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Fulltext BIIJ embracing social media

Kadri N, Ng Kh

Biomed Imaging Interv J, 2010 Jan-Mar;6(1):e1.
PMID: 21611061 DOI: 10.2349/biij.6.1.e1
Matched MeSH terms: Social Media*
Fulltext Salient features of customer engagement, visual presentation and copywriting for effective social media marketing: an exploratory perspective

Nooraini Mohamad Sheriff, Aisya Syahira Zulkifli, Wan Nur Shahira Wan Othman

Journal of Academia Universiti Teknologi MARA Negeri Sembilan, 2018;6(2):28-37.
MyJurnal

As internet-based marketing utilizes channels of social media to interact and attract prospective customers to make online purchase for apparels there is a need to ascertain the extent to which salient features of social media such as customer engagement, attractive visual presentation and copywriting that are capable of driving such purchase. A total of 128 usable questionnaires were included in this study. Distribution of online questionnaires was assisted where the online questionnaire link in Google document was emailed to the company’s sales team who in turn blasted the online questionnaire via email to all of their online customers in their data base. A positive significant (0.01) high correlation of .709 for customer engagement and .711 were obtained for visual presentation with online purchase for apparels. In addition, a positive significant (0.01) modest correlation of .653was secured for copywriting and online purchase of apparels. The study affirms that online firms using social media marketing must ensure they engage their online customers through discussions, reviews, contest and comments to understand them better and to build relationship between their brand and customer’s which has a positive impact on sales. Social media marketing too needs an exemplary visual presentation to explain abstract concepts and facilitates retention of information and maintain audience interest which ultimately has a positive impact on sale. Consequently, copywriting too performs an important role of convincing people about a product by transforming product features into benefits to convince readers into making a purchase.

Matched MeSH terms: Social Media*
Going viral: embracing the changing culture of social media in travel medicine

Flaherty GT, Walden LM

Travel Med Infect Dis, 2015 Mar-Apr;13(2):120-1.
PMID: 25812774 DOI: 10.1016/j.tmaid.2015.03.005
Matched MeSH terms: Social Media*
Fulltext Association Between Public Opinion and Malaysian Government Communication Strategies About the COVID-19 Crisis: Content Analysis of Image Repair Strategies in Social Media

Masngut N, Mohamad E

J Med Internet Res, 2021 08 04;23(8):e28074.
PMID: 34156967 DOI: 10.2196/28074

BACKGROUND: The COVID-19 health crisis has posed an unprecedented challenge for governments worldwide to manage and communicate about the pandemic effectively, while maintaining public trust. Good leadership image in times of a health emergency is paramount to ensure public confidence in governments' abilities to manage the crisis.
OBJECTIVE: The aim of this study was to identify types of image repair strategies utilized by the Malaysian government in their communication about COVID-19 in the media and analyze public responses to these messages on social media.
METHODS: Content analysis was employed to analyze 120 media statements and 382 comments retrieved from Facebook pages of 2 mainstream newspapers-Berita Harian and The Star. These media statements and comments were collected within a span of 6 weeks prior to and during the first implementation of Movement Control Order by the Malaysian Government. The media statements were analyzed according to Image Repair Theory to categorize strategies employed in government communications related to COVID-19 crisis. Public opinion responses were measured using modified lexicon-based sentiment analysis to categorize positive, negative, and neutral statements.
RESULTS: The Malaysian government employed all 5 Image Repair Theory strategies in their communications in both newspapers. The strategy most utilized was reducing offensiveness (75/120, 62.5%), followed by corrective action (30/120, 25.0%), evading responsibilities (10/120, 8.3%), denial (4/120, 3.3%), and mortification (1/120, 0.8%). This study also found multiple substrategies in government media statements including denial, shifting blame, provocation, defeasibility, accident, good intention, bolstering, minimization, differentiation, transcendence, attacking accuser, resolve problem, prevent recurrence, admit wrongdoing, and apologize. This study also found that 64.7% of public opinion was positive in response to media statements made by the Malaysian government and also revealed a significant positive association (P=.04) between image repair strategies utilized by the Malaysian government and public opinion.
CONCLUSIONS: Communication in the media may assist the government in fostering positive support from the public. Suitable image repair strategies could garner positive public responses and help build trust in times of crisis.

Matched MeSH terms: Social Media*
Fulltext Mining of Opinions on COVID-19 Large-Scale Social Restrictions in Indonesia: Public Sentiment and Emotion Analysis on Online Media

Tri Sakti AM, Mohamad E, Azlan AA

J Med Internet Res, 2021 08 09;23(8):e28249.
PMID: 34280116 DOI: 10.2196/28249

BACKGROUND: One of the successful measures to curb COVID-19 spread in large populations is the implementation of a movement restriction order. Globally, it was observed that countries implementing strict movement control were more successful in controlling the spread of the virus as compared with those with less stringent measures. Society's adherence to the movement control order has helped expedite the process to flatten the pandemic curve as seen in countries such as China and Malaysia. At the same time, there are countries facing challenges with society's nonconformity toward movement restriction orders due to various claims such as human rights violations as well as sociocultural and economic issues. In Indonesia, society's adherence to its large-scale social restrictions (LSSRs) order is also a challenge to achieve. Indonesia is regarded as among the worst in Southeast Asian countries in terms of managing the spread of COVID-19. It is proven by the increased number of daily confirmed cases and the total number of deaths, which was more than 6.21% (1351/21,745) of total active cases as of May 2020.
OBJECTIVE: The aim of this study was to explore public sentiments and emotions toward the LSSR and identify issues, fear, and reluctance to observe this restriction among the Indonesian public.
METHODS: This study adopts a sentiment analysis method with a supervised machine learning approach on COVID-19-related posts on selected media platforms (Twitter, Facebook, Instagram, and YouTube). The analysis was also performed on COVID-19-related news contained in more than 500 online news platforms recognized by the Indonesian Press Council. Social media posts and news originating from Indonesian online media between March 31 and May 31, 2020, were analyzed. Emotion analysis on Twitter platform was also performed to identify collective public emotions toward the LSSR.
RESULTS: The study found that positive sentiment surpasses other sentiment categories by 51.84% (n=1,002,947) of the total data (N=1,934,596) collected via the search engine. Negative sentiment was recorded at 35.51% (686,892/1,934,596) and neutral sentiment at 12.65% (244,757/1,934,596). The analysis of Twitter posts also showed that the majority of public have the emotion of "trust" toward the LSSR.
CONCLUSIONS: Public sentiment toward the LSSR appeared to be positive despite doubts on government consistency in executing the LSSR. The emotion analysis also concluded that the majority of people believe in LSSR as the best method to break the chain of COVID-19 transmission. Overall, Indonesians showed trust and expressed hope toward the government's ability to manage this current global health crisis and win against COVID-19.

Matched MeSH terms: Social Media*
Fulltext The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis

Singla RK, De R, Efferth T, Mezzetti B, Sahab Uddin M, Sanusi, et al.

Phytomedicine, 2023 Jan;108:154520.
PMID: 36334386 DOI: 10.1016/j.phymed.2022.154520

BACKGROUND: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools.
METHODS: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST.
RESULTS AND CONCLUSION: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events.

Matched MeSH terms: Social Media*
Socialization During the COVID-19 Pandemic: The Role of Social and Scientific Networks During Social Distancing

Momtazmanesh S, Samieefar N, Uddin LQ, Ulrichs T, Kelishadi R, Roudenok V, et al.

Adv Exp Med Biol, 2021;1318:911-921.
PMID: 33973219 DOI: 10.1007/978-3-030-63761-3_51

In the COVID-19 era, while we are encouraged to be physically far away from each other, social and scientific networking is needed more than ever. The dire consequences of social distancing can be diminished by social networking. Social media, a quintessential component of social networking, facilitates the dissemination of reliable information and fighting against misinformation by health authorities. Distance learning, telemedicine, and telehealth are among the most prominent applications of networking during this pandemic. Additionally, the COVID-19 pandemic highlights the importance of collaborative scientific efforts. In this chapter, we summarize the advantages of harnessing both social and scientific networking in minimizing the harms of this pandemic. We also discuss the extra collaborative measures we can take in our fight against COVID-19, particularly in the scientific field.

Matched MeSH terms: Social Media*
Fulltext Is there an association between article citations and altmetrics in travel medicine research?

Galickas D, Flaherty GT

J Travel Med, 2021 Dec 29;28(8).
PMID: 34414442 DOI: 10.1093/jtm/taab115
Matched MeSH terms: Social Media*
Fulltext Weak and strong ties and its connection to experts' problem-solving styles in scaffolding students' PBL activities on social media

Abdullah AH, Neo TK, Low JH

F1000Res, 2021;10:1076.
PMID: 35035894 DOI: 10.12688/f1000research.73210.2

Background: Studies have acknowledged that social media enables students to connect with and learn from experts from different ties available in the students' personal learning environment (PLE). Incorporating experts into formal learning activities such as scaffolding problem-solving tasks through social media, allows students to understand how experts solve real-world problems. However, studies that evaluate experts' problem-solving styles on social media in relation to the tie strength of the experts with the students are scarce in the extant literature. This study aimed to explore the problem-solving styles that the experts portrayed based on their ties with the students in problem-based learning (PBL) on Facebook. Methods: This study employed a simultaneous within-subject experimental design which was conducted in three closed Facebook groups with 12 final year management students, six business experts, and one instructor as the participants. The experts were invited by the students from the weak and strong ties in their PLE. Hinging on the Strength of Weak Ties Theory (Granovetter, 1973) and problem-solving styles (Selby et al., 2004), this study employed thematic analysis using the ATLAS.ti qualitative data analysis software to map the experts' comments on Facebook. Results: The experts from strong and weak ties who had a prior relationship with the students showed people preference style by being more sensitive to the students' learning needs and demonstrating firmer scaffolding compared to the weak ties' experts who had no prior relationship with the students. Regardless of the types of ties, all experts applied all manner of processing information and orientation to change but the degree of its applications are correlated with the working experience of the experts. Conclusion: The use of weak or strong ties benefited the students as it expedited their problem-solving tasks since the experts have unique expertise to offer depending on the problem-solving styles that they exhibited.

Matched MeSH terms: Social Media*
Fulltext A non-invasive machine learning mechanism for early disease recognition on Twitter: The case of anemia

Sarsam SM, Al-Samarraie H, Alzahrani AI, Shibghatullah AS

Artif Intell Med, 2022 Dec;134:102428.
PMID: 36462907 DOI: 10.1016/j.artmed.2022.102428

Social media sites, such as Twitter, provide the means for users to share their stories, feelings, and health conditions during the disease course. Anemia, the most common type of blood disorder, is recognized as a major public health problem all over the world. Yet very few studies have explored the potential of recognizing anemia from online posts. This study proposed a novel mechanism for recognizing anemia based on the associations between disease symptoms and patients' emotions posted on the Twitter platform. We used k-means and Latent Dirichlet Allocation (LDA) algorithms to group similar tweets and to identify hidden disease topics. Both disease emotions and symptoms were mapped using the Apriori algorithm. The proposed approach was evaluated using a number of classifiers. A higher prediction accuracy of 98.96 % was achieved using Sequential Minimal Optimization (SMO). The results revealed that fear and sadness emotions are dominant among anemic patients. The proposed mechanism is the first of its kind to diagnose anemia using textual information posted on social media sites. It can advance the development of intelligent health monitoring systems and clinical decision-support systems.

Matched MeSH terms: Social Media*
Fulltext Fake News Detection Model on Social Media by Leveraging Sentiment Analysis of News Content and Emotion Analysis of Users' Comments

Hamed SK, Ab Aziz MJ, Yaakub MR

Sensors (Basel), 2023 Feb 04;23(4).
PMID: 36850346 DOI: 10.3390/s23041748

Nowadays, social media has become the main source of news around the world. The spread of fake news on social networks has become a serious global issue, damaging many aspects, such as political, economic, and social aspects, and negatively affecting the lives of citizens. Fake news often carries negative sentiments, and the public's response to it carries the emotions of surprise, fear, and disgust. In this article, we extracted features based on sentiment analysis of news articles and emotion analysis of users' comments regarding this news. These features were fed, along with the content feature of the news, to the proposed bidirectional long short-term memory model to detect fake news. We used the standard Fakeddit dataset that contains news titles and comments posted regarding them to train and test the proposed model. The suggested model, using extracted features, provided a high detection accuracy of 96.77% of the Area under the ROC Curve measure, which is higher than what other state-of-the-art studies offer. The results prove that the features extracted based on sentiment analysis of news, which represents the publisher's stance, and emotion analysis of comments, which represent the crowd's stance, contribute to raising the efficiency of the detection model.

Matched MeSH terms: Social Media*
Fulltext Halal or Haram? The COVID-19 Vaccine Discussion Among Twitter users in Malaysia

Mohd Jenol NA, Ahmad Pazil NH

J Relig Health, 2023 Aug;62(4):2933-2946.
PMID: 36964281 DOI: 10.1007/s10943-023-01798-4

Vaccine hesitancy is gaining attention due to the increasing spread of the COVID-19 pandemic in Malaysia. Malaysia is a majority Muslim country and religion has a significant influence on the acceptance or rejection of vaccines. This is clearly seen through the disagreement over the halal status of vaccines. Social media has become a platform for discussion and dissemination of information and dis-information on vaccines. Thus, it has had a relatively significant influence on vaccine hesitancy among social media users. By analysing tweets from February 2020 to February 2021 using Twitter API, this paper highlights the discussion of COVID-19 vaccines' halal status on Twitter. This study focuses on the analysis of vaccination reluctancy among the Twitter users in Malaysia and found that the most prevalent theme from the discussion is the constructed religious narratives to justify scientifically misleading and false claims concerning vaccination represented on social media. This finding also calls for a deeper understanding of society's constructed knowledge concerning contemporary issues in the digital age on social media.

Matched MeSH terms: Social Media*
Fulltext Consequences of local culinary memorable experience: Evidence from TikTok influencers

Shoukat MH, Selem KM, Elgammal I, Ramkissoon H, Amponsah M

Acta Psychol (Amst), 2023 Aug;238:103962.
PMID: 37356362 DOI: 10.1016/j.actpsy.2023.103962

Underpinned by integrating self-determination and source credibility theories (SCT), this paper investigates the focal roles of memorable local food experiences (MLX) and travel influencer endorsement (TIE) on revisit intention. A questionnaire was used to collect data from 513 TikTok influencers (individuals who frequently post videos on TikTok and have a large number of followers). A purposive sampling technique is used to collect data from TikTok influencers who create videos about food tourism in Pakistan. SmartPLS 4.4 was used with PLS-SEM. The empirical results suggest a positive and significant linkage of culinary memorable experience factors with MLX. The focal effects of MLX and TIE on revisit intention are significantly positive. Our findings further revealed that MLX partially mediated the linkage of culinary memorable experience factors with revisit intention, while TIE strengthened the positive relationship between MLX and revisit intention. The study's findings influence travel agents, local food providers, and marketing specialists who develop marketing strategies for local food tourism and online trip purchasing.

Matched MeSH terms: Social Media*
The impact of social media on mental health among young people

Tong WT, Bono SA, Low WY

Asia Pac J Public Health, 2023 Sep;35(6-7):449-450.
PMID: 37649284 DOI: 10.1177/10105395231198919
Matched MeSH terms: Social Media*
Fulltext Contract doctors' strike in Malaysia: A content analysis of the perception of medical fraternity and stakeholders on Facebook

Jinah N, Lee KY, Zakaria NH, Zakaria N, Ismail M, Mohmad S

PLoS One, 2023;18(9):e0292213.
PMID: 37768943 DOI: 10.1371/journal.pone.0292213

Contract appointment policy for newly graduated medical officers was implemented by the Ministry of Health Malaysia in 2016 to overcome the lack of permanent posts. Contract officers faced disadvantages in terms of salary, leave provision, and career prospects. A nationwide strike, Hartal Doktor Kontrak (HDK) was organised on 26th July 2021. Besides generating widespread public attention, HDK was also closely scrutinised by the medical fraternity and stakeholders. This content analysis aimed to explore how the medical fraternity and stakeholders viewed the strike as their perception would offer vital insights into the fundamental causes and viable solutions to the contract appointment policy. A qualitative content analysis of Facebook (FB) posts on the HDK strike was conducted from 1st June 2021 until 28th February 2022. A total of 182 FB posts were retrieved from stakeholders, medical fraternity groups, and medical key opinion personnel. Inductive coding was used in the thematic analysis to identify pertinent themes. Three main themes emerged: triggering factors, reactions to the strike, and outcomes of the strike. Factors that led to the strike included unequal treatment faced by contract officers, frustration with the government's lack of long-term solutions, and aggravation by the COVID-19 pandemic. In terms of reactions, there was a mixture of supportive and opposing voices. No substantial negative impact on the healthcare service resulted from the strike. Instead, it generated widespread attention that propelled the government into implementing solutions to prevent adverse short and long-term consequences. Various suggestions were proposed, including the reform of human resource planning and undergraduate medical education. The results highlight the importance of proactive systemic measures by the government to prevent further strikes that may jeopardise healthcare provision. In summary, social media was found to influence the progress and outcome of HDK, thus demonstrating the impact of media influence on similar issues.

Matched MeSH terms: Social Media*
Fulltext Content framing role on public sentiment formation for pre-crisis detection on sensitive issue via sentiment analysis and content analysis

Watimin NH, Zanuddin H, Rahamad MS, Yadegaridehkordi E

PLoS One, 2023;18(10):e0287367.
PMID: 37851696 DOI: 10.1371/journal.pone.0287367

Social media has been tremendously used worldwide for a variety of purposes. Therefore, engagement activities such as comments have attracted many scholars due its ability to reveal many critical findings, such as the role of users' sentiment. However, there is a lacuna on how to detect crisis based on users' sentiment through comments, and for such, we explore framing theory in the study herein to determine users' sentiment in predicting crisis. Generic content framing theory consists of conflict, economic, human interest, morality, and responsibility attributes frame as independent variables whilst sentiment as dependent variables. Comments from selected Facebook posting case studies were extracted and analysed using sentiment analysis via Application Programme Interface (API) webtool. The comments were then further analysed using content analysis via Positive and Negative Affect Schedule (PANAS) scale and statistically evaluated using SEM-PLS. Model shows that 44.8% of emotion and reactions towards sensitive issue posting are influenced by independent variables. Only economic consequences and responsibility attributes frame had correlation towards emotion and reaction at p<0.05. News reporting on direction towards economic and responsibility attributes sparks negative sentiment, which proves that it can best be described as pre-crisis detection to assist the Royal Malaysian Police and other relevant stakeholders to prevent criminal activities in their respective social media.

Matched MeSH terms: Social Media*
Fulltext COVID-19 Vaccine Acceptance among Social Media Users: A Content Analysis, Multi-Continent Study

Shaaban R, Ghazy RM, Elsherif F, Ali N, Yakoub Y, Aly MO, et al.

Int J Environ Res Public Health, 2022 May 08;19(9).
PMID: 35565132 DOI: 10.3390/ijerph19095737

Vaccine hesitancy (VH) is defined as a delayed in acceptance or refusal of vaccines despite availability of vaccination services. This multinational study examined user interaction with social media about COVID-19 vaccination. The study analyzed social media comments in 24 countries from five continents. In total, 5856 responses were analyzed; 83.5% of comments were from Facebook, while 16.5% were from Twitter. In Facebook, the overall vaccine acceptance was 40.3%; the lowest acceptance rates were evident in Jordan (8.5%), Oman (15.0%), Senegal (20.0%) and Morocco (20.7%) and the continental acceptance rate was the lowest in North America 22.6%. In Twitter, the overall acceptance rate was (41.5%); the lowest acceptance rate was found in Oman (14.3%), followed by USA (20.5%), and UK (23.3%) and the continental acceptance rate was the lowest in North America (20.5%), and Europe (29.7%). The differences in vaccine acceptance across countries and continents in Facebook and Twitter were statistically significant. Regarding the tone of the comments, in Facebook, countries that had the highest number of serious tone comments were Sweden (90.9%), USA (61.3%), and Thailand (58.8%). At continent level, serious comments were the highest in Asia (58.4%), followed by Africa (46.2%) and South America (46.2%). In Twitter, the highest serious tone was reported in Egypt (72.2%) while at continental level, the highest proportion of serious comments was observed in Asia (59.7%), followed by Europe (46.5%). The differences in tone across countries and continents in Facebook and Twitter and were statistically significant. There was a significant association between the tone and the position of comments. We concluded that the overall vaccine acceptance in social media was relatively low and varied across the studied countries and continents. Consequently, more in-depth studies are required to address causes of such VH and combat infodemics.

Matched MeSH terms: Social Media*
Fulltext Global trends in research related to social media in psychology: mapping and bibliometric analysis

Zyoud SH, Sweileh WM, Awang R, Al-Jabi SW

Int J Ment Health Syst, 2018;12:4.
PMID: 29387147 DOI: 10.1186/s13033-018-0182-6

Background: Social media, defined as interactive Web applications, have been on the rise globally, particularly among adults. The objective of this study was to investigate the trend of the literature related to the most used social network worldwide (i.e. Facebook, Twitter, LinkedIn, Snapchat, and Instagram) in the field of psychology. Specifically, this study will assess the growth in publications, citation analysis, international collaboration, author productivity, emerging topics and the mapping of frequent terms in publications pertaining to social media in the field of psychology.

Methods: Publications related to social media in the field of psychology published between 2004 and 2014 were obtained from the Web of Science. The records extracted were analysed for bibliometric characteristics such as the growth in publications, citation analysis, international collaboration, emerging topics and the mapping of frequent terms in publications pertaining to social media in the field of psychology. VOSviewer v.1.6.5 was used to construct scientific maps.

Results: Overall, 959 publications were retrieved during the period between 2004 and 2015. The number of research publications in social media in the field of psychology showed a steady upward growth. Publications from the USA accounted for 57.14% of the total publications and the highest h-index (48).The most common document type was research articles (873; 91.03%). Over 99.06% of the publications were published in English. Computers in Human Behavior was the most prolific journal. The University of Wisconsin-Madison ranked first in terms of the total publications (n = 39). A visualisation analysis showed that personality psychology, experimental psychology, psychological risk factors, and developmental psychology were continual concerns of the research.

Conclusions: This is the first study reporting the global trends in the research related to social media in the psychology field. Based on the raw data from the Web of Science, publication characteristics such as quality and quantity were assessed using bibliometric techniques over 12 years. The USA and its institutions play a dominant role in this topic. The most preferred topics related to social media in psychology are personality psychology, experimental psychology, psychological risk factors, and developmental psychology.

Matched MeSH terms: Social Media*
Fulltext A normalization model for repeated letters in social media hate speech text based on rules and spelling correction

Mansur Z, Omar N, Tiun S, Alshari EM

PLoS One, 2024;19(3):e0299652.
PMID: 38512966 DOI: 10.1371/journal.pone.0299652

As social media booms, abusive online practices such as hate speech have unfortunately increased as well. As letters are often repeated in words used to construct social media messages, these types of words should be eliminated or reduced in number to enhance the efficacy of hate speech detection. Although multiple models have attempted to normalize out-of-vocabulary (OOV) words with repeated letters, they often fail to determine whether the in-vocabulary (IV) replacement words are correct or incorrect. Therefore, this study developed an improved model for normalizing OOV words with repeated letters by replacing them with correct in-vocabulary (IV) replacement words. The improved normalization model is an unsupervised method that does not require the use of a special dictionary or annotated data. It combines rule-based patterns of words with repeated letters and the SymSpell spelling correction algorithm to remove repeated letters within the words by multiple rules regarding the position of repeated letters in a word, be it at the beginning, middle, or end of the word and the repetition pattern. Two hate speech datasets were then used to assess performance. The proposed normalization model was able to decrease the percentage of OOV words to 8%. Its F1 score was also 9% and 13% higher than the models proposed by two extant studies. Therefore, the proposed normalization model performed better than the benchmark studies in replacing OOV words with the correct IV replacement and improved the performance of the detection model. As such, suitable rule-based patterns can be combined with spelling correction to develop a text normalization model to correctly replace words with repeated letters, which would, in turn, improve hate speech detection in texts.

Matched MeSH terms: Social Media*
Fulltext Sustainable impact of COVID-19 on education projects: aspects of naturalism

Pu S, Ali Turi J, Bo W, Zheng C, Tang D, Iqbal W

Environ Sci Pollut Res Int, 2022 Oct;29(46):69555-69572.
PMID: 35567688 DOI: 10.1007/s11356-022-20387-8

History records show that pandemics and threats have always given new directions to the thinking, working, and learning styles. This article attempts to thoroughly document the positive core of coronavirus 2019 (COVID-19) and its impact on global social psychology, ecological stability, and development. Structural equation modeling (SEM) is used to test the hypotheses and comprehend the objectives of the study. The findings of the study reveals that the path coefficients for the variables health consciousness, naturalism, financial impact and self-development, sustainability, compassion, gregariousness, sympathy, and cooperation demonstrate that the factors have a positive and significant effect on COVID-19 prevention. Moreover, the content analysis was conducted on recently published reports, blog content, newspapers, and social media. The pieces of evidence from history have been cited to justify the perspective. Furthermore, to appraise the opinions of professionals of different walks of life, an online survey was conducted, and results were discussed with expert medical professionals. Outcomes establish that the pandemics give birth to creativity, instigate innovations, prompt inventions, establish human ties, and foster altruistic elements of compassion and emotionalism.

Matched MeSH terms: Social Media*

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