scholarly journals Multilingual Sentiment Analysis: A Systematic Literature Review

2021 ◽  
Vol 29 (1) ◽  
Author(s):  
Nur Atiqah Sia Abdullah ◽  
Nur Ida Aniza Rusli
Keyword(s):  
Literature Review ◽  
Sentiment Analysis ◽  
Systematic Literature Review ◽  
Online Community ◽  
Language Analysis ◽  
Evaluation Models ◽  
Topic Clustering ◽  
The Common ◽  
N Gram ◽  
Processing Techniques

With the explosive growth of social media, the online community can freely express their opinions without disclosing their identities. People with hidden agendas can easily post fake opinions to discredit target products, services, politicians, or organizations. With these big data, monitoring opinions and distilling their sentiments remain a formidable task because of the proliferation of diverse sites with a large volume of opinions that are portrayed in multilingual. Therefore, this paper aims to provide a systematic literature review on multilingual sentiment analysis, which summarises the common languages supported in multilingual sentiment analysis, pre-processing techniques, existing sentiment analysis approaches, and evaluation models that have been used for multilingual sentiment analysis. By following the systematic literature review, the findings revealed, most of the models supported two languages, and English is seen as the most used language in sentiment analysis studies. None of the reviewed literature has catered the combination of languages for English, Chinese, Malay, and Hindi language on multilingual sentiment analysis. The common pre-processing techniques for the multilingual domain are tokenization, normalization, capitalization, N-gram, and machine translation. Meanwhile, the sentiment analysis classification techniques for multilingual sentiment are hybrid sentiment analysis, which includes localized language analysis, unsupervised topic clustering, and then followed by multilingual sentiment analysis. In terms of evaluation, most of the studies used precision, recall, and accuracy as the benchmark for the results.

Sentiment Analysis in Education Domain: A Systematic Literature Review

2018 ◽  
pp. 285-297 ◽  
Author(s):  
Karen Mite-Baidal ◽  
Carlota Delgado-Vera ◽  
Evelyn Solís-Avilés ◽  
Ana Herrera Espinoza ◽  
Jenny Ortiz-Zambrano ◽  
...  
Keyword(s):  
Literature Review ◽  
Sentiment Analysis ◽  
Systematic Literature Review

scholarly journals Usability Evaluation Model for Mobile Visually Impaired Applications

2020 ◽  
Vol 14 (05) ◽  
pp. 95
Author(s):  
Azham Hussain ◽  
Ahlam Mohamed Omar
Keyword(s):  
Literature Review ◽  
Visual Impairment ◽  
Systematic Literature Review ◽  
Mobile Applications ◽  
Mobile Application ◽  
Visually Impaired ◽  
Evaluation Model ◽  
Usability Evaluation ◽  
Evaluation Models ◽  
Usability Evaluation Methods

The usability of the mobile applications is the most important factor in developing, so the key to develop successful mobile applications is usability, especially for users have specific needs such as visually impaired. However, developers do not focus on visually impaired users. Moreover, there are limited studies and usability evaluation models for mobile applications for visually impaired so developers use just a modified usability evaluation methods which are not enough and useful to evaluate mobile applications for visually impaired, or they use general usability evaluation models. Therefore, using these methods or models is difficult for evaluator and not useful for visually impaired users. This study conducts Systematic Literature Review (SLR) to identify usability dimensions that help mobile applications developers and evaluators to evaluate mobile application for users which have moderate and severe visual impairment. The result shows that, six dimensions that have a significant impact on moderate and severe visually impaired users' satisfaction, who use mobile applications. These dimensions namely efficiency, effectiveness, satisfaction, errors, accessibility and understandability.

scholarly journals Systematic Literature Review on Machine Learning and Student Performance Prediction: Critical Gaps and Possible Remedies

2021 ◽  
Vol 11 (22) ◽  
pp. 10907
Author(s):  
Boran Sekeroglu ◽  
Rahib Abiyev ◽  
Ahmet Ilhan ◽  
Murat Arslan ◽  
John Bush Idoko
Keyword(s):  
Machine Learning ◽  
Literature Review ◽  
Student Performance ◽  
Systematic Literature Review ◽  
Performance Prediction ◽  
Global Education ◽  
Future Studies ◽  
The Future ◽  
The Common ◽  
Students Success

Improving the quality, developing and implementing systems that can provide advantages to students, and predicting students’ success during the term, at the end of the term, or in the future are some of the primary aims of education. Due to its unique ability to create relationships and obtain accurate results, artificial intelligence and machine learning are tools used in this field to achieve the expected goals. However, the diversity of studies and the differences in their content create confusion and reduce their ability to pioneer future studies. In this study, we performed a systematic literature review of student performance prediction studies in three different databases between 2010 and 2020. The results are presented as percentages by categorizing them as either model, dataset, validation, evaluation, or aims. The common points and differences in the studies are determined, and critical gaps and possible remedies are presented. The results and identified gaps could be eliminated with standardized evaluation and validation strategies. It is determined that student performance prediction studies should be more frequently focused on deep learning models in the future. Finally, the problems that can be solved using a global dataset created by a global education information consortium, as well as its advantages, are presented.

scholarly journals A Systematic Literature Review of Inclusive Climate Change Adaption

2021 ◽  
Vol 13 (19) ◽  
pp. 10617
Author(s):  
Ha Pham ◽  
Marc Saner
Keyword(s):  
Climate Change ◽  
Literature Review ◽  
International Development ◽  
Systematic Literature Review ◽  
Selection Criteria ◽  
Knowledge Integration ◽  
Grey Literature ◽  
Inclusive Approach ◽  
The Common ◽  
Inclusive Processes

Inclusive approaches have been applied in many areas, including human resources, international development, urban planning, and innovation. This paper is a systematic literature review to describe the usage trends, scope, and nature of the inclusive approach in the climate change adaptation (CCA) context. We developed search algorithms, explicit selection criteria, and a coding questionnaire, which we used to review a total of 106 peer-reviewed articles, 145 grey literature documents, and 67 national communications to the United Nations Framework Convention on Climate Change (UNFCCC); 318 documents were reviewed in total. Quantitatively, the methodology reveals a slight increase in usage, with a focus on non-Annex 1 countries, gender issues, and capacity building. Qualitatively, we arranged the key insights into the following three categories: (1) inclusion in who or what adapts; (2) motivating inclusive processes; and (3) anticipated outcomes of inclusive CCA. We conclude, with the observation, that many issues also apply to Annex 1 countries. We also argue that the common language nature of the word ‘inclusive’ makes it applicable to other CCA-relevant contexts, including government subsidies, science policy, knowledge integration and mobilization, performance measurement, and the breadth of the moral circle that a society should adopt.

scholarly journals Dissociating Meat from its Animal Origins: A Systematic Literature Review

2019 ◽  
Author(s):  
Jonas R. Kunst
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Behavioral Outcomes ◽  
Future Research ◽  
Moderating Variables ◽  
Cross Cultural Differences ◽  
Long Time ◽  
The Common ◽  
Ambivalent Relationship

Meat eaters often have an ambivalent relationship with the common practice of killing animals for food. They enjoy the taste of meat but dislike the harming of animals that it entails. This moral conflict, often referred to as the ‘meat paradox,’ tends to result in cognitive dissonance that meat eaters need to resolve. One of the arguably most basic strategies to deal with this dissonance is to cognitively dissociate meat from its animal origins. Whereas philosophers for long time have theorized about the role of such dissociation for consumer behavior, researchers have only recently started to empirically investigate the phenomenon. Here, we present the first systematic literature review of research on consumers’ tendency to dissociate meat from its animal origins. Twenty-one publications comprising eight qualitative, one mixed-methods, four correlational, and twenty experimental/interventional studies were identified, which all provided support for the central psychological role of dissociation for meat consumption. However, the review also revealed the need for further research on moderating variables such as gender, age and generation, dietary styles, and people’s place of living, including cross-cultural differences. Strikingly, no study so far seems to have included behavioral outcomes, urging the need for future research on how dissociation might affect behavior.

scholarly journals Arabic Aspect-Based Sentiment Analysis: A Systematic Literature Review

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Ruba Obiedat ◽  
Duha Al-Darras ◽  
Esra Alzaghoul ◽  
Osama Harfoushi
Keyword(s):  
Literature Review ◽  
Sentiment Analysis ◽  
Systematic Literature Review
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