Highlights Understanding Sentiment Analysis Role and Opinion Mining In Covid-19 and Other Infectious Diseases. Literature’s Categorization for Sentiment Analysis and Infectious Disease. Academic Challenges and Motivations of Sentiment Analysis with Infectious Diseases. Different Applications for Mitigating Infectious Diseases by Sentiment Analysis.

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In this study, pre-service teaching refers to teaching English as a second language (TESL) to Malaysian students whose first language is not English. TESL prepares English-language learners to become future teachers of English as a second language. To date, no multi-criteria framework has been developed to evaluate and select the skills of pre-service teachers. This study presents a new framework to assess and rank the English skills of pre-service teachers on the basis of fuzzy Delphi and multi-criteria analysis. Three experiments were conducted. Firstly, criteria were identified from the literature review and the opinions of representative experts via the Delphi method. Secondly, 31 pre-service teachers were evaluated to determine the skills of pre-service teachers on the basis of Delphi criteria outcomes. English proficiency was tested through the English Language Testing Service and four language skill examinations. Each examination was evaluated by experts with vast experience in English teaching. Thirdly, pre-service teachers were ranked on the basis of a set of evaluated Delphi criteria outcomes through the technique for the order of preference by similarity to ideal solution (TOPSIS) method. Thereafter, the mean and standard deviation were utilized to ensure the identical systematic ranking of pre-service teachers. Findings are as follows. Twenty-five criteria from previous studies are representative as evaluated by the opinions of experts, which were gathered through interviews and a structured questionnaire. The validity of content was verified using a five-point Likert scale. With Delphi method outcomes, 14 criteria were selected and included in the final framework. The results of the proposed evaluation framework were tested on Malaysian pre-service teachers. TOPSIS is effective for solving the selection problems of pre-service teachers. In the final experiment, significant differences were recognized between the scores of groups, indicating identical ranking results.

This study proposes an evaluation and benchmarking decision matrix (DM) on the basis of multi-criteria decision making (MCDM) for young learners' English mobile applications (E-apps) in terms of listening, speaking, reading and writing (LSRW) skills. Benchmarking E-apps for young learners is challenging due to (a) multiple criteria, (b) criteria importance and (c) data variation. The DM was constructed on the basis of the intersection amongst evaluation criteria in terms of LSRW and E-apps for young learners. The criteria were adopted from a preschool education curriculum standard. The DM data included six E-apps as alternatives and 17 skills as criteria. Thereafter, the six E-apps were evaluated by distributing a checklist form amongst six English learning experts. These apps were subsequently benchmarked by utilising MCDM methods, namely, best-worst method (BWM) and technique for order of preference by similarity to ideal solution (TOPSIS). BWM was used for criterion weighting, whereas TOPSIS was employed to benchmark and rank the apps. TOPSIS was utilised in two contexts, namely, individual and group. In the group context, internal and external aggregations are applied. Mean was computed to ensure that the E-apps undergo a systematic ranking for objective validation. This study provides scenarios and a benchmarking checklist to evaluate and compare the proposed work with six relative studies. Results indicated that (1) BWM is suitable for criteria weighting. (2) TOPSIS is suitable for benchmarking and ranking E-apps. Moreover, the internal and external TOPSIS group decision making exhibited similar findings, with the best app being 'Montessori' and the worst app being 'FunWithFlupe.' (3) For objective validation, remarkable differences were observed amongst the group scores, which indicate that the internal and external ranking results are identical. (4) In the evaluation, the proposed DM revealed advantages over the six relative studies by 40.00%, 53.33%, 40.00%, 46.67%, 46.67% and 46.67%. INDEX TERMS Language learning app evaluation, language learning app assessment, language teaching/learning strategies. B. B. ZAIDAN received the B.Sc. degree in applied mathematics from Al-Nahrain University, Baghdad, Iraq, in 2004, and the M.Sc. degree in data communications and information security from the University of Malaya, Malaysia, in 2009. He is currently working as a Senior Lecturer with the Department of Computing, University Pendidikan Sultan Idris. He led or has been a member for many funded research projects, and has published more than 150 articles at various international conferences and journals. His research areas are artificial intelligence, decision theory, information security and network, and multicriteria evaluation and benchmarking. O. S. ALBAHRI received the B.Sc. degree in computer science from Al Turath University College, Baghdad, Iraq, in 2011, the M.Sc. degree in computer science and communication from Arts,

The activities of urban farming in Southeast are still limited and scattered. In order to give valuable insights into the urban agriculture of Southeast Asia and to support researchers, we need to know in details the available options and gaps in this research direction that will serve future researchers. Thus, in this study, a review is conducted to map the research landscape into a coherent taxonomy. The research procedure focuses on all these subject matters related to urban farming system activities, technology application and their use in the urban farms and smallholder farming activities in Southeast Asia. These studies selected from the three major digital databases, namely, the ScienceDirect, Web of Science, and Scopus. The study selection process consists of research into literature sources, followed by three iterations of screening and filtering, excluded duplicate articles, screening the titles and abstracts and reading of the full-text articles. The final included result is 88 articles, which will be adopted on in this study. Further, a review in details of the layout of the research landscape of literature is conducted into a cohesive classification with its descriptive analysis. We also identify the essential characteristics of this emerging field in the following aspects: benefits of using urban farming activities in Southeast Asia, challenges hindering utilization, and recommendations to improve the acceptance and use of urban farming applications in literature.