied in the field of linguistics and related disciplines

Syntactic and Semantic Patterns of Domain-specific Multiword Units in Marine Accident Investigation Reports

The present study is a systematic corpus-based investigation of the domain-specific multiword units (henceforth MWUs) in marine accident investigation reports (henceforth MAIR), with a view to characterizing their most prominent syntactic, semantic and functional features. To achieve these principal objectives, the target MWUs were first identified by applying a new approach, which incorporates the notion of ‘meaning’ into statistical-based measures. This method ensures the domain-specific MWU extraction to the largest extent and provides valid data for the subsequent analysis. Through proposing a three-dimensional analytical framework, this study has obtained the following findings: First, the domain-specific MWUs are largely composed of two-word sequences, while the occurrences of 4- and 5-word MWUs are relatively rare. Among all the target MWUs, only 1.10% of the expressions occur very commonly within the genre (˚1,000 times). By contrast, the majority of the expressions (70.97%) occur with the frequency less than 100 times. The skewed distribution indicates that MAIR genre tends to employ a wide variety of domain-specific MWUs rather than repetition of a small number of common expressions. Second, in terms of the syntactic features of the domain-specific MWUs, NP structure is the most commonly employed grammatical type. The abundant use of this structure implies that the domain-specific meaning of MAIR genre is largely carried in the nominal group. Apart from NP structure, there is also a marked prevalence of VP structures among the domain-specific MWUs in MAIR genre and these MWUs present structural variation. Of all the VP-based patterns, the ‘verb phrase with active verb’ pattern stands out since it incorporates a large number of action verbs, which are used to describe the actions done by people. The wide use of these phrases implies that MAIR genre tends to highlight the people’s roles during the accidents, with particular attention to the information about what or who caused or performed the activity. Similarly, PP structures were also frequently adopted by the domain-specific MWUs, especially the pattern beginning with preposition of. This pattern was mostly used to specify possessions. It thus can be inferred that the information that provided in MAIR genre tends to be concrete and specific. Third, by conducting a functional analysis of the target MWUs, it was found that the primary function of the domain-specific MWUs is to express referential meanings and contribute to the thematic development. Furthermore, due to their multifunctional nature, some referential MWUs also perform the function of stance and discourse organizing. When expressing stance, most MWUs express impersonal epistemic stance, with the purpose of minimizing the imposition of the reporters’ opinions. Other word sequences appear to be deontic in nature, as they are mainly realized by the MWUs incorporating with require or modal verbs. The primary function of these MWUs is to set out the obligations and issue suggestions for the agents according to certain norms and regulations. When functioning as discourse organizer, the domain-specific MWUs usually adopt the pattern of ‘that-clause controlled by main verbs in active voice’ to introduce the topics. Unlikely, when using for elaborating the topics, they tend to clarify the logical relationships, especially the causative-resultative relation, rather than providing additional information in MAIR genre. Fourth, the distinctive semantic features of the domain-specific MWUs can be best reflected when these MWUs perform the functions of activity identification and specification. For instance, most domain-specific MWUs used for describing activities are of general nature, but they convey specialized meaning in MAIR genre. Similarly, when domain-specific MWUs are used to provide tangible or intangible frames for specifying certain attributes, the use of these MWUs in MAIR genre is significantly deviant from their use in general English register. In all, by gaining insights into the salient features of the domain-specific MWUs in MAIR genre, the present study may make contributions and implications in the following aspects: the construction of extraction method for domain-specific MWUs, the compilation of maritime-specific MWU list, the teaching and learning of maritime English, especially the maritime-specific MWUs, and providing reference for writing MAIR to the experts who are from non-native English speaking countries.Abstract i List of Tables v List of Figures vii Chapter 1 Introduction 1 1.1. Background of this study 1 1.2. Objectives of this study 3 1.3. Significance of this study 4 1.4. Terminological issues 5 1.5. Organization of this dissertation 6 Chapter 2 Theoretical background 8 2.1. Understanding the notions of phraseology 8 2.2.1. An overview of influential notions of phraseology 9 2.1.2. Parameters of defining MWUs 13 2.1.3. Operational definition of MWUs 17 2.1.4. An overview of influential taxonomy of phraseology 19 2.2. Theoretical discussion of MWUs 23 2.2.1. Theoretical framework of this study 23 2.2.2. Nature of multiword units 25 2.2.3. Previous studies of phraseology 29 Chapter 3 Analytical framework and research design 37 3.1. Analytical framework 37 3.1.1 Analytical framework for syntactic features of domain-specific MWUs 38 3.1.2. Analytical framework for semantic features of domain-specific MWUs 40 3.1.3. Analytical framework for functional features of domain-specificMWUs 42 3.2. Research questions 43 3.3. Corpora used in this study 44 3.3.1. Corpus of Marine Accident Investigation Reports (COMAIR) 44 3.3.2. British National Corpus Baby (BNC Baby) 47 3.4. Tools and procedures for data analysis 48 3.4.1. Tools for data processing 48 3.4.2. Procedures for data analysis 49 3.4.3. Inter-rater reliability 50 3.5. Summary 51 Chapter 4 Identification of domain-specific MWUs in the COMAIR 52 4.1. Current approaches to MWU extraction 52 4.2. My proposed approach to domain-specific MWU extraction 53 4.3. The detailed process of domain-specific MWU extraction 55 4.3.1. Step 1: N-gram retrieval 55 4.3.2. Step 2: Keyword-gram extraction 56 4.3.3. Step 3: Measuring the association strength of keyword-grams 58 4.3.4. Step 4: Filtering out process 66 4.3.5. Step 5: Domain-specific MWU identification 70 Chapter 5 Frequency distributions and syntactic features of domain-specific MWUs 72 5.1. Frequency distributions of domain-specific MWUs 72 5.1.1. Frequency distributions of domain-specific MWUs in various lengths 72 5.1.2. Overall frequency distribution across different frequency bands 74 5.2. Syntactic features of domain-specific MWUs 76 Chapter 6 Functional and semantic features of domain-specific MWUs 80 6.1. Distributions across primary discourse functions 80 6.2. Multiple functioning 82 6.3. Stance MWUs 84 6.3.1. Notion of stance MWUs 84 6.3.2. Stance MWUs in COMAIR 84 6.4. Discourse organizing MWUs 90 6.4.1. Notion of discourse organizing MWUs 90 6.4.2. Discourse organizing MWUs in COMAIR 90 6.5. Referential MWUs 96 6.5.1. Notion of referential MWUs 97 6.5.2. Referential MWUs in COMAIR 97 6.6. Summary 112 Chapter 7 Conclusions and implications 113 7.1. Summary of the major findings 113 7.2. Implications of this study 116 7.3. Limitations of this study 117 References 118 Appendix 132Docto

Textpresso: An Ontology-Based Information Retrieval and Extraction System for Biological Literature

We have developed Textpresso, a new text-mining system for scientific literature whose capabilities go far beyond those of a simple keyword search engine. Textpresso's two major elements are a collection of the full text of scientific articles split into individual sentences, and the implementation of categories of terms for which a database of articles and individual sentences can be searched. The categories are classes of biological concepts (e.g., gene, allele, cell or cell group, phenotype, etc.) and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., biological process, etc.). Together they form a catalog of types of objects and concepts called an ontology. After this ontology is populated with terms, the whole corpus of articles and abstracts is marked up to identify terms of these categories. The current ontology comprises 33 categories of terms. A search engine enables the user to search for one or a combination of these tags and/or keywords within a sentence or document, and as the ontology allows word meaning to be queried, it is possible to formulate semantic queries. Full text access increases recall of biological data types from 45% to 95%. Extraction of particular biological facts, such as gene-gene interactions, can be accelerated significantly by ontologies, with Textpresso automatically performing nearly as well as expert curators to identify sentences; in searches for two uniquely named genes and an interaction term, the ontology confers a 3-fold increase of search efficiency. Textpresso currently focuses on Caenorhabditis elegans literature, with 3,800 full text articles and 16,000 abstracts. The lexicon of the ontology contains 14,500 entries, each of which includes all versions of a specific word or phrase, and it includes all categories of the Gene Ontology database. Textpresso is a useful curation tool, as well as search engine for researchers, and can readily be extended to other organism-specific corpora of text. Textpresso can be accessed at http://www.textpresso.org or via WormBase at http://www.wormbase.org

Lexikos at eighteen: an analysis

At eighteen, Lexikos became a major player in the field of linguistics, by being awarded an Impact Factor. This article presents a double analysis of the foundation that led to this success. On the one hand a thorough statistical study is undertaken with regard to all contributors and their contributions to Lexikos. To this end a metadata database was designed, with the aim to answer the question: 'Who publishes what type of material from where and when?' On the other hand a content analysis is carried out which focuses on the actual topics (i.e. 'keywords') in Lexikos. To this end an all-inclusive text corpus containing all the Lexikos material was built, with the aim to answer the question: 'What are the major trends in Lexikos?

Tracing the evolution of digitalisation research in business and management fields: Bibliometric analysis, topic modelling and deep learning trend forecasting

Research on digitalisation trends and digital topics has become one of the most prolific streams of research within the fields of business and management during the course of the past few years. The purpose of this study is to provide a general picture of the intellectual structure and the conceptual space of this research realm. To this purpose, 6067 publications related to digital topics, indexed in the business and management categories of Web of Science (WoS), and dated from 1990 to 2020 are explored based on the approaches of bibliometric analysis, topic modelling and trend forecasting. The results of the bibliometric analysis comprise insights into the publication and citation structure, the most productive authors, the most productive universities, the most productive countries, the most productive journals, the most cited studies and the most prevalent themes and sub-themes on digitalisation in business and management. In addition, the outcomes of the topic modelling give new knowledge on the latent topical structure along with the rising, falling and fluctuating trends of this literature. In addition, the results of the trend forecasting enable readers to have a glimpse of how the underlying trends of the literature will probably change within the next years until 2025. These results provide guidance and orientation for both academics and practitioners who are initiating or currently developing their efforts in this discipline.info:eu-repo/semantics/acceptedVersio