List Of Keywords Research Articles

The reference corpus matters

Abstract This study investigates the effect that reference corpora of different registers have on the content of keyword lists. The study focusses on two target corpora and the keyword lists generated for each when using three distinct reference corpora. The two target corpora consist of published research by faculty at two PhD-granting programs in applied linguistics in North America. The reference corpora comprise published research in applied linguistics, newspaper and magazine articles, and fiction texts, respectively. The findings suggest that while common keywords representing each target corpus emerge regardless of the reference corpus used in the analysis, there are also substantial differences. Primarily, using a reference corpus of the same sub-register as the target corpus better highlights content unique to each target corpus while using a reference corpus of a different register better uncovers words that reflect the register that the target corpora represent. Implications for conducting keyword analysis are discussed.

“The junkie abuses, the psychonaut learns”: a qualitative analysis of an online drug forum community

Purpose Drug-related web forums have been argued to be an effective way to investigate the latest generation of drug users. The purpose of this paper is to explore discussions about drugs and new psychoactive substances (NPS) on an Italian psychonauts’ online community in order to gain a better understanding of the psychonauts’ profiles by scrutinising their main motives for consumption, which is mainly addressed to psychedelic drugs. Design/methodology/approach To collect data, a keywords list was used in the forum search engine. The first five most recent conversations (threads) for each of ten most frequently mentioned substances were selected. In addition, ten posts written by new forum members to introduce themselves were added to the data set, bringing the total number of threads to 60. The data were coded using Atlas.ti 7 applying a template model analysis (King, 1998). Findings The forum members present themselves as well-educated, informed drug users, and connoisseurs of the pharmacological properties of chemical compounds: accordingly, they claim to be aware of drug effects and possible risks. The analysis of the motives for using psychedelic drugs substantially confirms previous studies, indicating that the main reasons include spiritual needs, self-exploration and self-treatment. The shift from a recreational use towards more “committed” aims such as self-development is seen as a step forward in a drug user’s career. A generalised interest in harm reduction suggests that the psychonauts’ attitude may be a protective factor against adverse consequences of drug use. The most problematic users represented in the data are those who use drugs for self-treatment, since their discourse focusses on suffering rather than on pleasure. Originality/value Most efforts to analyse and monitor drug-related forums have focussed on “leading edge” English-language international websites. No studies have dealt with Italian forums. Furthermore the study address a misleading use of the term e-psychonauts recently introduced by some scholars whose’s studies were focussed on NPS.

Cerebrospinal Fluid Correlates of Neuropsychiatric Symptoms in Patients with Alzheimer's Disease/Mild Cognitive Impairment: A Systematic Review.

Neuropsychiatric symptoms (NPS) are common, accelerate the conversion to dementia, and are associated with increased caregiver burden in Alzheimer's disease (AD) and mild cognitive impairment (MCI). The aim of this study is to identify potential associations between the core cerebrospinal fluid (CSF) biomarkers (amyloid/tau) and NPS in AD/MCI. For this systematic review, four databases, PubMed (1946-2018), Cochrane (2005-2018), EMBASE (1947-2018), and PsycINFO (1806-2018) were searched for relevant observational studies using an extensive list of keywords. English studies were selected for critical appraisal based on our inclusion/exclusion criteria. Inclusion criteria were defined as 1) at least one AD CSF biomarker has been measured; 2) at least one NPS has been assessed; and 3) analysis has been done to examine the association between core AD CSF biomarker and NPS (main outcome). Animal, postmortem, and review studies were excluded. In total, 21 studies qualified for the systematic review. The overall picture regarding the association between NPS and AD CSF biomarkers is conflicting. However, agitation/aggression was significantly and consistently related to core AD CSF biomarkers. Moreover, depression was the only NPS to occasionally be associated with lower core AD CSF pathology. Our study has revealed agitation/aggression as the most consistent NPS related to core AD CSF biomarkers. Future studies are required to focus on other neglected NPS domains such as disinhibition. Moreover, why depression was the only NPS inversely associated with core AD CSF pathology remains to be elucidated. Our study also revealed a great degree of heterogeneity, hence calling for a more standardized "objective" approach for the evaluation of NPS.

Corpus-Assisted Critical Discourse Analysis of Saudi Vision 2030

Saudi Vision 2030 is a plan to steer the country towards prosperity through diversified economy, better government services and conducive environment for all to thrive. The study of wordlists, keyword lists, collocation analyses, identification of core issues on the basis of lexical fields and their reflection in 2018 English newspapers in Saudi Arabia qualifies the corpus-assisted present study for Critical Discourse Analysis. The corpora of 4.3 million words and 2.0 million words from the English Newspapers in Saudi Arabia published in 2013 and 2018 respectively have been compiled for the study. Saudi Vision 2030 has been treated as a specialized corpus to get frequency lists and collocations. The analyses identified the extraordinary use of second person plural pronoun ‘we’ ‘our’, modal auxiliary ‘will’ etc.; such explorations paved the way for entry into more qualitative investigations. On the basis keyword lists, key issues have been identified in all three corpora. Some key issues including the largest lexical field in newspaper corpora viz. ‘Security’ has been found missing in the said vision. The present study aims to bring forth a fresh insight into Saudi Vision 2030 and to advocate the corpus-assisted methodology for critical discourse analysis.

Research trends in Korean medicine based on temporal and network analysis

BackgroundMuch research on Korean medicine has been recently published in Korea. The aim of this study was to determine the research trends in Korean medicine by performing a comprehensive analysis of articles that have been published in Korea using temporal and network analysis methods.MethodsA total of 29,876 articles from 1963 to 2018 were prepared from OASIS (Oriental Medicine Advanced Searching Integrated System), the largest portal for Korean medicine. After the keywords and years were extracted from the metadata of the articles, an annual frequency matrix was obtained for the keywords. By using the matrix, the temporal trends of the keywords were analyzed by comparing the changes in similarity between the lists of keywords by year. Moreover, to analyze the relationship among research topics, a clustered network was constructed in which a node was a keyword and an edge was a similarity between two keywords.ResultsThe temporal trend of the keywords was classified into six chronological phases. The appearance frequency of most keywords tended to increase gradually, but only the keywords “mibyeong,” “systems biology” and “korean medicine hospital” appeared in the most recent phase. The network of keywords was clustered and visualized into thirteen groups with the Gephi software. The main keywords in each group were related to effects such as “anti-inflammation” and “antioxidant,” to diseases such as “allergic rhinitis” and “diabetes” and to therapies such as “herbal acupuncture” and “herbal formula.”ConclusionsThe analysis of the trends determined in this study provides a systematic understanding as well as future research directions in Korean medicine to researchers. In the future, an overall analysis of the research trends in Korean medicine will be done by analyzing articles published in Korea and other countries.

Sentiment Analysis of Brand Personality Positioning Through Text Mining

This article uses text mining and a Chinese word segmentation program developed by the Chinese Knowledge and Information Processing Group in Taiwan's Academia Sinica to analyze Facebook posts from 14 e-commerce companies. In addition, a list of keywords representing brand personalities is analyzed to reveal key factors affecting which social media posts attract consumers' attention. This research uses statistical analysis with a nonmanual questionnaire that is efficient and based on computer science to provide a reference for businesses operating Facebook fan pages and internet marketing.

Small-aperture strategies for the correction of presbyopia.

The recent scientific literature provides evidence of long-term results with small-aperture corneal inlays, as well as new evidence from a multicenter postmarket study of small-aperture intraocular lenses (IOLs) and early reports of the use of topical agents for presbyopia correction through pupil constriction. The field of small-aperture optics is growing and changing rapidly. This article reviews what is known to date about various small-aperture optics platforms, including a posterior chamber IOL, add on device, corneal inlay, contact lenses, and pupil-constricting drops. Additionally, the impact of small-aperture technologies on light perception and visual performance, as well as the relative merits of monocular versus binocular small apertures are discussed. Small-aperture optics are a dynamic, physiologic solution to the problem of presbyopia. They are effective throughout the range of accommodation loss and in pseudophakia. Small-aperture optics offer an opportunity to improve vision in presbyopes with and without cataracts. In some forms, they may also be able to reduce the impact of aberrations or improve vision in eyes with corneal irregularities, scars, or iris damage.

Патриотизм, лоббизм, демонстративность… Фреймирование импортозамещения в российских печатных СМИ

Цитирование: Казун А.Д., Дорофеева О.Е. (2019) Патриотизм, лоббизм, демонстративность… Фреймирование импортозамещения в российских печатных СМИ // Мир России. Т. 28. № 3. С. 132–154. DOI: 10.17323/1811-038X-2019-28-3-132-154
 В статье анализируется дискуссия в российской прессе по вопросу импортозамещения в период с августа 2014 по декабрь 2016 года. Отбор новостных сообщений производился с использованием базы печатных изданий «Интегрум». По итогам анализа 269 статей, опубликованных в «Российской газете», «Новой газете», «Комсомольской правде», «Коммерсанте», были выделены восемь основных фреймов, посредством которых конструировалась дискуссия: антизападный, патриотичный, «последствия», ностальгический, сентиментальный, «индивидуальные интересы», эгоистичный и демонстративный. Наиболее популярными оказались патриотичный фрейм и фрейм «последствия», при этом спектр используемых фреймов различался в зависимости от издания. На основании проведенного качественного анализа публикаций в СМИ был сформулирован список ключевых слов, которые использовались для определения места импортозамещения в сетевой повестке дня. Исследование совместных упоминаний этих слов в российской прессе позволил выделить три крупных кластера в публичной дискуссии по экономическим вопросам: экономико-политический, патриотично-эгоистичный и кластер протекционизма. По итогам исследования сделан вывод, что в дискуссии об импортозамещении сочетаются как экономические, так и политические аргументы, а СМИ, в свою очередь, часто прибегают к идеологическим конструктам для обоснования того или иного отношения к импортозамещению.

Corpus-Assisted Critical Discourse Analysis of Saudi Vision 2030

Saudi Vision 2030 is a plan to steer the country towards prosperity through diversified economy, better government services and conducive environment for all to thrive. The study of wordlists, keyword lists, collocation analyses, identification of core issues on the basis of lexical fields and their reflection in 2018 English newspapers in Saudi Arabia qualifies the corpus-assisted present study for Critical Discourse Analysis. The corpora of 4.3 million words and 2.0 million words from the English Newspapers in Saudi Arabia published in 2013 and 2018 respectively have been compiled for the study. Saudi Vision 2030 has been treated as a specialized corpus to get frequency lists and collocations. The analyses identified the extraordinary use of second person plural pronoun ‘we’ ‘our’, modal auxiliary ‘will’ etc.; such explorations paved the way for entry into more qualitative investigations. On the basis keyword lists, key issues have been identified in all three corpora. Some key issues including the largest lexical field in newspaper corpora viz. ‘Security’ has been found missing in the said vision. The present study aims to bring forth a fresh insight into Saudi Vision 2030 and to advocate the corpus-assisted methodology for critical discourse analysis.

Applying crowdsourcing techniques in urban planning: A bibliometric analysis of research and practice prospects

Urban planning requires more public involvement and larger group participation to achieve scientific and democratic decision making. Crowdsourcing is a novel approach to gathering information, encouraging innovation and facilitating group decision-making. Unfortunately, although previous research has explored the utility of crowdsourcing applied to urban planning theoretically, there are still rare real practices or empirical studies using practical data. This study aims to identify the prospects for implementing crowdsourcing in urban planning through a bibliometric analysis on current research. First, database and keyword lists based on peer-reviewed journal articles were developed. Second, semantic analysis is applied to quantify co-occurrence frequencies of various terms in the articles based on the keyword lists, and in turn a semantic network is built. Then, cluster analysis was conducted to identify major and correlated research topics, and bursting key terms were analyzed and explained chronologically. Lastly, future research and practical trends were discussed. The major contribution of this study is identifying crowdsourcing as a novel urban planning method, which can strengthen government capacities by involving public participation, i.e., turning governments into task givers. Regarding future patterns, the application of crowdsourcing in urban planning is expected to expand to transportation, public health and environmental issues. It is also indicated that the use of crowdsourcing requires governments to adjust urban planning mechanisms.

TRAFFIC EVENT DETECTION USING TWITTER DATA BASED ON ASSOCIATION RULES

Abstract. Social media platforms allow millions of people worldwide to instantly share their thoughts online. Many people use social media to share traffic related experiences and events with online posts. A large amount of traffic related data can be obtained from these online posts – especially geosocial media data, where posts are tagged with geolocation information such as coordinates or place names. By extracting traffic events from geosocial media data, drivers can adapt to changing traffic conditions, while traffic management departments can propose timely and effective plans to improve traffic conditions. Most of the existing studies query traffic-related information based on a list of single keywords, which result in large amounts of noisy data – negative data containing one or more traffic-related keywords, but do not actually represent real-world traffic events. This paper aims to filter noisy data by mining association rules among words in positive data containing messages representing traffic events. Messages are more likely to be true traffic events if they follow the co-occurrence pattern of words mined from positive samples. A case study was conducted in Toronto, Canada using Twitter data. The tweets queried by the association rules were classified into non-traffic event, traffic accidents, roadwork, severe weather conditions, and special events with an 85% accuracy based on supervised machine learning methods. Compared with hourly average travel speed data, 81% of detected events were identified as real-world traffic events. This research sheds light on traffic condition monitoring in smart transportation platforms, which plays an important role for smart cities.

List of keywords for polymer science (IUPAC Technical Report)

Abstract This paper provides a list of the most important terms from all areas of polymer science including polymer chemistry, polymer physics, polymer technology and polymer properties. These have been assembled into a representative list of terms that serves as an IUPAC recommended list of keywords for polymer science.

A semi-automated tool for identifying agricultural roadway crashes in crash narratives

Objective: Crash reports contain precoded structured data fields and a crash narrative that can be a source of rich information not included in the structured data. The narrative can be useful for identifying vulnerable roadway users, such as agricultural workers. However, using the narratives often requires manual reviews that are time consuming and costly. The objective of this research was to develop a simple and relatively inexpensive, semi-automated tool for screening crash narratives and expediting the process of identifying crashes with specific characteristics, such as agricultural crashes.Methods: Crash records for Louisiana from 2010 to 2015 were obtained from the Louisiana Department of Transportation (LaDOTD). Records with narratives were extracted and stratified by vehicle type. The majority of analyses focused on a vehicle type of farm equipment (Type T). Two keyword lists, an inclusion list and an exclusion list, were created based on the published literature, subject-matter experts, and findings from a pilot project. Next, a semi-automated tool was developed in Microsoft Excel to identify agricultural crashes. Lastly, the tool’s performance was assessed using a gold standard set of agricultural narratives identified through manual review.Results: The tool reduced the search space (e.g., number of narratives that need manual review) for narratives requiring manual review from 6.7 to 59.4% depending on the research question. Sensitivity was high, with 96.1% of agricultural crash narratives being correctly classified. Of the gold standard agricultural narratives, 58.3% included an equipment keyword and 72.8% included a farm equipment brand.Conclusion: This article provides information on how crash narratives can supplement structured crash data. It also provides an easy-to-implement method to facilitate incorporating narratives into safety research along with keyword lists for identifying agricultural crashes.

Assisted reproductive technology and the risk of preeclampsia: an updated systematic review and meta-analysis

BackgroundThe objective of this systematic review and meta-analyses was to assess the risk of preeclampsia among women who conceived with assisted reproductive technology (ART).MethodsWe searched the ISI Web of Knowledge, Medline/PubMed, Scopus, and Embase (from inception to May 2017) for English language articles using a list of key words. In addition, reference lists from identified studies and relevant review articles were also searched. Data extraction was performed by two authors, and the study quality was assessed using the Newcastle–Ottawa Scale. Random-effects model meta-analysis was applied to pool the relative risks (RR) across studies.ResultsA total of 48 studies (5 case-control studies and 43 cohort studies) were included in this meta-analysis. The Cochran Q test and I2 statistics revealed substantial heterogeneity (Q = 26,313.92, d.f. = 47, p < 0.001 and I2 = 99.8%). Meta-analysis showed a significant increase in preeclampsia in women who conceived by ART compared with those who conceived spontaneously (RR = 1.71, 95% CI = 1.11–2.62, p = 0.015).ConclusionsThe findings of this systematic review indicate that the use of ART treatment is associated with a 1.71-fold increase in preeclampsia.

Diversity Awareness and Documentation Practices Among Oncology Advanced Practice Providers.

Advanced practice providers (APPs) care for widely diverse populations. The Institute of Medicine (IOM) states that bias, prejudice, and stereotyping by a health-care provider may contribute to disparities, which are associated with worse outcomes. The IOM called for efforts to increase awareness among health-care providers. The objective of this study is to assess the cultural self-awareness of oncology APPs who practice in a community-based outpatient cancer center and investigate the extent to which APPs include cultural care into patient assessments and document this data. Oncology APPs completed a questionnaire evaluating cultural self-awareness. A prospective, quality improvement chart review was performed to analyze the extent to which cultural themes were addressed during oncology clinic visits. A list of cultural keywords was used as a guide. About 10% of the 2015 cancer population at the institution was examined, which included a stratified sample of the top six disease groups. Responses were analyzed. All APPs demonstrated average or above-average cultural awareness. Documentation of cultural assessment was low. Of the 28 cultural keyword items, an average of 4.88 items were addressed during each visit. Multiple cultural items, including literacy, language, insurance status, and belief about the disease were addressed less than 5% of the time.

코퍼스를 활용한 호텔영어의 키워드 연구

This study extracted and examined the key words of Hotel English Corpus. The Hotel English Corpus used in this study consists of 719,578 words and five genres such as hotel homepages, academic journals, newspapers, books and spoken English textbooks. WordSmith tools 6.0 was used to extract the positive and negative key words in 5 genres and compare the lexical characteristics. The keywords were classified into two main categories; the positive keywords and the negative keywords. The positive keywords generated from the Hotel English Corpus show the characteristics of Hotel English and should be given priority treatment. The study confirms that the keyword lists which are different according to the each genre are essential and helpful and also play a significant role in hotel English education and research. This study suggests that there are different keywords which are frequently used in each genre and the hotel English learners including hotel employees, hotel guests and researchers should study these words to understand and use better hotel English.

Mobile Applications in Neurosurgery: A Systematic Review, Quality Audit, and Survey of Canadian Neurosurgery Residents

In the past decade, smartphone applications (Apps) have experienced remarkable development across all fields of medicine, including neurosurgery. However, owing to a lack of regulatory oversight and peer review, a clear need exists for a comprehensive review and audit of the existing available Apps. In the present study, we systematically reviewed the existing mobile Apps in neurosurgery, evaluated their clinical use by neurosurgery residents in Canada, and performed a quality audit of the most popular Apps. Indexed Apps were identified from either the Google Play Store or the iOS App Store using a comprehensive list of keywords related to neurosurgery. A subsequent cross-sectional survey of 76 Canadian neurosurgery residents was conducted, including a section on smartphone App use. We next evaluated the most popular Apps among the residents using the Healthcare Smartphone App Evaluation Tool and performed a quality audit of their content using established medical references. The survey identified 118 mobile Apps related to neurosurgery. The 3 most used Apps used by the current cohort of Canadian neurosurgery residents were Neurosurgery Survival Guide, Neuromind, and the Journal of Neurosurgery App. Each of these 3 Apps received an excellent score on the Healthcare Smartphone App Evaluation Tool. A quality audit of 30 pages of the Neurosurgery Survival Guide and 40 clinical scores of the Neuromind App, performed by 10 neurosurgery residents, failed to reveal inaccurate or false statements. The present study has highlighted the current landscape of neurosurgery mobile Apps and their use among neurosurgery residents.

Keywords in Written Academic Legal Texts: A Corpus-Derived List

This study presents the Written Academic Legal Vocabulary (WALV), a discipline-specific genre-focused list of keywords in a corpus of academic legal texts. To generate this list, a purpose-customized corpus of full-length academic texts is created and analyzed with the help of corpus-based analytical tools. Items on the list are chosen based on criteria such as frequency of occurrence, range and keyness. The keywords recur more frequently in a specialized corpus than in a general reference corpus, a finding that attests to the pedagogical utility of these expressions as possible focus of explicit instruction. The final list consists of 298 headwords and 219 families (lemmas). Findings also indicate that the list includes words belonging to different grammatical types, the most common of which are nouns. The list also incorporates a large number of abbreviations, shortenings and acronyms.

Incorporating text dispersion into keyword analyses

Keyword analysis has become an indispensable tool for discourse analysts, being applied to identify the words that are especially characteristic of the texts in a target discourse domain. But, surprisingly, the statistical computation of keyness makes no reference to those texts. Rather, once a corpus has been constructed, it is treated as a homogeneous whole for the computation of keyness. As a result, the keywords in such lists are relatively frequent in the corpus, but they are often not widely dispersed across the texts of that corpus and are thus not truly representative of the target discourse domain. The purpose of this study is to propose a new method for keyword analysis – text dispersion keyness – that is based on text dispersion, rather than corpus frequency. We compare the effectiveness of this measure to four other methods for computing keyness, carrying out a series of case studies to identify the keywords that are typical of online travel blogs. A variety of quantitative and qualitative analyses are carried out to compare these methods based on their content-generalisability and content-distinctiveness, demonstrating that text dispersion keyness is a superior measure for generating keyword lists.

Assimilation of oil news into prices

Do investors quickly and rationally react to the content of oil-related news articles revealing supply and demand information? Our paper creates a novel keyword list of 130 oil-related words and modifiers that enable investors/researchers to measure the information content of oil stories. We find significant short-term overreaction to the text of Dow Jones oil-related news articles. Phrases like output cut, production cut, shortage, and demand up in lagged news articles are associated with lower oil prices the following trading day. The evidence is consistent with the notion that oil traders overreact to the content of widely-read news articles.