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The paper presents a two-part forensic linguistic analysis of an historic collection of abuse letters, sent to individuals in the public eye and individuals' private homes between 2007 and 2009. We employ the technique of structural topic modelling (stm) to identify distinctions in the core topics of the letters, gauging the value of this relatively under-used methodology in forensic linguistics. Four key topics were identified in the letters, 'Politics A' and 'B', 'Healthcare' and 'Immigration', and their coherence, correlation and shifts in topic were evaluated. Following the stm, a qualitative corpus linguistic analysis was undertaken, coding concordance lines according to topic, with the reliability between coders tested. This coding demonstrated that various connected statements within the same topic tend to gain or lose prevalence over time, and ultimately confirmed the consistency of content within the four topics identified through stm throughout the letter series. The discussion and conclusions to the paper reflect on the findings and also consider the utility of these methodologies for linguistics and forensic linguistics in particular. The study demonstrates real value in revisiting a forensic linguistic dataset such as this to test and develop methodologies for the field. [ABSTRACT FROM AUTHOR]

This paper explores the differences between the young adult version and the original version of The Da Vinci Code by Dan Brown through the lens of corpus linguistics. The study adds to the limited number of linguistic case studies analysing intralingual literary adaptations for children and highlights 'traditional' adaptation strategies such as Purification, Language adaptation, Abridgment and Localization. However, the analyses also highlighted other types of adjustments not covered in the above categories and previously observed in another study on intralingual adaptations for young audiences (Bianchi 2018). This suggests the need for creating a classification of adaptation strategies specific to intralingual adaptations targeting young readers. [ABSTRACT FROM AUTHOR]

Following Barthes’s seminal Système de la Mode, there have been relatively few studies focusing on fashion journalism from a linguistic perspective. This paper offers an in-depth analysis of hyphenated phrasal expressions (HPEs) of three or more constituents in the American edition of Vogue. The Vogue corpus covers a timeframe from 2003 to 2019 to provide diachronic insights. Corpus software was used to extract and analyse all hyphenated phrasal expressions. Results showed a general rise in usage over time, with most functioning as adjectives in line with the descriptive and evaluative purposes of fashion journalism. A wide range of structural patterns reflected richly detailed and striking mental images (i.e., *-and-*, *-meets-*), multiple roles (i.e., *-slash-*, NP-NP-NP), and novelty [(*)-of-the-moment, *-to-be]. Extensive clause-like HPEs offered a particularly interesting window on the writing talents of this discourse community. The study provides a useful benchmark for contrastive studies aiming to understand to what extent HPE usage in American Vogue may influence the writing style of journalists of other language backgrounds, with particular reference to Italian fashion journalism.

By joining manual analysis and corpus linguistics methods, this paper compares and contrasts the use of suspended quotations in Charles Dickens and Jane Austen. An analysis of two authors whose styles, aims and literary contexts are so different is functional to creating a list of functions typically performed by suspended quotation generally. The study shows that some roles of the suspended quotation reported for Dickens’ novels in previous literature are indeed specific to this writer and his idea of narrative, while others can be considered ‘author-independent’. Furthermore, the current analysis has revealed that suspended quotations lend themselves to a much wider range of functions than those reported and described in the literature thus far.

This article presents an empirical linguistic case study of seven Chinese trainee translators’ framing practice, focusing on how they reconstructed key lexical concepts in an English-to-Chinese news translation task. The research aim was to demonstrate how frames conceptualized in Frame Semantics (Fillmore, 1982) rationally serve as analytical and interpretive units of meaning, which contributes to providing a structural description and sufficient interpretation of translational discourse. The findings suggest that frames as context-motivated knowledge structures are crucial units of meaning to interrogate both source texts and translated texts in translation practice. This study has implications in translation training concerning how knowledge of frame application enters into training practice for source text interpretation and target text production.

Recently in the field of design, it is becoming more important to generate innovative ideas of "what to create" at early design stage than ideas of "how well to make". Ideation informatics to enhance idea generation by adding systematicity and exhaustiveness of information technology to human intuition should be a prospective approach to the problem. In this research, a ten sentence pattern model is proposed as a computable description of function and user experience (UX) at early design stage as a fundamental technology for ideation informatics by extending the English basic five sentence patterns. An XML format is designed to add semantic information to words, phrases, and sentences described in the ten sentence pattern model by using concept dictionary, i.e., concept identifiers of EDR electronic dictionary and synsets of Japanese WordNet, and software to calculate their semantic similarity is implemented in Python. Then, based on the knowledge of cognitive neuroscience that "human creation does not create something out of nothing, but the memory of the past is the basis of creation", a database of functions and UXs of existing products and services is prepared as an extension of human memory. Using the database, experiments to coming up ideas for solving problems related to the new coronavirus. From the obtained results, the effectiveness and possibility of the proposed method are confirmed.

Abstract Scientific research is increasingly characterised by the volume of documents and data that it produces, from experimental plans and raw data to reports and papers. Researchers frequently struggle to manage and curate these materials, both individually and collectively. Previous studies of Electronic Lab Notebooks (ELNs) in academia and industry have identified semantic web technologies as a means for organising scientific documents to improve current workflows and knowledge management practices. In this paper, we present a qualitative, user-centred study of researcher requirements and practices, based on a series of discipline-specific focus groups. We developed a prototype semantic ELN to serve as a discussion aid for these focus groups, and to help us explore the technical readiness of a range of semantic web technologies. While these technologies showed potential, existing tools for semantic annotation were not well-received by our focus groups, and need to be refined before they can be used to enhance current researcher practices. In addition, the seemingly simple notion of “tagging and searching” documents appears anything but; the researchers in our focus groups had extremely personal requirements for how they organise their work, so the successful incorporation of semantic web technologies into their practices must permit a significant degree of customisation and personalisation.

This article uses the semantic tagging tools provided by Wmatrix3 to investigate the discourse of corporate annual reports to shareholders from leading UKbased companies in four sectors: pharmaceuticals, food, mining and finance. Six potentially interesting areas of commonality are identified (change, inclusion, size: big, important, cause and effect, and time: begin). Concordance lines from these areas in each subcorpus are then analysed qualitatively to identify the presence of shared value-systems in the discourse of the reports. A contrastive analysis is then conducted which reveals differences between the four sectors in the keyness of areas such as safety, strength, newness and focus, as well as colleague and client orientation. These findings are discussed in the light of previous research on business communication. Finally, some advantages of using semantic tagging over standard corpus linguistic tools are discussed.

This study describes the quantitative aspects of metaphor in academic publications. In particular, we analyze the frequency of metaphor types and source domains in medical papers written by native and non-native speakers of English. The data have been collected from selected published articles on cancer and tissue engineering. The method combines a manual procedure with a semantic tagger and keyness statistics in Wmatrix software for metaphor identification. The results show that while the distribution of metaphor is relatively stable across tissue engineering and cancer articles written by native and non-native speakers, indirect metaphor is more often used than other types of metaphor. Moreover, the findings indicate that some metaphorical source domains are specifically used for a particular topic and that some are more frequently exploited by native speakers of English than by non-native speakers. This study has implications for English for Academic Purposes (EAP) pedagogy and the development of metaphorical awareness activities as it may set the ground for future corpus studies that analyze metaphor properties in academic registers. [ABSTRACT FROM AUTHOR]

This study explores the similarities and differences in content between the dialogic and the narrative parts in Jane Austen's Pride and Prejudice, and between the novel's dialogues and those in its 1940 and 2005 film adaptations. These four datasets were semantically tagged and compared to one another by using qualitative and quantitative methods. The findings show how, in covering conceptual areas largely complementary to those of the narrative, the dialogues in the novel perform various communicative functions. The investigation also points to how dialogues are adapted to the semiotic needs and goals of its film adaptations. [ABSTRACT FROM AUTHOR]

A semantic tagger aiming to detect relevant entities in Arabic medical documents and tagging them with their appropriate semantic class is presented. The system takes profit of a Multilingual Framework covering four languages (Arabic, English, French, and Spanish), in a way that resources available for each language can be used to improve the results of the others, this is specially important for less resourced languages as Arabic. The approach has been evaluated against Wikipedia pages of the four languages belonging to the medical domain. The core of the system is the definition of a base tagset consisting of the three most represented classes in SNOMED-CT taxonomy and the learning of a binary classifier for each semantic category in the tagset and each language, using a distant learning approach over three widely used knowledge resources, namely Wikipedia, Dbpedia, and SNOMED-CT.

This paper offers an overview of the highlights of the 2019 NFAIS Annual Conference, Creating Strategic Solutions in a Technology-Driven Marketplace that was held in Alexandria, VA from February 13 - February 15, 2019. The goal of the conference was to focus on how technological innovations, especially Artificial Intelligence and machine learning, along with changing market demands, are creating new opportunities within the information community. Speakers were invited to demonstrate that such innovations have the potential to provide researchers with new tools with which to advance their quest for scientific discovery and also have the potential to provide the much-needed insights to assist business leaders in making their strategic decisions with confidence. The diverse speakers made their point - technology is driving us forward. But the real message of the conference was all about the value of content and how that value can be increased by leveraging appropriate technology. Like changing a rough stone into in incomparable diamond, technology can transform traditional content into a faceted gem! [ABSTRACT FROM AUTHOR]

This paper uses Wmatrix to generate semantic tagging to compare corpora of media representations between the American Dream and the Chinese Dream. The USAS tagger is used to assign the semantic field tags to the America Dream Corpus (ADC) and the Chinese Dream Corpus (CDC). The motivation of this study is to replicate the studies using an automated and inclusive method based on semantic tagging (Potts, A. & P. Baker. 2012. Does semantic tagging identify cultural change in British and American English? International Journal of Corpus Linguistics 17(3). 295–324), and more importantly, to conduct a broad semantic categorization on both national dreams so as to uncover the cultural, social and historical similarities and/or differences. It is found that the cultural difference of the individualistic home and work association of the American Dream versus the collectivistic nation and world attributions of the Chinese Dream. The different historical stage and social-economic contexts are disclosed from the different temporal positions from time category, and the contrastive tags associated with negative representation of the American Dream and positive representation of the Chinese Dream. [ABSTRACT FROM AUTHOR]

Abstract Understanding customer behavior and driving customer satisfaction are necessary for any business to succeed in the competing market. Companies need to be aware of the prevailing customer perceptions to make more accurate and effective plans for product development and marketing. Customer feedback is available through multiple channels. Specifically, we are interested in the unstructured data available as text that would be available through social media, comments from a survey, voice recordings of customer interactions, and chat transcripts. Analyzing such data correctly is critical, as it reveals everything from buying trends to product flaws and provides a significant business advantage. It would further strengthen business opportunity to uncover customer interests, product improvements, and marketing insights. In this paper, we explore different technologies of Deep Learning and Natural Language Processing (NLP) that would help analyze better the contextual information to capture customer feedback. [ABSTRACT FROM AUTHOR]

Copyright of Iberica is the property of Asociacion Europea de Lenguas para Fines Especificos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Impolite behaviour is thought to be easier to investigate than polite or politic behaviour in diachronic contexts, because of attracting more evaluative comment. But an approach based on such metapragmatic commentary can miss a lot of facework strategies in contexts such as the UK parliament (modern and historical). In this paper, I draw on Historic Hansard datasets (1812–2003) to demonstrate how a (semi)automatic method involving contiguous searches of two-to-four features can better reveal the nuances of these MPs’ facework strategies than a focus on metapragmatic terms has afforded hitherto. The (semi)automatic method uses the recently created Historic Thesaurus Semantic Tagger (HTST) to search formeaning constellations(Archer and Malory 2017). Meaning constellations relating to facework are made up of sequences of semantic fields and/or parts-of-speech which, when organised in certain ways, achieve im/politeness, politic behaviour, strategic ambiguity, a combination of face enhancement and face threat, etc. This paper discusses a number of these meaning constellations, with a particular focus on those which engage in both face enhancement and face aggravation simultaneously (whilst nonetheless avoiding the label, “unparliamentary language”). [ABSTRACT FROM PUBLISHER]

A semantic tagger aiming to detect relevant entities in Arabic medical documents and tagging them with their appropriate semantic class is presented. The system takes profit of a Multilingual Framework covering four languages (Arabic, English, French, and Spanish), in a way that resources available for each language can be used to improve the results of the others, this is specially important for less resourced languages as Arabic. The approach has been evaluated against Wikipedia pages of the four languages belonging to the medical domain. The core of the system is the definition of a base tagset consisting of the three most represented classes in SNOMED-CT taxonomy and the learning of a binary classifier for each semantic category in the tagset and each language, using a distant learning approach over three widely used knowledge resources, namely Wikipedia , Dbpedia , and SNOMED-CT . [ABSTRACT FROM AUTHOR]

The paper describes our proposal for adopting 3D spatial representation, based on suitable indications and metrics, for the evaluation of experiences conducted in a Personal Learning Environment (PLE) and its social extension, the Personal Learning Network (PLN).The use of 3D space is a mean for integrating different perspectives (e.g., structured and non-structured learning) but also to foster the cooperation between users. Moreover, information coming from the use of 3D space can represent a precious feedback for better understanding ongoing learning activities, but it will be extremely useful for enhancing and improving the development of existing PLE-PLN support tool.

The paper describes the focus, scope and the rationale of PhytoKeys, a newly established, peer-reviewed, open-access journal in plant systematics. PhytoKeys is launched to respond to four main challenges of our time: (1) Appearance of electronic publications as amendments or even alternatives to paper publications; (2) Open Access (OA) as a new publishing model; (3) Linkage of electronic registers, indices and aggregators that summarize information on biological species through taxonomic names or their persistent identifiers (Globally Unique Identifiers or GUIDs; currently Life Science Identifiers or LSIDs); (4) Web 2.0 technologies that permit the semantic markup of, and semantic enhancements to, published biological texts. The journal will pursue cutting-edge technologies in publication and dissemination of biodiversity information while strictly following the requirements of the current International Code of Botanical Nomenclature (ICBN).

Social online communities and platforms play a significant role in the activities of software developers either as an integral part of the main activities or through complimentary knowledge and information sharing. As such techniques become more prevalent resulting in a wealth of shared information, the need to effectively organize and sift through the information becomes more important. Top-down approaches such as formal hierarchical directories have shown to lack scalability to be applicable to these circumstanes. Light-weight bottom-up techniques such as community tagging have shown promise for better organizing the available content. However, in more focused communities of practice, such as software engineering and development, community tagging can face some challenges such as tag explosion, locality of tags and interpretation differences, to name a few. To address these challenges, we propose a semantic tagging approach that benefits from the information available in Wikipedia to semantically ground the tagging process and provide a methodical approach for tagging social software engineering content. We have shown that our approach is able to provide high quality tags for social software engineering content that can be used not only for organizing such content but also for making meaningful and relevant content recommendation to the users both within a local community and also across multiple social online communities. We have empirically validated our approach through four main research questions. The results of our observations show that the proposed approach is quite effective in organizing social software engineering content and making relevant, helpful and novel content recommendations to software developers and users of social software engineering communities. [ABSTRACT FROM AUTHOR]

This study combines quantitative semi-automated corpus methods with manual qualitative analysis to investigate the use of Violence metaphors for cancer and end of life in a 1,500,000-word corpus of data from three stakeholder groups in healthcare: patients, family carers and healthcare professionals. Violence metaphors in general, especially military metaphors, are conventionally used to talk about illness, particularly cancer. However, they have also been criticized for their potentially negative implications. The use of innovative methodology enables us to undertake a more rigorous and systematic investigation of Violence metaphors than has previously been possible. Our findings show that patients, carers and professionals use a much wider set of Violence-related metaphors than noted in previous studies, and that metaphor use varies between interview and online forum genres and amongst different stakeholder groups. Our study has implications for the computer-assisted study of metaphor, metaphor theory and analysis more generally, and communication in healthcare settings. [ABSTRACT FROM AUTHOR]

Evidence for annotating Homeric poetry in Ancient Greece is as old as the 5th Century BCE, when the «Iliad» and «Odyssey» were performed by professional singers/composers who also performed annotations to the poetry in answer to questions from their audiences. As the long transition from a song culture into a literate society took place in Ancient Greece from the 8th to the 2nd and 1st centuries BCE, annotations were gradually incorporated into written poetic texts. By the 10th Century CE, the quantity of written annotations in the margins of medieval manuscripts has become huge. For the first two versions of «The Ancient Hero», a HarvardX MOOC, it was not possible to implement the set of annotation tools that we requested as a vehicle for close reading and assessment. Using a partial system, we were able to create a semblance of annotations in close reading self-assessment exercises. For the anticipated third version, we expect to have a complete set of textual and video annotation tools developed for HarvardX, including semantic tagging and full sharing of annotations. Such a system, which promises to make the educational experience more effective, will also inaugurate a digital phase in the long history of Homeric annotation. [ABSTRACT FROM AUTHOR]

Copyright of Procesamiento del Lenguaje Natural is the property of Sociedad Espanola para el Procesamiento del Lenguaje Natural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper explores the viability of automated semantic tagging as a tool of cultural analysis comparing American and British English using the Brown family of corpora. Pairs of corpora representing written language production from circa 1961, 1991 and 2006 were contrasted by comparing key semantic tags. This method was then evaluated in relation to three earlier studies which attempted to uncover cultural differences via assigning keywords to ad hoc categories. After outlining the differences found, we conclude that computerised semantic tagging can offer a wider reaching and more scientific comparison of language patterns. However, we suggest that this method is most appropriate as a starting point for a more in-depth cultural analysis, rather than as a final or certain indication of cultural change. [ABSTRACT FROM AUTHOR]

We propose a semantic collaborative filtering method to enhance recommendation quality derived from user-generated tags. Social tagging is employed as an approach in order to grasp and filter users' preferences for items. In addition, we explore several advantages of semantic tagging for ambiguity, synonymy, and semantic interoperability, which are notable challenges in information filtering. The proposed approach first determines semantically similar users using social tagging and subsequently discovers semantically relevant items for each user. Experimental results show that our method offers significant advantages both in terms of improving the recommendation quality and in dealing with ambiguity, synonymy, and interoperability issues. [ABSTRACT FROM AUTHOR]