From the president's desk: #EndCCStigma: Social media as a tool to change public perception of 2‐year colleges

2021 ◽  
Vol 2022 (197) ◽  
pp. 141-155
Author(s):  
Steve Robinson
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.


2021 ◽  
Author(s):  
Peng Jing ◽  
Yunhao Cai ◽  
Baihui Wang ◽  
Bichen Wang ◽  
Jiahui Huang ◽  
...  

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.


PERSPEKTIF ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 20
Author(s):  
Muhammad Wahyu Effendi ◽  
Yan Hendra ◽  
Armansyah Matondang

<h1>This research is based on the social media account of Instagram @humas_pemkomedan which contains the image of Medan City Government. The purpose of this study to determine the public perception about the image of Medan City Government through social media accounts Instagram. Theories used in this study include the theoretical description of communication, perception, society, image, social media, Instagram. The research method used is qualitative descriptive method. Selection of informants here is the people of Medan City who follow social media accounts Instagram @humas_pemkomedan and informants in this study following the principle of saturation where if the data needed is still less will be done addition of informants to get new information until the data obtained reach saturation point that if from the source is the same, then the data collection through the interview is stopped. Data collection   techniques  were  conducted   by  semi-structured interviews to all informants, and the results of this study showed that where the perception of the image is described into the first two aspects through Instagram profile and the second is the content of Instagram @humas_pemkomedan consisting of 6 categories of uploads are as follows: The activities of Medan city administration, news reports on work, information and appeal, congratulations, videos, figures, then Public Perceptions About Government Image Medan City Through Social Media Account Instagram is tend to be positive.</h1>


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.  


2019 ◽  
Vol 1 (2) ◽  
pp. 193-205
Author(s):  
Ria Andryani ◽  
Edi Surya Negara ◽  
Dendi Triadi

The amount of production data generated by social media opportunities that can be exploited by various parties, both government and private sectors to produce the information. Social media data can be used to know the behavior and public perception of the phenomenon or a particular event. To obtain and analyze social media data needed depth knowledge of Internet technology, social media, databases, data structures, information theory, data mining, machine learning, until the data and information visualization techniques. In this research, social media analysis on a particular topic and the development of prototype devices software used as a tool of social media data retrieval or retrieval of data applications. Social Media Analytics (SMA) aims to make the process of analysis and synthesis of social media data to produce information can be used by those in need. SMA process is done in three stages, namely: Capture, Understand and Present. This research is exploratorily focused on understanding the technology that became the basis of social media using various techniques exist and is already used in the study of social media analytic previously.


2019 ◽  
Vol 3 (1) ◽  
pp. 6-11
Author(s):  
Wayne W. L. Chan ◽  

The legal authorities, particularly the police force, have been increasingly facing challenges given the popularity of social media [1, 2]. However, we know very little about how public perceptions of the police are being shaped by social media. In this context, this study attempted to investigate the impact of social media on young people’s perceptions of the police in Hong Kong. The focus of this study was placed on Facebook since it was one of the most popular social media platforms in the city. Facebook was not only conceptualized as a communication medium but also a social networking arena. In this connection, qualitative individual interviews were conducted to explore the online social networking on Facebook and its relation to the perceptions of police force. It was found that the Facebook users who were more likely to stay closely connected with other users with similar views would tend to form the politicized perception of police force. On the other hand, the Facebook users who were to be networked with some other users or real persons with dissimilar views would hold more neutral perceptions of the police. This study was the first of its kind to investigate the role of online social networking in the perceptions of the police, thus filling an important gap in our knowledge of the increasing impact of social media. Therefore, the results of current study were expected to contribute to society by avoiding the disproportionate public discourse about law and order. Keywords: Social Media, Online Social Networking, Public Perception, Police Force.


2021 ◽  
Author(s):  
Brent Pretty

As of late there's been great interest in social media’s ability to predict elections. Platforms such as Twitter and Facebook, owing to their cultural ubiquity, offer a plethora of data and an opportunity to track public perception at a granular level in real time. The ability to passively analyze public opinion is a massive step forward in the realm of political prediction, and has the potential to redefine the field of campaign strategy. In this piece of research I analyzed the current state of social media based electoral prediction. I examined the methods and techniques used to collect and analyze data, and compared their results against both each other and other methods of prediction such as telephone polling. In this I found a field that is still in its infancy. Much work remains to be done until a set of best practices surrounding social media based electoral prediction are accumulated.


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