scholarly journals An analysis of COVID-19 economic measures and attitudes: evidence from social media mining

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Dorota Domalewska

AbstractThis paper explores the public perception of economic measures implemented as a reaction to the COVID-19 pandemic in Poland in March–June 2020. A mixed-method approach was used to analyse big data coming from tweets and Facebook posts related to the mitigation measures to provide evidence for longitudinal trends, correlations, theme classification and perception. The online discussion oscillated around political and economic issues. The implementation of the anti-crisis measures triggered a barrage of criticism pointing out the shortcomings and ineffectiveness of the solutions. The revised relief legislation was accompanied by a wide-reaching informative campaign about the relief package, which decreased negative sentiment. The analysis also showed that with regard to online discussion about risk mitigation, social media users are more concerned about short-term economic and social effects rather than long-term effects of the pandemic. The findings have significant implications for the understanding of public sentiment related to the COVID-19 pandemic, economic attitudes and relief support implemented to fight the adverse effects of the pandemic.

2021 ◽  
Vol 2 (2) ◽  
pp. 16-25
Author(s):  
Babu Aravind Sivamani ◽  
Dakshinamoorthy Karthikeyan ◽  
Chamundeswari Arumugam ◽  
Pavan Kalyan

This paper attempts to find a relation between the public perception of a company and its stock value price. Since social media is a very powerful tool used by a lot of people to voice their opinions on the performance of a company, it is a good source of information about the public sentiment. Previous studies have shown that the overall public sentiment collected from sites like Twitter do have a relation to the market price of a company over a period of time. The goal is to build on their research to improve the accuracy of predictions and determine if the public perception surrounding a company is a driving factor of its stock growth.


2021 ◽  
Vol 24 (1) ◽  
pp. 60-80
Author(s):  
Sarah Banet-Weiser

When the hashtag #metoo began to circulate in digital and social media, it challenged a familiar interpretation of those who are raped or sexually harassed as victims, positioning women as embodied agents. Yet, almost exactly a year after the #metoo movement shot to visible prominence, a different, though eerily similar, story began to circulate on the same multi-media platforms as #metoo: a story about white male victimhood. Powerful men in positions of privilege (almost always white) began to take up the mantle of victimhood as their own, often claiming to be victims of false accusations of sexual harassment and assault by women. Through the analysis of five public statements by highly visible, powerful men who have been accused of sexual violence, I argue that the discourse of victimhood is appropriated not by those who have historically suffered but by those in positions of patriarchal power. Almost all of the statements contain some sentiment about how the accusation (occasionally acknowledging the actual violence) ‘ruined their life’, and all of the statements analyzed here center the author, the accused white man, as the key subject in peril and the authors position themselves as truth-tellers about the incidents. These statements underscore certain shifts in the public perception of sexual violence; the very success of the #metoo movement in shifting the narrative has meant that men have had to defend themselves more explicitly in public. In order to wrestle back a hegemonic gender stability, these men take on the mantle of victimhood themselves.


2021 ◽  
Vol 9 (3) ◽  
pp. 232596712199005
Author(s):  
Jonathan S. Yu ◽  
James B. Carr ◽  
Jacob Thomas ◽  
Julianna Kostas ◽  
Zhaorui Wang ◽  
...  

Background: Social media posts regarding ulnar collateral ligament (UCL) injuries and reconstruction surgeries have increased in recent years. Purpose: To analyze posts shared on Instagram and Twitter referencing UCL injuries and reconstruction surgeries to evaluate public perception and any trends in perception over the past 3 years. Study Design: Cross-sectional study. Methods: A search of a 3-year period (August 2016 and August 2019) of public Instagram and Twitter posts was performed. We searched for >22 hashtags and search terms, including #TommyJohn, #TommyJohnSurgery, and #tornUCL. A categorical classification system was used to assess the sentiment, media format, perspective, timing, accuracy, and general content of each post. Post popularity was measured by number of likes and comments. Results: A total of 3119 Instagram posts and 267 Twitter posts were included in the analysis. Of the 3119 Instagram posts analyzed, 34% were from patients, and 28% were from providers. Of the 267 Twitter posts analyzed, 42% were from patients, and 16% were from providers. Although the majority of social media posts were of a positive sentiment, over the past 3 years, there was a major surge in negative sentiment posts (97% increase) versus positive sentiment posts (9% increase). Patients were more likely to focus their posts on rehabilitation, return to play, and activities of daily living. Providers tended to focus their posts on education, rehabilitation, and injury prevention. Patient posts declined over the past 3 years (–28%), whereas provider posts increased substantially (110%). Of posts shared by health care providers, 4% of posts contained inaccurate or misleading information. Conclusion: The majority of patients who post about their UCL injury and reconstruction on social media have a positive sentiment when discussing their procedure. However, negative sentiment posts have increased significantly over the past 3 years. Patient content revolves around rehabilitation and return to play. Although patient posts have declined over the past 3 years, provider posts have increased substantially with an emphasis on education.


2018 ◽  
Vol 168 (1) ◽  
pp. 122-139 ◽  
Author(s):  
Catherine Archer ◽  
Kai-Ti Kao

Many mothers can find themselves increasingly isolated and overwhelmed after giving birth to a new baby. This period can be a source of extreme stress, anxiety and depression, which can not only have an economic impact on national health services, but can also have long-term effects on the development of the child. At the same time, social media use among most new mothers has become ubiquitous. This research investigates the role of social media, potentially as a mechanism for social support, among Australian mothers of young children aged from birth to 4 years. The findings indicate that participants had mixed responses to their social media use. While social support was deemed a benefit, there were also some negative aspects to social media use identified. The findings highlight the need to critically interrogate social media’s ability to act as a source of social support for new mothers.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aasif Ahmad Mir ◽  
Sevukan Rathinam ◽  
Sumeer Gul

PurposeTwitter is gaining popularity as a microblogging and social networking service to discuss various social issues. Coronavirus disease 2019 (COVID-19) has become a global pandemic and is discussed worldwide. Social media is an instant platform to deliberate various dimensions of COVID-19. The purpose of the study is to explore and analyze the public sentiments related to COVID-19 vaccines across the Twitter messages (positive, neutral, and negative) and the impact tweets make across digital social circles.Design/methodology/approachTo fetch the vaccine-related posts, a manual examination of randomly selected 500 tweets was carried out to identify the popular hashtags relevant to the vaccine conversation. It was found that the hashtags “covid19vaccine” and “coronavirusvaccine” were the two popular hashtags used to discuss the communications related to COVID-19 vaccines. 23,575 global tweets available in public domain were retrieved through “Twitter Application Programming Interface” (API), using “Orange Software”, an open-source machine learning, data visualization and data mining toolkit. The study was confined to the tweets posted in English language only. The default data cleaning and preprocessing techniques available in the “Orange Software” were applied to the dataset, which include “transformation”, “tokenization” and “filtering”. The “Valence Aware Dictionary for sEntiment Reasoning” (VADER) tool was used for classification of tweets to determine the tweet sentiments (positive, neutral and negative) as well as the degree of sentiments (compound score also known as sentiment score). To assess the influence/impact of tweets account wise (verified and unverified) and sentiment wise (positive, neutral, and negative), the retweets and likes, which offer a sort of reward or acknowledgment of tweets, were used.FindingsA gradual decline in the number of tweets over the time is observed. Majority (11,205; 47.52%) of tweets express positive sentiments, followed by neutral (7,948; 33.71%) and negative sentiments (4,422; 18.75%), respectively. The study also signifies a substantial difference between the impact of tweets tweeted by verified and unverified users. The tweets related to verified users have a higher impact both in terms of retweets (65.91%) and likes (84.62%) compared to the tweets tweeted by unverified users. Tweets expressing positive sentiments have the highest impact both in terms of likes (mean = 10.48) and retweets (mean = 3.07) compared to those that express neutral or negative sentiments.Research limitations/implicationsThe main limitation of the study is that the sentiments of the people expressed over one single social platform, that is, Twitter have been studied which cannot generalize the global public perceptions. There can be a variation in the results when the datasets from other social media platforms will be studied.Practical implicationsThe study will help to know the people's sentiments and beliefs toward the COVID-19 vaccines. Sentiments that people hold about the COVID-19 vaccines are studied, which will help health policymakers understand the polarity (positive, negative, and neutral) of the tweets and thus see the public reaction and reflect the types of information people are exposed to about vaccines. The study can aid the health sectors to intensify positive messages and eliminate negative messages for an enhanced vaccination uptake. The research can also help design more operative vaccine-advocating communication by customizing messages using the obtained knowledge from the sentiments and opinions about the vaccines.Originality/valueThe paper focuses on an essential aspect of COVID-19 vaccines and how people express themselves (positively, neutrally and negatively) on Twitter.


Author(s):  
Muhammad Aditya Majdi

Public perception of immigration content at the TPI East Jakarta Class I Immigration Office is very important in determining the quality of information and understanding of immigration provided to the public by focusing on social media Instagram. With some literacy regarding public perceptions it can produce a public view of immigration content that has been disseminated through social media Instagram TPI Class I Immigration Office, East Jakarta. This can be used as study and learning material in seeing some of the shortcomings that must be addressed by the TPI East Jakarta Class I Immigration Office regarding public perceptions of immigration content. With the descriptive qualitative research method, it explains that there are still gaps or shortcomings of immigration content disseminated through social media Instagram TPI Class I Immigration Office, East Jakarta. So it is very necessary to make several further research studies related to public perceptions of immigration content so as to harmonize understanding between the information provider and the recipient of the information.  


SISTEMASI ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 197
Author(s):  
Okta Fanny ◽  
Heri Suroyo

From the research that has been done, it can be concluded that Sentiment Analysis can be used to know the sentiment of the public, especially Twitter netizens against omnibus law. After the sentiment analysis, it looks neutral artmen with the largest percentage of 55%, then positive sentiment by 35% and negative sentiment by 10%. The results of the analysis showed that the Naïve Bayes Classifier method provides classification test results with accuracy in Hashtag Pro with an average accuracy score of 92.1%, precision values with an average of 94.8% and recall values with an average of 90.7%. While Hashtag Counter For data classification, with an average accuracy value of 98.3%, precision value with an average of 97.6% and recall value with an average of 98.7%. The result of text cloud analysis conducted on a combination of hashtags both Hashtag pros and Hashtags cons, the dominant word appears is Omnibus Law which means that all hashtags in scrap is really discussing the main topic that is about Omnibus Law


1989 ◽  
Vol 2 (1) ◽  
pp. 18-24
Author(s):  
Douglas H. Rapelje

After two years of design research, the near-term goal of the Senior Citizens Department, Regional Niagara, was to build innovative homes to address the issues and programs the studies revealed. The long-term objective was to build homes that would start to change the public perception of long-term care facilities. Featuringa “Town Square”, the home comprises five houses of 20 beds, each providing a different level of care. Corridors are a unique design, and each house has its own dining room facilities and activity room. A central Day Care lounge features dining room facilities for family and friends. The Department hopes the overall design will help to break down the stereotype image of long-term care design, an d provide a suitable environment for the mentally and physically frail, as well as ambulatory residents.


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