The Weaponisation of Public Comment Rules in Policy Deliberations A Case Study of COVID-19 Community Engagement at Florida Schools

The Covid-19 pandemic heightened already intense and increased scrutiny of public education in recent years. The administrative impulse to stage community engagement efforts to deliberate upon these questions, however well-intentioned, rarely realises full community engagement and reflection. Based on an examination of public engagement events held at Florida schools related to the Covid-19 health crisis, the proposed essay identifies a more concerning transformation of "public comment" into a weaponisable prop for lawmakers seeking the public legitimacy necessary for their agenda, marrying the worlds of critical studies with those of public administration and its orientations. More than merely failing to genuinely engage the public, we argue that such events forestall a more productive arrangement of the democratic form that does not rely on publicness and the leader that secures that space. Ultimately, we suggest a path that affords the possibility of public engagement, but that does not seal off the possibility of that more radical democratic future to come.

The Weaponisation of Public Comment Rules in Policy Deliberations

The Covid-19 pandemic heightened already intense and increased scrutiny of public education in recent years. The administrative impulse to stage community engagement efforts to deliberate upon these questions, however well-intentioned, rarely realises full community engagement and reflection. Based on an examination of public engagement events held at Florida schools related to the Covid-19 health crisis, the proposed essay identifies a more concerning transformation of "public comment” into a weaponisable prop for lawmakers seeking the public legitimacy necessary for their agenda, marrying the worlds of critical studies with those of public administration and its orientations. More than merely failing to genuinely engage the public, we argue that such events forestall a more productive arrangement of the democratic form that does not rely on publicness and the leader that secures that space. Ultimately, we suggest a path that affords the possibility of public engagement, but that does not seal off the possibility of that more radical democratic future to come. [ FROM AUTHOR] Copyright of Javnost-The Public is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

The undervalued power of museum-guided tours: a case study of Xuhui Art Museum in China

Amid the Covid-19 pandemic, how to attract back visitors has been a major problem for museums across the world. Among diverse museum activities, human-guided tours remain under-studied to date. A post-hoc case analysis on Xuhui Art Museum provided empirical evidence demonstrating the potential power of guided tours. Quantitative methods in content analysis and semantic network analysis were employed to identify general features of visitor comments from both visitor books and social media. An in-depth interview was also conducted with the Chief Curator. Results reveal that the work of ‘jiangjie', or tour guiding, is greatly appreciated and plays a vital role in improving visitor experience and satisfaction. This study calls for re-evaluation of the functions, potential and effects of tour guiding, and a renewal of live tours for better on-site experience in a post COVID-19 period.

Sentiment analysis of students' Facebook comments toward university announcements

Students' opinions are among the critical indicators to evaluate the university teaching process. However, due to the absence of an official online system in most universities that provides a mechanism for obtaining students' opinions on several university announcements, most students use various social networks to express their feelings and provide their opinions toward these announcements. We present, through this paper, sentiment analysis of Facebook comments written in the Moroccan Arabic dialect. These comments reflect the opinions of students about university announcements during the COVID-19 pandemic, especially those related to teaching mode and ex-am planning. Then, the comments collected were cleaned, preprocessed, and manually classified into four categories, namely positive, neutral, negative, and bipolar. Further, data dimensionality reduction is applied using TF-IDF and Chi-square test. Finally, we evaluated the performance of three standard classifiers, i.e., Naïve Bayesian (NB), Support Vector Machines (SVM), and Random Forests (RF) using k-fold cross-validation. The results showed that the SVM-based classifier performs as well as the RF-based classifier regarding the classification's accuracy and F1-score, while the NB-based classifier lags behind them. © 2022 IEEE.

Clicks and comments: Representation of wildlife crime in Pakistan in social media posts

To evaluate the online presence of wildlife crime and the public's reaction to these crimes, we collected data on species, locations, animal status, and motives of wildlife crime depicted on nine Pakistani Facebook pages and eight groups from January 2016 to May 2021. We categorized reactions to images depicting birds, mammals, and reptiles and applied generalized linear models to the total number of reactions on posts. In 594 relevant posts, we identified 10,644 animals of 138 species. Common Krait (Bungarus caeruleus) had the highest number of posts, followed by Grey Francolin (Ortygornis pondicerianus) and Black Francolin (Francolinus francolinus). The number of posts has generally increased, particularly after the Covid-19 lockdown in March 2020. Almost 66 % of the posts showed animals being killed, 27 % were captured with no visible signs of torture, and the rest showed visible signs of torture in captivity. The most common reason for wildlife crimes was illegal hunting, followed by fear and illegal trade. Most victims of illegal hunting were birds, while reptiles were predominantly killed for fear. However, illegal trade was affecting all three classes of animals. Killed or tortured animals received more reactions than non-tortured animals, as well as more comments both against and in favor of the crime. Crimes against reptiles received more pro-crime comments than birds and mammals. Our results reflect the importance of social media to monitor wildlife crimes. Urgent actions are necessary by the relevant authorities to improve management and strengthen the response of law enforcement to wildlife crime. © 2023 The Authors

Safety Perception Evaluation of Civil Aviation Based on Weibo Posts in China: An Enhanced Large-Scale Group Decision-Making Framework

The massive spread of COVID-19 and the crash of China Eastern Airlines MU5735 have negatively impacted the public's perception of civil aviation safety, which further affects the progress of the civil aviation industry and economic growth. The aim of research is to investigate the public's perception of China's civil aviation safety and give the authorities corresponding suggestions. First, we use online comment collection and sentiment analysis techniques to construct a novel evaluation index system reflecting the public's greatest concern for civil aviation safety. Then, we propose two novel large-scale group decision-making (LSGDM) models for aggregating evaluation: (1) K-means clustering with a novel distance measure for evaluators combined with unsupervised K-means clustering in two-stage, (2) unsupervised K-means clustering for evaluators combined with unsupervised K-means clustering for processing evaluation in two-stage. Finally, we compare the characteristics of different models and use the average of the two models as the final evaluation results. © 2023, The Author(s) under exclusive licence to Taiwan Fuzzy Systems Association.

Novel ABC: Aspect Based Classification of Sentiments Using Text Mining for COVID-19 Comments

Intricate text mining techniques encompass various practices like classification of text, summarization and detection of topic, extraction of concept, search and retrieval of ideal content, document clustering along with many more aspects like sentiment extraction, text conversion, natural language processing etc. These practices in turn can be used to discover some non-trivial knowledge from a pool of text-based documents. Arguments, difference in opinions and confrontations in the form of words and phrases signify the knowledge regarding an ongoing situation. Extracting sentiment from text that is gathered from online networking web-based platforms entitles the task of text mining in the field of natural language processing. This paper presents a set of steps to optimize the text mining techniques in an attempt to simplify and recognize the aspect-based sentiments behind the content obtained from social media comments. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The Role of the Russian Social Network Vkontakte During the Covid-19 Pandemic in Teaching Students of Agro-Industrial Faculties the First Foreign Language

This work is devoted to interactive methods of using the Russian social network VKontakte in the study of the first foreign language by students of technical universities of agro-industrial faculties. Currently, training is closely connected with modern Internet technologies and social networks. Social network is one of the forms of distance learning. In our article, we described an experiment conducted with the first-year full-time students of the Don State Technical University studying their first foreign language. The goal of our research was the identification and description of the most influencing forms and methods for the motivation of students in teaching the first foreign language. In the presented research work, we used the empirical method and the method of pedagogical research. We have explored a variety of social networks that are most often used by students, namely: Instagram, Odnoklassniki, Twitter, YouTube. We conducted an experiment and made an analysis of the obtained data. The material for our analysis was the social network VKontakte. We have created an open training group, in which students of the agro-industrial faculty of full-time education studying the first foreign language were signed. As a result of the inquest, we have identified the most relevant social network among first-year students. It has been established that Internet sources influence the interest and motivation of students in learning the first foreign language. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Analyzing the Effect of COVID-19 on Education by Processing Users' Sentiments

COVID-19 infection has been a major topic of discussion on social media platforms since its pandemic outbreak in the year 2020. From daily activities to direct health consequences, COVID-19 has undeniably affected lives significantly. In this paper, we especially analyze the effect of COVID-19 on education by examining social media statements made via Twitter. We first propose a lexicon related to education. Then, based on the proposed dictionary, we automatically extract the education-related tweets and also the educational parameters of learning and assessment. Afterwards, by analyzing the content of the tweets, we determine the location of each tweet. Then the sentiments of the tweets are analyzed and examined to extract the frequency trends of positive and negative tweets for the whole world, and especially for countries with a significant share of COVID-19 cases. According to the analysis of the trends, individuals were globally concerned about education after the COVID-19 outbreak. By comparing between the years 2020 and 2021, we discovered that due to the sudden shift from traditional to electronic education, people were significantly more concerned about education within the first year of the pandemic. However, these concerns decreased in 2021. The proposed methodology was evaluated using quantitative performance metrics, such as the F1-score, precision, and recall. © 2023 by the authors. Licensee MDPI, Basel, Switzerland.

A comment-driven evidence appraisal approach to promoting research findings into practice when only uncertain evidence is available.

BACKGROUND: Comments in PubMed are usually short papers for supporting or refuting claims, or discussing methods and findings in original articles. This study aims to explore whether they can be used as a quick and reliable evidence appraisal instrument for promoting research findings into practice, especially in emergency situations such as COVID-19 in which only missing, incomplete or uncertain evidence is available. METHODS: Evidence-comment networks (ECNs) were constructed by linking COVID-19-related articles to the commentaries (letters, editorials or brief correspondence) they received. PubTator Central was used to extract entities with a high volume of comments from the titles and abstracts of the articles. Among them, six drugs were selected, and their evidence assertions were analysed by exploring the structural information in the ECNs as well as the sentiment of the comments (positive, negative, neutral). Recommendations in WHO guidelines were used as the gold standard control to validate the consistency, coverage and efficiency of comments in reshaping clinical knowledge claims. RESULTS: The overall positive/negative sentiments of comments were aligned with recommendations for/against the corresponding treatments in the WHO guidelines. Comment topics covered all significant points of evidence appraisal and beyond. Furthermore, comments may indicate the uncertainty regarding drug use for clinical practice. Half of the critical comments emerged 4.25 months earlier on average than the guideline release. CONCLUSIONS: Comments have the potential as a support tool for rapid evidence appraisal as they have a selection effect by appraising the benefits, limitations and other clinical practice issues of concern in existing evidence. We suggest as a future direction an appraisal framework based on the comment topics and sentiment orientations to leverage the potential of scientific commentaries supporting evidence appraisal and decision-making.

Public Engagement with Romanian Government Social Media Accounts during the COVID-19 Pandemic.

Following international best practice examples, the Romanian government resorted to its social media accounts to disseminate information and unfold an awareness and persuasion campaign to fight the COVID-19 pandemic. The article focuses on the use of the government's YouTube and Facebook accounts to persuade the population to get vaccinated in 2021 via video messages tailored for this purpose. The research quantified the volume of public engagement with the two waves of the persuasive campaign, finding that, while click-based reactions tended to show a positive attitude toward the campaign, the comments mainly denoted frustration, anger, and anxiety on the part of the public. Moreover, the citizens' engagement with the campaign messages was by far lower than the number of subscribers and followers of the analyzed social media accounts. The goal of the COVID-19 public health persuasion campaign was to build support for the governmental policy and minimize the risks of the pandemic while vaccination was being rolled out. The public reaction to the governmental campaign showed that a finer and more adapted approach was necessary. This study offers a qualitative basis for informing health communication strategies of the challenges posed by social media platforms used in crisis times.

Online Review Comments affecting Purchase Intention: A Pilot Study

The outbreak of COVID-19 since the end of 2019 has led many people to work for home, reducing economic activity in many countries except online shopping, which is thriving during the pandemic. However, shopping is not take-and-go activity,as it needs references to help make the decision. Buying goods online is not as convenient as buying at physical stores where the customers can check the actual state of goods, obtain recommendations from the clerks or compare it with other similar goods. All these physical activities are persuasions. However, the main references for buying online are online third-party comments and brand image. People noticed the comments online, whether positive or negative about the product. Consumers write comments on the Internet according to their different impressions on the brands. Therefore, how the brand image and online comments affect persuasion is worthy of study. This pilot study thus takes the purchase of mobile phones as an example to explore the factors of people's evaluation of comments and brand image. The analytical results of exploratory factor analysis show that the questionnaire design is suitable. The formal study can take these research results as a reference. © 2021 ACM.

i-Comments: On-screen Individualized Comments for Online Learning Support

With the rapid development of digitization in education, online learning has become an alternative and promising way to enable flexible learning scenarios. Especially after COVID-19, online learning draws more and more attention. However, online learning has inherent disadvantages and problems. One of them is that learners have difficulty in concentrating, and the other one is that they may feel lonely during lessons. In this study, a new model of on-screen individualized comments, namely i-Comments, is proposed for online learning support. In the proposed model, three elements, i.e., timing, content, and quantity of i-Comments, are defined respectively, which are used to help learners improve concentration and decrease the feeling of loneliness. Furthermore, an experiment is designed to evaluate the model and verify whether the proposed model can help learners gain a better learning experience and improve their learning effectiveness. © 2022 IEEE.

Sentiment Analysis for YouTube Educational Videos Using Machine and Deep Learning Approaches

YouTube is one of the most popular video-sharing platforms. Recently, the use of YouTube as an educational tool has increased due to the covid-19 pandemic. The quality of the educational videos is crucial in the learning process. Users' comments on educational videos can help to determine the quality of the videos. Such comments can be utilized using a natural language processing technique called Sentiment Analysis. This research proposes a model to perform sentiment analysis on YouTube Arabic educational videos using classical machine learning classifiers and deep learning models. There are six experiments were conducted on two types of datasets: imbalance and balanced datasets. In addition, three balancing techniques were utilized which are: oversampling, under-sampling, and SMOTE. The results show that the best accuracy obtained from all the experiments was 96% by the SVC, RF, and DL model using the oversampling and SOMTE techniques. The worst accuracy achieved by the ML classifiers was 74% by the KNN classifier using the under-sampling technique. Meanwhile, the worst accuracy achieved by the DL model was 89% for the manually balanced dataset using the bigram, trigram, and five-gram. Additionally, this research introduced a novel dataset based on Arabic YouTube educational videos. This model can be beneficial to many researches in data mining research area or related research areas. © 2022 IEEE.

COVID-19 Vaccine Acceptance among Social Media Users: A Content Analysis, Multi-Continent Study.

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.

COVID-19 Vaccine Acceptance among Social Media Users: A Content Analysis, Multi-Continent Study

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.

Opting for Polarizing Emotions: Strategies of Czech Pro-Vaccination Discussants in the Emotionalized Public Sphere and Debate on a Measles Epidemic

Drawing upon a case study of a heated public online debate on vaccination related to a measles epidemic in the Czech Republic in 2019, this article’s contribution is twofold: First, it adds to recent debates about the emotionalization of the (online) public sphere, and second, it examines communication strategies of vaccination supporters. To capture the heterogeneity of the online debate, we analyzed the discussion forums of 3 mainstream online news servers. Providing observations relevant to current debates surrounding anti-COVID-19 vaccination, our data reveal that the deliberative potential of online debate concerning vaccination is undermined by the offensive nature of pro-vaccination comments. These comments tend to be uncivil, toxic, and offensive mainly due to the use of communication strategies employing destructive emotions. We conclude that by labeling their opponents and constructing dichotomies in which they associate them with individualism and irrationality, the pro-vaccination discussants contribute to further polarization of stances toward vaccination. © 2022 (Lenka Vochocová, Dino Numerato, and Tereza Sedláčková).

Amplify or suppress the inspiration? Comment valence influences the reception of inspirational COVID-19 videos

Can popular media play a role in inspiring and uplifting peoples' spirits during the COVID-19 pandemic? The current study extended existing positive media psychology research by exploring the positive effects of inspirational COVID-19 online videos on meaningful affect, norm perceptions, and prosocial intentions. It was also proposed that positive online comments would amplify beneficial outcomes. A survey experiment (n = 620) with a 2 (video type: inspirational vs. Noninspirational) x 3 (comment type: positive comments, negative comments, or no comments) between-subjects design examined impacts on norm perceptions of self-transcendent behaviors, meaningful affect, and prosocial intentions. Results showed that inspirational videos (vs. noninspirational ones) led to greater prosocial intentions, which were mediated by more positive norm perceptions and stronger meaningful affect. However, instead of an amplifying effect of positive comments, evidence emerged of a suppressing effect of negative comments. Participants who read negative comments (vs. positive comments or no comments) about inspirational content reported more negative norm perceptions, lower levels of meaningful affect, and less prosocial intentions. Also, the light triad personality did not moderate any of the observed effects. The study advances inspirational media research by demonstrating that the content itself is not solely responsible for observed effects but also other cues in the media environment (e.g., others' comments). In addition, it introduced norm perceptions as a potential underlying mechanism in positive media effects. (PsycInfo Database Record (c) 2022 APA, all rights reserved) Impact Statement Inspirational online videos referencing COVID-19 helped to not only elicit positive emotions (e.g., the feeling of being touched and inspired) among individuals but also increase the norm perception that self-transcendent behaviors were favored by others, further leading to greater intentions to act in prosocial ways. However, such positive effects were dampened when the inspirational videos were accompanied by negative comments. The viewing of inspirational video content with accompanying positive comments can be an effective means for promoting mental health and social good. (PsycInfo Database Record (c) 2022 APA, all rights reserved)