scholarly journals Public Perception of Artificial Intelligence in Medical Care: Content Analysis of Social Media

10.2196/16649 ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. e16649 ◽  
Author(s):  
Shuqing Gao ◽  
Lingnan He ◽  
Yue Chen ◽  
Dan Li ◽  
Kaisheng Lai
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
Content Analysis ◽  
Medical Care ◽  
General Public ◽  
Public Perception ◽  
Public Attitudes ◽  
Negative Attitudes ◽  
Data Set ◽  
The Public

Background High-quality medical resources are in high demand worldwide, and the application of artificial intelligence (AI) in medical care may help alleviate the crisis related to this shortage. The development of the medical AI industry depends to a certain extent on whether industry experts have a comprehensive understanding of the public’s views on medical AI. Currently, the opinions of the general public on this matter remain unclear. Objective The purpose of this study is to explore the public perception of AI in medical care through a content analysis of social media data, including specific topics that the public is concerned about; public attitudes toward AI in medical care and the reasons for them; and public opinion on whether AI can replace human doctors. Methods Through an application programming interface, we collected a data set from the Sina Weibo platform comprising more than 16 million users throughout China by crawling all public posts from January to December 2017. Based on this data set, we identified 2315 posts related to AI in medical care and classified them through content analysis. Results Among the 2315 identified posts, we found three types of AI topics discussed on the platform: (1) technology and application (n=987, 42.63%), (2) industry development (n=706, 30.50%), and (3) impact on society (n=622, 26.87%). Out of 956 posts where public attitudes were expressed, 59.4% (n=568), 34.4% (n=329), and 6.2% (n=59) of the posts expressed positive, neutral, and negative attitudes, respectively. The immaturity of AI technology (27/59, 46%) and a distrust of related companies (n=15, 25%) were the two main reasons for the negative attitudes. Across 200 posts that mentioned public attitudes toward replacing human doctors with AI, 47.5% (n=95) and 32.5% (n=65) of the posts expressed that AI would completely or partially replace human doctors, respectively. In comparison, 20.0% (n=40) of the posts expressed that AI would not replace human doctors. Conclusions Our findings indicate that people are most concerned about AI technology and applications. Generally, the majority of people held positive attitudes and believed that AI doctors would completely or partially replace human ones. Compared with previous studies on medical doctors, the general public has a more positive attitude toward medical AI. Lack of trust in AI and the absence of the humanistic care factor are essential reasons why some people still have a negative attitude toward medical AI. We suggest that practitioners may need to pay more attention to promoting the credibility of technology companies and meeting patients’ emotional needs instead of focusing merely on technical issues.

scholarly journals Public Perception of Artificial Intelligence in Medical Care: Content Analysis of Social Media (Preprint)

2019 ◽  
Author(s):  
Shuqing Gao ◽  
Lingnan He ◽  
Yue Chen ◽  
Dan Li ◽  
Kaisheng Lai
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
Content Analysis ◽  
Medical Care ◽  
General Public ◽  
Public Perception ◽  
Public Attitudes ◽  
Negative Attitudes ◽  
Data Set ◽  
The Public

BACKGROUND High-quality medical resources are in high demand worldwide, and the application of artificial intelligence (AI) in medical care may help alleviate the crisis related to this shortage. The development of the medical AI industry depends to a certain extent on whether industry experts have a comprehensive understanding of the public’s views on medical AI. Currently, the opinions of the general public on this matter remain unclear. OBJECTIVE The purpose of this study is to explore the public perception of AI in medical care through a content analysis of social media data, including specific topics that the public is concerned about; public attitudes toward AI in medical care and the reasons for them; and public opinion on whether AI can replace human doctors. METHODS Through an application programming interface, we collected a data set from the Sina Weibo platform comprising more than 16 million users throughout China by crawling all public posts from January to December 2017. Based on this data set, we identified 2315 posts related to AI in medical care and classified them through content analysis. RESULTS Among the 2315 identified posts, we found three types of AI topics discussed on the platform: (1) technology and application (n=987, 42.63%), (2) industry development (n=706, 30.50%), and (3) impact on society (n=622, 26.87%). Out of 956 posts where public attitudes were expressed, 59.4% (n=568), 34.4% (n=329), and 6.2% (n=59) of the posts expressed positive, neutral, and negative attitudes, respectively. The immaturity of AI technology (27/59, 46%) and a distrust of related companies (n=15, 25%) were the two main reasons for the negative attitudes. Across 200 posts that mentioned public attitudes toward replacing human doctors with AI, 47.5% (n=95) and 32.5% (n=65) of the posts expressed that AI would completely or partially replace human doctors, respectively. In comparison, 20.0% (n=40) of the posts expressed that AI would not replace human doctors. CONCLUSIONS Our findings indicate that people are most concerned about AI technology and applications. Generally, the majority of people held positive attitudes and believed that AI doctors would completely or partially replace human ones. Compared with previous studies on medical doctors, the general public has a more positive attitude toward medical AI. Lack of trust in AI and the absence of the humanistic care factor are essential reasons why some people still have a negative attitude toward medical AI. We suggest that practitioners may need to pay more attention to promoting the credibility of technology companies and meeting patients’ emotional needs instead of focusing merely on technical issues.

scholarly journals Online public discourse on artificial intelligence and ethics in China: context, content, and implications

AI & Society ◽  
2021 ◽  
Author(s):  
Yishu Mao ◽  
Kristin Shi-Kupfer
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
General Public ◽  
Public Discourse ◽  
It Industry ◽  
The Public ◽  
Ethical Implications ◽  
The World ◽  
Ai Ethics ◽  
Social Media Platforms

AbstractThe societal and ethical implications of artificial intelligence (AI) have sparked discussions among academics, policymakers and the public around the world. What has gone unnoticed so far are the likewise vibrant discussions in China. We analyzed a large sample of discussions about AI ethics on two Chinese social media platforms. Findings suggest that participants were diverse, and included scholars, IT industry actors, journalists, and members of the general public. They addressed a broad range of concerns associated with the application of AI in various fields. Some even gave recommendations on how to tackle these issues. We argue that these discussions are a valuable source for understanding the future trajectory of AI development in China as well as implications for global dialogue on AI governance.

ANALISA YURIDIS HAK KEBEBASAN BERPENDAPAT BERDASARKAN KETENTUAN UNDANG-UNDANG NOMOR 19 TAHUN 2016 TENTANG PERUBAHAN ATAS UNDANG-UNDANG NOMOR 11 TAHUN 2008 TENTANG INFORMASI DAN TRANSAKSI ELEKTRONIK

2020 ◽  
Vol 18 (1) ◽  
pp. 001
Author(s):  
Eddy Suwito
Keyword(s):  
Social Media ◽  
General Public ◽  
Legal Information ◽  
The Public ◽  
Harm To Others ◽  
The Law ◽  
The Republic

The development of technology that continues to grow, the public increasingly facilitates socialization through technology. Opinion on free and uncontrolled social media causes harm to others. The law sees this phenomenon subsequently changing. Legal Information Known as Information and Electronic Transaction Law or ITE Law. However, the ITE Law cannot protect the entire general public. Because it is an Article in the ITE Law that is contrary to Article in the 1945 Constitution of the Republic of Indonesia.

A Comparative Content Analysis of Physician, General Public and Media Opinion Leader Posts Regarding Physician-patient Conflicts on Microblog (Preprint)

2020 ◽  
Author(s):  
Wanqi Gong ◽  
Qin Guo
Keyword(s):  
Content Analysis ◽  
Public Opinion ◽  
General Public ◽  
Public Perception ◽  
Medical Science ◽  
Popular Science ◽  
Opinion Leaders ◽  
Objective Evidence ◽  
Comparative Content ◽  
Physician Patient

BACKGROUND Physician-patient conflicts have increased more than ten times from the 2000s to 2010s in China and arouse heated discussion on microblog. However, little is known about similarities and differences among views of opinion leaders from the general public, physician, and media regarding physician-patient conflict issues on microblog. OBJECTIVE This study aimed to explore how opinion leaders from physician, the general public, and media areas framed the posts on major physician-patient conflict issues on microblog. Findings will provide more objective evidence of trilateral (health profession, general public, and media) attitudes and perspectives on physician-patient conflicts. METHODS A comparative content analysis was conducted to examine the posts (N=545) from microblog opinion leaders regarding the major physician-patient conflicts in China from 2012 to 2017. RESULTS Media used significantly more conflict (M=0.16) and attribution frames (M=0.16) but least popularize medical science frame (M=0.03) than physician (M=0.06, p<0.001; M=0.06, p<0.001; M=0.08, p=0.035, respectively) and general public opinion leaders (M=0.06, p<0.001; M=0.09, p=0.003; M=0.12, p<0.001, respectively). There are no significant differences in the use of conflict, cooperation, negative and popular science frames between general public and physician opinion leaders. CONCLUSIONS This imbalanced use of frames by media would cultivate and reinforce the public perception of physician-patient contradiction. The physician and general public opinion leaders share some commons in post frames, implying that they do not have a fundamental discrepancy on physician-patient conflict issues. It is essential to guide and encourage media microbloggers to make every effort to popularize medical science and improve physician-patient relationships.

scholarly journals ‘Ruined’ lives: Mediated white male victimhood

2021 ◽  
Vol 24 (1) ◽  
pp. 60-80
Author(s):  
Sarah Banet-Weiser
Keyword(s):  
Social Media ◽  
Sexual Harassment ◽  
Sexual Violence ◽  
Public Perception ◽  
White Male ◽  
The Public ◽  
Multi Media ◽  
Patriarchal Power ◽  
Almost All ◽  
False Accusations

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.

Public perception of COVID-19 vaccines from the digital footprints left on Twitter: analyzing positive, neutral and negative sentiments of Twitterati

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aasif Ahmad Mir ◽  
Sevukan Rathinam ◽  
Sumeer Gul
Keyword(s):  
Social Media ◽  
Public Perception ◽  
English Language ◽  
Social Issues ◽  
Application Programming Interface ◽  
Content Type ◽  
The Public ◽  
Public Reaction ◽  
Types Of Information ◽  
The Impact

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.

Self-Presentation of Female Athletes: A Content Analysis of Athlete Avatars

2016 ◽  
Vol 9 (4) ◽  
pp. 460-475 ◽  
Author(s):  
Megan B. Shreffler ◽  
Meg G. Hancock ◽  
Samuel H. Schmidt
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Web Sites ◽  
Female Athletes ◽  
Common Theme ◽  
Traditional Media ◽  
Self Presentation ◽  
The Public ◽  
Athletic Competence

Unlike traditional media, which frames female athletes in sexualized manners and in socially accepted roles such as mothers and girlfriends, user-controlled social-media Web sites allow female athletes to control the image and brand they wish to portray to the public. Using Goffman’s theory of self-presentation, the current study aimed to investigate how female athletes were portraying themselves via their Twitter avatar pictures. A total of 207 verified Twitter avatars of female athletes from 6 sports were examined through a content analysis. The avatars from each player were coded using the following themes: athlete as social being, athlete as promotional figure, “selfie,” athletic competence, ambivalence, “girl next door,” and “sexy babe.” The results revealed that athletic competence was the most common theme, followed by selfie and athlete as social being. Thus, when women have the opportunity to control their image through social media they choose to focus on their athletic identities.

How to Podcast in Archaeology

2018 ◽  
Vol 6 (3) ◽  
pp. 259-266
Author(s):  
Colin P. Amundsen ◽  
Cristina Belmonte
Keyword(s):  
Social Media ◽  
Digital Media ◽  
General Public ◽  
Public Archaeology ◽  
Social Media Marketing ◽  
Public Outreach ◽  
Trial And Error ◽  
Business World ◽  
The Public ◽  
Broad Approach

ABSTRACTThe problem for archaeologists doing public outreach could be that we do not know who our audience is. Marketing to just the public at large is an extremely broad approach filled with the pitfalls of not engaging enough of the public, so it might be necessary to first find out who within the general public would have the most interest in your discovery and then tailor your presentation to that audience. At the podcastCooking with Archaeologistswe are using digital media, social media marketing, and our experience from the business world to do just that. Podcasting has been a trial-and-error project filled with uncertainty and doubt, and for archaeologists engaged in public archaeology it might be a practical approach to reaching the public and a medium to build an engaged and interested audience. In this “how-to” article, we will reveal what we have learned from this exciting and somewhat demanding venture and suggest how podcasting is a democratizing venture that connects the public to archaeology and the archaeologist.

scholarly journals What the Public Think about Social Services: A Report from Scotland

2019 ◽  
Vol 50 (4) ◽  
pp. 1146-1166
Author(s):  
Trish McCulloch ◽  
Stephen Webb
Keyword(s):  
Social Services ◽  
Public Perception ◽  
Online Survey ◽  
Public Perceptions ◽  
Data Set ◽  
Service Workers ◽  
The Public ◽  
Welfare Institutions ◽  
Nationally Representative ◽  
Two Stages

Abstract This article reports on findings of a government-funded research project which set out to understand what the public think about social services in Scotland. The authors were particularly keen to examine issues of legitimacy, trust and licence to operate for social services as they are framed in public perceptions. Drawing on a national online survey of 2,505 nationally representative adults, the findings provide the first and largest empirical data set on public perceptions of social services in Scotland. Data analysis occurred in two stages and employed descriptive statistical measurement and cross-tabulation analysis. The findings indicate that, overall, people in Scotland are positive about social services and the value of their impact on society. Furthermore, they believe that social services perform a valuable public role. These findings are significant for debates surrounding social services and suggest that the Scottish public has a more positive view of social services than social service workers and welfare institutions typically perceive. The findings demonstrate the need to develop a more theoretically rich understanding of the relationships between public perception, legitimacy and social licence in social services, including attention to co-productive models of engagement.

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