Which way records management research?

2020 ◽  
Vol 39 (1) ◽  
pp. 29-45
Author(s):  
Omwoyo Bosire Onyancha
Keyword(s):  
Information Management ◽  
Health Sector ◽  
Records Management ◽  
Medical Computing ◽  
Research Areas ◽  
The Social ◽  
Computer Based ◽  
Scopus Database ◽  
Broad Subject

This paper evaluates the keywords and subject areas in records management (RM) publications, as indexed in the Scopus database, with a view to mapping RM research from 1971 to 2018 so as to determine the direction of research in the field. A total of 4 762 documents were obtained from the Scopus database using the term records management and searching within the title, abstract and keywords fields. The data was analysed using VOSviewer software. The findings reveal that interest in RM research has grown as the volume of publications has continued to increase. Whereas there was no dominant area of research in the 1980s, as far as RM research is concerned, the main focus in the 2010s was the management of electronic health records, thereby signalling a shift in RM research from being just an information management exercise to being used for the management of records in the medical and health sector. Other popular research areas in the 2010s were health care, electronic medical record/s, information management, medical computing, information systems, and electronic document exchange. A classification of the RM publications according to Scopus’s broad subject fields revealed that RM research is mainly conducted in computer science, engineering, medicine, and the social sciences. The study predicts a slow growth in the number of RM publications in the next ten years (2019-2028), greater focus on RM in the health sector, and continued dominance of computer-based systems and electronic records as topics of RM research.

scholarly journals Social origins of risk semiotics

2020 ◽  
pp. 29-38
Author(s):  
Vyacheslav K. Shcherbin
Keyword(s):  
Modern Society ◽  
Negative Results ◽  
Research Areas ◽  
Social Risks ◽  
The Social ◽  
The World ◽  
Main Components ◽  
Opposite Attitude

The article examines the structure of the inter-relationship between society and its inherent risks, the main components of which are society’s accumulated experience in predicting and mitigating risks, the continuous complication of modern society and the new social risks it generates. The reasons for the formation of these components, the positive and negative results of their use by society are analyzed. The reactions of managers and scientists to existing social risks are described. The main difference between these reactions is the diametrically opposite attitude of managers and scientists to the phenomenon of reductionism in solving complex social problems. The article defines the role of interdisciplinary research areas (synergetics, systemology, the combined social analysis, science of science, etc.) in solving problems related to social risks. The proposed by A. G. Teslinov’s classification of existing worlds (the material world, the world of ideas, the social world and the world of signs) correlates with traditional disciplinary classifications. The place of a new scientific direction (risk semiotics) in the system of existing risk sciences, as well as among other artificial semiotics is established. The conclusion about the need for interrelated development of social semiotics and risk semiotics is substantiated.

scholarly journals Sentiment classification of user's reviews on drugs based on global vectors for word representation and bidirectional long short-term memory recurrent neural network

2021 ◽  
Vol 23 (1) ◽  
pp. 345
Author(s):  
Hadab Khalid Obayed ◽  
Firas Sabah Al-Turaihi ◽  
Khaldoon H. Alhussayni
Keyword(s):  
Neural Network ◽  
Short Term Memory ◽  
Human Life ◽  
Health Sector ◽  
Ground Truth ◽  
Second Stage ◽  
The Social ◽  
Word Representation ◽  
Two Phases

<p>The process of product development in the health sector, especially pharmaceuticals, goes through a series of precise procedures due to its directrelevance to human life. The opinion of patients or users of a particular drugcan be relied upon in this development process, as the patients convey their experience with the drugs through their opinion. The social media field provides many datasets related to drugs through knowing the user's ratingand opinion on a drug after using it. In this work, a dataset is used that includes the user’s rating and review on the drug, for the purpose of classifying the user’s opinions (reviews) whether they are positive ornegative. The proposed method in this article includes two phases. The first phase is to use the Global vectors for word representation model for converting texts into the vector of embedded words. As for the second stage, the deep neural network (Bidirectional longshort-termmemory) is employedin the classification of reviews. The user's rating is used as a ground truth inevaluating the classification results. The proposed method present sencouraging results, as the classification results are evaluated through threecriteria, namely Precision, Recall and F-score, whose obtained values equal(0.9543, 0.9597and0.9558), respectively. The classification results of theproposed method are compared to a number of classifiers, and it was noticed that the results of the proposed method exceed those of the alternative classifiers.</p>

Social-Psychological Models in Labor Motivation Analysis

2004 ◽  
pp. 90-101 ◽  
Author(s):  
A. Surkov
Keyword(s):  
Economic Analysis ◽  
Psychological Approach ◽  
Social Psychological ◽  
Economic Man ◽  
The Social ◽  
Psychological Models ◽  
Social Psychological Approach

Benefits of using social-psychological approach in the analysis of labor motivations are considered in the article. Classification of employees as objects of economic analysis is offered: "the economic man", "the man of the organization", "the social man" and "the asocial man". Related models give the opportunity to predict behavior of the firm in different situations, such as shocks of various nature.

Cases of social innovations implemented in the public health sector

2020 ◽  
Vol 16 (9) ◽  
pp. 1600-1621
Author(s):  
E.V. Molchanova
Keyword(s):  
Public Health ◽  
Systems Approach ◽  
Health Sector ◽  
Demographic Challenges ◽  
Disability Adjusted Life ◽  
The Social ◽  
Social Innovations ◽  
Demographic Processes ◽  
Disease Study ◽  
Disability Adjusted Life Year

Subject. The article discusses medical and demographic processes in Russia and Finland. Objectives. I evaluate cases of social innovations implemented for the preservation and strengthening of public health in Finland under the auspices of The Global Burden of Disease Study. Methods. Methodologically, the study relies upon the ideology of the GDB Project, which rests on the DALY (the Disability Adjusted Life Year). Results. I analyzed the morbidity and mortality rates, DALY in Russia and Finland, determined what mainly triggers the risk (environmental, behavioral, metabolic) fueling some public health degradation. The article provides the insight into the efficiency of some social innovations implemented in Finland and suggests what should be done to outline medical and demographic programs in Russia. Conclusions and Relevance. The medical and demographic situation in Russia requires new tools to find innovative solutions for the social policy and, inter alia, the use of the GBD technique, which proved to be effective. Referring to evidence from Finland, demographic challenges in Russian can be handled through a systems approach, i.e. socio-economic actions, improvement of the healthcare and social security, wellness propaganda.

Philosophcal review of h. white̕s tropological theory in the context of the new philosophy of history

2020 ◽  
Vol 3 (152) ◽  
pp. 92-99
Author(s):  
S. M. Geiko ◽  
◽  
O. D. Lauta
Keyword(s):  
Modern Science ◽  
Historical Knowledge ◽  
Text Organization ◽  
The Social ◽  
History Of ◽  
Actual Material ◽  
The Common ◽  
Historical Nature ◽  
Selection Of

The article provides a philosophical analysis of the tropological theory of the history of H. White. The researcher claims that history is a specific kind of literature, and the historical works is the connection of a certain set of research and narrative operations. The first type of operation answers the question of why the event happened this way and not the other. The second operation is the social description, the narrative of events, the intellectual act of organizing the actual material. According to H. White, this is where the set of ideas and preferences of the researcher begin to work, mainly of a literary and historical nature. Explanations are the main mechanism that becomes the common thread of the narrative. The are implemented through using plot (romantic, satire, comic and tragic) and trope systems – the main stylistic forms of text organization (metaphor, metonymy, synecdoche, irony). The latter decisively influenced for result of the work historians. Historiographical style follows the tropological model, the selection of which is determined by the historian’s individual language practice. When the choice is made, the imagination is ready to create a narrative. Therefore, the historical understanding, according to H. White, can only be tropological. H. White proposes a new methodology for historical research. During the discourse, adequate speech is created to analyze historical phenomena, which the philosopher defines as prefigurative tropological movement. This is how history is revealed through the art of anthropology. Thus, H. White’s tropical history theory offers modern science f meaningful and metatheoretically significant. The structure of concepts on which the classification of historiographical styles can be based and the predictive function of philosophy regarding historical knowledge can be refined.

A Study of the Cloud Computing Adoption Issues and Challenges

2020 ◽  
Vol 13 (3) ◽  
pp. 313-318 ◽  
Author(s):  
Dhanapal Angamuthu ◽  
Nithyanandam Pandian
Keyword(s):  
Cloud Computing ◽  
High Performance ◽  
Cloud Service ◽  
Ease Of Use ◽  
Modern Trend ◽  
Security Issues ◽  
Research Areas ◽  
Data Location ◽  
Broad Classification

<P>Background: The cloud computing is the modern trend in high-performance computing. Cloud computing becomes very popular due to its characteristic of available anywhere, elasticity, ease of use, cost-effectiveness, etc. Though the cloud grants various benefits, it has associated issues and challenges to prevent the organizations to adopt the cloud. </P><P> Objective: The objective of this paper is to cover the several perspectives of Cloud Computing. This includes a basic definition of cloud, classification of the cloud based on Delivery and Deployment Model. The broad classification of the issues and challenges faced by the organization to adopt the cloud computing model are explored. Examples for the broad classification are Data Related issues in the cloud, Service availability related issues in cloud, etc. The detailed sub-classifications of each of the issues and challenges discussed. The example sub-classification of the Data Related issues in cloud shall be further classified into Data Security issues, Data Integrity issue, Data location issue, Multitenancy issues, etc. This paper also covers the typical problem of vendor lock-in issue. This article analyzed and described the various possible unique insider attacks in the cloud environment. </P><P> Results: The guideline and recommendations for the different issues and challenges are discussed. The most importantly the potential research areas in the cloud domain are explored. </P><P> Conclusion: This paper discussed the details on cloud computing, classifications and the several issues and challenges faced in adopting the cloud. The guideline and recommendations for issues and challenges are covered. The potential research areas in the cloud domain are captured. This helps the researchers, academicians and industries to focus and address the current challenges faced by the customers.</P>

scholarly journals Automated Classification of Fake News Spreaders to Break the Misinformation Chain

Information ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 248
Author(s):  
Simone Leonardi ◽  
Giuseppe Rizzo ◽  
Maurizio Morisio
Keyword(s):  
Social Media ◽  
Network Architecture ◽  
Diffusion Mechanism ◽  
Automated Classification ◽  
Fake News ◽  
Neural Network Architecture ◽  
User Classification ◽  
The Social ◽  
Network Topologies

In social media, users are spreading misinformation easily and without fact checking. In principle, they do not have a malicious intent, but their sharing leads to a socially dangerous diffusion mechanism. The motivations behind this behavior have been linked to a wide variety of social and personal outcomes, but these users are not easily identified. The existing solutions show how the analysis of linguistic signals in social media posts combined with the exploration of network topologies are effective in this field. These applications have some limitations such as focusing solely on the fake news shared and not understanding the typology of the user spreading them. In this paper, we propose a computational approach to extract features from the social media posts of these users to recognize who is a fake news spreader for a given topic. Thanks to the CoAID dataset, we start the analysis with 300 K users engaged on an online micro-blogging platform; then, we enriched the dataset by extending it to a collection of more than 1 M share actions and their associated posts on the platform. The proposed approach processes a batch of Twitter posts authored by users of the CoAID dataset and turns them into a high-dimensional matrix of features, which are then exploited by a deep neural network architecture based on transformers to perform user classification. We prove the effectiveness of our work by comparing the precision, recall, and f1 score of our model with different configurations and with a baseline classifier. We obtained an f1 score of 0.8076, obtaining an improvement from the state-of-the-art by 4%.

Polarity Classification of Arabic Sentiments

2016 ◽  
Vol 11 (3) ◽  
pp. 32-49 ◽  
Author(s):  
Mohammed N. Al-Kabi ◽  
Heider A. Wahsheh ◽  
Izzat M. Alsmadi
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Operating Characteristic ◽  
Opinion Mining ◽  
Online Social Network ◽  
The Social ◽  
Polarity Classification ◽  
Arabic Sentiment Analysis ◽  
Modern Standard

Sentiment Analysis/Opinion Mining is associated with social media and usually aims to automatically identify the polarities of different points of views of the users of the social media about different aspects of life. The polarity of a sentiment reflects the point view of its author about a certain issue. This study aims to present a new method to identify the polarity of Arabic reviews and comments whether they are written in Modern Standard Arabic (MSA), or one of the Arabic Dialects, and/or include Emoticons. The proposed method is called Detection of Arabic Sentiment Analysis Polarity (DASAP). A modest dataset of Arabic comments, posts, and reviews is collected from Online social network websites (i.e. Facebook, Blogs, YouTube, and Twitter). This dataset is used to evaluate the effectiveness of the proposed method (DASAP). Receiver Operating Characteristic (ROC) prediction quality measurements are used to evaluate the effectiveness of DASAP based on the collected dataset.

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