Balancing Authentic Content and “Hot Topic” Discussions in an ESP Classroom

Letter to the editor: A response to the comments of

Hot topic survey: Discussing the results of experts’ responses on controversial issues in FGM/C

Finding rising stars through hot topics detection

As a new form of social media, microblogging provides platform sharing, wherein users can share their feelings and ideas on certain topics. Bursty topics from microblogs are the results of the emerging issues that instantly attract more followers and more attention online, which provide a unique opportunity to gauge the relation between expressed public sentiment and hot topics. This paper presents a Social Sentiment Sensor (SSS) system on Sina Weibo to detect daily hot topics and analyze the sentiment distributions toward these topics. SSS includes two main techniques, namely, hot topic detection and topic-oriented sentiment analysis. Hot topic detection aims to detect the most popular topics online based on the following steps, topic detection, topic clustering, and topic popularity ranking. We extracted topics from the hashtags using a hashtag filtering model because they can cover almost all the topics. Then, we cluster the topics that describe the same issue, and rank the topic clusters via their popularity to exploit the final hot topics. Topic-oriented sentiment analysis aims to analyze public opinions toward the hot topics. After retrieving the topic-related messages, we recognize sentiment for each message using a state-of-the-art SVM (Support Vector Machine) sentiment classifier. Then, we summarize the sentiments for the hot topic to achieve topic sentiment distribution. Based on the above framework and algorithms, SSS produces a real-time visualization system to monitor social sentiments, which is offering the public a new and timely perspective on the dynamics of the social topics.

With information explosion occurring in past decades, the rapid growth of papers published results in the rapid change of hot topics, especially in the biomedical domain. It turns out very hard for researchers who are interested in biomedical domain to track hot topics over time, as well as to predict the trends of them in the near future. Based on the above demand, it is important to have a model which is able to follow and predict the trend of hot topics continuously. Deep learning has been proven to be an efficient method to extract information from texts and use the information to predict the future trends. Under the thriving background of Deep Learning, Graph Neural Network (GNN) is able to capture the information from graph structures. There are various applications using GNN models, such as traffic flow prediction, chemical structure discovering, etc. In this research project, a dynamic spatio-temporal graph neural network is presented to keep track of the selected hot keywords and topics in the biomedical domain and predict the possible frequencies in the near future. The input of the model is obtained by extracting the monthly frequency information of selected keywords and topics from paper abstracts in PubMed, the largest biomedical literature collection. After training with data over a decade, the model is able to predict trends of selected hot keywords and topics in next 5 months. Thus, the presented model can help follow the trend of hot topics in the biomedical domain.

In the finding of hot topics on microblog, the short text, less word, non-standard word use and other features of microblog have made the traditional identification method of hot topic powerless. To solve this problem, discovery method of microblog hot topic based on speed increase has been put forward. First, divide pretreated microblog according to windows with equal quality, count word frequency of each word in each window and express as two-tuple sequence of time; then calculate increase slope of each word in every two adjacent windows to find words with faster increasing speed; later calculate increasing speed of users and article number of microblogs related to the word to make sure whether the word is hot subject term; finally produce hot topic from the cluster of hot subject term. The feasibility of this method has been verified by experiment. Experimental results show that this method has improved identification efficiency and lowered omission ratio and fall-out ratio, which can effectively and promptly discover the hot topic of microblog.

In recent years, the recognition of hot topics and the analysis of their evolution path in the frontier of a field have received widespread attention from the academic community. It can not only reveal the development trend of a certain field but also discover the evolution law of topic content in different development stages of the field. However, there are still some problems in some current research methods, such as inaccurate recognition of hot topics and unclear evolution path, which seriously affect the comprehensiveness and accuracy of the analysis. To solve the above problems, the paper uses LDA (Latent Dirichlet Allocation) model to propose a hot topic recognition and evolution analysis method, which aims to reveal the evolution law of topic content level in different development stages of the field, such as inheritance, merging, division, and other topic evolution trends so as to provide decision support for domain knowledge innovation services. LDA adopts the Gibbs symmetric sampling method, which can make the adopted data converge, and under the given conditions, the data is symmetrical in the high-dimensional space structure, which makes the analysis result more accurate. Main research process: Firstly, LDA is used to extract global topics and stage topics. Second, the topics are filtered using a similarity calculation algorithm. Thirdly, novelty and support are used to recognize hot topics. Finally, three paths of inheritance evolution, merging evolution, and division evolution are formed for hot topics.

Latest Trends in Twitter from Arab Countries and the World

Hot Topics in Social Media and Reproductive Health.

Nowadays Micro blog has become a new tool of social intercourse. It effectively integrates various multimedia so that it is possible for users to release and update information freely. The characteristics of the micro blog bring great challenges to hot topic detecting. This paper proposed an approach of mining hot topics from micro blog by detecting the key terms emerging in large numbers and clustering them. To extract subject headings, a compound weight was structured by considering the term frequency and the growth rate to measure the likelihood of a word to be a hot topic keyword; To construct the hot topic, contextual relevance model was used to support incremental clustering, which is more suitable to the problem compared with semantic similarity. The experiments on real world data in micro blog show the effectiveness of the approach out of massive messages. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.4283 Full Text: PDF

Opportunism has been a hot topic in marketing channel for long time. It is not conducive to channel harmony and performance. The development of 5G technology provides a realistic basis for big data analysis. In the data age, scholars have to face another challenge that how to reveal the research status of opportunism from comprehensive analysis of objective data, efficiently identify potential hot topics in the field from massive papers, track its evolution path and provide visual analysis. Using 365 papers indexed by WOS core databases with the theme of “opportunism” and “opportunistic behavior” published from 1990 to 2019 as the research object, and uses visualization software such as Citespace to draw authors, institution cooperation maps, keyword co-occurrence maps, etc. The study analyzes the hot topics and development trends in the field of marketing channel opportunism, and also point out the future development direction for marketing channel opportunism research.

A scientific, systematic and standardized procurement policy of weapon equipment is an important guarantee for the modernization of weapon equipment. This paper proposed the hot topic analysis of weapon equipment procurement policy based on the LDA model, analyzed the keywords of weapon equipment procurement policy text, used the LDA model to analyze the text topic, obtained the topic and topic word probability distribution, and calculates the text topic popularity. On this basis, hot topics such as weapon equipment procurement project management, supervision and inspection, license management, confidentiality management, and fair competition were analyzed. The research conclusions provide reference for finding the hot topics of weapon equipment procurement policy and further improving weapon equipment procurement policy system.

Modern digital learning tools have become an integral part of maritime education and training (MET). Modernisation of MET with digital tools requires the development of new skills for maritime professionals (e.g., specialists in the management of shipboard technical systems and complexes). The purpose of the present study was to analyse the role of digital learning platforms, specifically, learning management systems (LMS), modular object-oriented dynamic learning environments (MOODLE), and online ESP courses. The study described the LMS MOODLE tools used in ESP online courses for future specialists in the management of shipboard technical systems and complexes to develop their professional competence. The study analysed the possibilities of the digital educational environment for the development of professional skills and competences of students of maritime educational institutions. The advantages of integrating e-learning into the training of ship’s mechanics were determined, specifically through flexibility in access to materials, adaptability of the educational process, and the possibility of forming individual learning paths. It was concluded that the LMS MOODLE significantly contributes to the development of professional competence of maritime specialists in e-learning. This ensures a comprehensive approach to MET and allows future specialists in the management of shipboard technical systems and complexes to take an active part in e-learning. As a result, students acquire theoretical knowledge with practical skills necessary for further work on board. The practical value of this study lies in its possible application of LMS MOODLE by teachers in teaching ESP in maritime higher education institutions

The article is devoted to theoretical and empirical research of the terminological field of the problem of forming professional and pedagogical competence of future teachers of higher education in the conditions of postgraduate studies at a technical university. The authors emphasize that the meaning of the concepts of “competence”, “professional competence”, “pedagogical competence” and “professional and pedagogical competence of future higher education teachers” is not determined by their terms (names), but is revealed through their definitions. The article presents the results of a study of theoretical works by scientists and the results of empirical research involving university postgraduate students to determine the substantive characteristics of the main definitions of “competence”, “professional competence”, “pedagogical competence”, “professional pedagogical competence” and “professional pedagogical competence of future higher education teachers”.The researchers propose a substantive model of professional pedagogical competence of future higher education teachers as an integral complex that combines a high level of theoretical and practical training for innovative pedagogical activity, qualities that are professionally significant for teachers, and ensures the successful performance of teaching functions, where the structural blocks are: motivational, cognitive, organizational-activity, and personal-reflective components.

The article clarifies the essence of the concepts of «сompetence» and «professional competence», determines the components of teacher’s professional competence: motivational (interest and motivation for future professional activity), cognitive (formed knowledge), operational (acquired skills and abilities) and personal-reflexive (ability to self-esteem, self-development and self- improvement). The author, on the basis of comparative analysis, shows the experience of forming the future teacher’s professional competence in leading countries such as: Germany, Denmark, Great Britain, France and others. The article outlines the peculiarities of the formation of the future teacher’s professional competence in determined countries. The interesting aspect in the formation of the future teacher’s professional competence in Germany is its information component, whose high level of evaluation is facilitated by the introduction of modern multimedia technologies in the educational process. The peculiarity of the Danish system of the future teachers’ professional competence formation is the availability of an additional vocational guidance level. So while forming the professional competence of a future teacher in the UK, considerable attention is paid to student’s research activities built on the humanization and democratization of the educational process in this country. The specificity of the future teachers’ professional competence formation in universities of France is that its most important component is the information and communication component. On the basis of the conducted analysis, the positive experience of the future teachers’ professional competence formation abroad is generalized; the recommendations on its introduction into the system of professional training in higher education institutions of Ukraine are worked out. The conclusion is made that the formation of the future teacher’s professional competence abroad will contribute to: the introduction of professional selection of applicants for teaching professions; exploiting the potential of non-formal education; an increase in the duration of teaching practice and the introduction of a mentoring system; inclusion of academic disciplines, that provide inclusive education, into the educational process; providing benefits to active teaching methods based on an interdisciplinary and problem-based approach; creating conditions for the exchange of experience of higher educational institutions with foreign educational institutions.