Public interest in science or bots? Selective amplification of scientific articles on Twitter

Negative sentiments toward anterior cruciate ligament injury prevention outweigh positive awareness discussions on social media

Mark Pearson Blogging & Tweeting without Being Sued: A Global Guide to the Law for Anyone Writing Online. Sydney: Allen & Unwin, 2012. 222 pp.What makes the twenty-first century truly global? To this question, journalism and mass communication educators and students most likely will respond, Internet. Few of those outside journalism and mass communication will demur. No matter what we are doing on the Internet, we are engaging in global communication-wittingly or unwittingly.Journalism professor Mark Pearson, formerly of Bond University and currently of Griffith University in Australia, is keenly aware of the Internet's transnational impact on our communication in its legal context. His small book, titled Blogging & Tweeting without Being Sued, is for those social media users who tend to ignore their status as international publishers (p. ix).Pearson, who specializes in media law, notes, My aims are modest: to introduce you to some common legal principles that broadly apply to online publishing in many parts of the world and to bring to life with the stories of bloggers and social media users who have encountered them (p. x).These days, more books on the law of social media are on the market. For example, Social Media and the Law (Daxton R. Stewart, ed., 2013) and Social Media and the Law (Kathryn L. Ossian, ed., 2013) have been published this year. The former is guidebook for communication students and professionals, while the latter targets law practitioners as a legal treatise. The of these and other social media law books should be hardly surprising. As a New York judge stated in 2012, reality of today's world is that social media, whether it be Twitter, Facebook, Pinterest, Google+ or any other site, is the way people communicate (People v. Harris, 945 N.Y.S.2d 505, 507 n.3, N.Y. Crim. Ct. 2012).What sets Pearson's book apart from other social media books? It is globally encompassing (Let's think globally), and it is refreshingly informative and readable. Nearly all the major topics are examined in the nine-chapter book: defamation (Ch. 2), free speech versus fair trial (Ch. 3), anonymous speech (Ch. 4), privacy (Ch. 5), con- fidentiality (Ch. 6), hate speech (Ch. 7), copyright (Ch. 8), and censorship and national security (Ch. 9).Chapter 1: Down to Basics surveys the risks of going global in a flash by high- lighting several Internet cases. It touches on conflict of laws, publication in libel law, interest (the public has a stake) versus public's interest (the public is just curious), and other significant legal concepts.American law is treated more extensively in the book than is the law of other coun- tries. The defamation chapter is a case in point. Pearson discusses Section 230 of the U.S. Communications Decency Act that immunizes Internet Service Providers (ISPs) from liability for third parties' comments. He also points out the American actual rule as a uniquely media-friendly defense against libel lawsuits by public figures. In this connection, he could have more clearly differentiated the constitutional malice (knowing falsity or reckless disregard for the truth) in the First Amendment law from the common law malice (spite or ill will).Pearson is correct: First Amendment doesn't have a passport. As an illustra- tion, he tells the story of the U.S.-based blogger Gopalan Nair, a native of Singapore. Nair was jailed in Singapore for sixty days for blogging his bare-knuckled criticisms of a Singaporean judge. …

During the COVID-19 pandemic, social media became increasingly relied upon for health information in Canada. By analyzing georeferenced tweets using natural language processing, we aimed to understand regional discussions and concerns about school closures, masking, vaccines, and lockdowns during the pandemic's first two years. Using Twitter's application programming interface, we collected English-language tweets with keywords related to COVID-19 posted between January 1, 2020 and February 22, 2022 from Canadian users. Out of all retained tweets, 2,851,951 (47.9%) were about vaccines, 1,344,008 (22.6%) about lockdowns, 1,011,909 (17%) about schooling, and 752,014 (12.6%) about masking. Tweets on schooling received the most engagement, with the highest rates of likes (17.3%), retweets (18.7%), replies (10%), and quotes (6.8%). The most common emotions expressed were trust, fear, and anticipation, with lockdown tweets showing greater fear and sadness. Overall, sentiment was negative, particularly regarding lockdowns in the Northwest Territories and Alberta. During the COVID-19 pandemic, Twitter became an essential tool for analyzing public sentiment regarding government actions. Users showed the most interest in vaccines, followed by lockdowns, schooling, and masking, with the highest engagement on schooling tweets. Our analysis of sentiment, emotion, and content revealed valuable insights into public beliefs about COVID-19 in Canada, highlighting regional differences and shifts in sentiment, particularly negative reactions to school closures as government recommendations evolved. Our study adds to the growing evidence supporting the use of natural language processing for real-time analysis of social media content to early identify public health concerns.

Colorectal cancer (CRC) is the second leading cause of cancer-related mortality worldwide. Social media platforms such as Twitter are extensively used to communicate about cancer care, yet little is known about the role of these online platforms in promoting early detection or sharing the lived experiences of patients with CRC. This study tracked Twitter discussions about CRC and characterized participating users to better understand public communication and perceptions of CRC during the COVID-19 pandemic. Tweets containing references to CRC were collected from January 2020 to April 2021 using Twitter's Application Programming Interface. Account metadata was used to predict user demographic information and classify users as either organizations, individuals, clinicians, or influencers. We compared the number of impressions across users and analyzed the content of tweets using natural language processing models to identify prominent topics of discussion. There were 72,229 unique CRC-related tweets by 31,170 users. Most users were male (66%) and older than 40 years (57%). Individuals accounted for most users (44%); organizations (35%); clinicians (19%); and influencers (2%). Influencers made the most median impressions (35,853). Organizations made the most overall impressions (1,067,189,613). Tweets contained the following topics: bereavement (20%), appeals for early detection (20%), research (17%), National Colorectal Cancer Awareness Month (15%), screening access (14%), and risk factors (14%). Discussions about CRC largely focused on bereavement and early detection. Online coverage of National Colorectal Cancer Awareness Month and personal experiences with CRC effectively stimulated goal-oriented tweets about early detection. Our findings suggest that although Twitter is commonly used for communicating about CRC, partnering with influencers may be an effective strategy for improving communication of future public health recommendations related to CRC.

Twitter has withstood the test of time as a successful social networking platform. In many circles globally, the majority of users choose Twitter when choosing a social media outlet for reliable scientific information and news. However, the Twitter application programming interface (API) limitations do not allow for low-cost data science options for academia. It becomes very expensive for academic researchers to gain the full potential of data analytics available from Twitter using a free API account. In this article, we present our big data analytics platform developed at our DaTALab at Lakehead University, Canada, that allows users to focus on their Twitter search criteria and gain access to large amounts of Twitter data at the touch of a button. The platform supports the collection of social media data and applies many filters for cleaning and further use for machine learning (ML) and artificial intelligence (AI)-based systems. Our focus has been primarily on healthcare-related research, which shows the strength of the presented platform. However, the platform itself is malleable to any topic of interest. Data collected and processed are suitable for further AI/ML analysis. We present our platform using a specific healthcare search topic to emphasize the power of our system for future research endeavors in the healthcare field.

Correlated or synchronized bots commonly exist in social media sites such as Twitter. Bots work towards gaining human followers, participating in campaigns, and engaging in unethical activities such as spamming and false click generation. In this paper, we perform temporal pattern mining on bot activities in Twitter. We discover motifs (repeating behavior), discords (anomalous behavior), joins, bursts and dynamic clusters in activities of Twitter bots, and explain the significance of these temporal patterns in gaining competitive advantage over humans. Our analysis identifies a small set of indicators that separates bots from humans with high precision.

Swedish Radio is nowadays broadcasting three daily science news shows during prime time, but this has not always been the case. In fact, ten years ago very few people believed that there would be any public interest in science at all. Even fewer would have guessed that Science News would be among the highest public ratings and lead the list of downloaded pod radio. This chapter tells the story about how Science News was established. One of the bigger obstacles to get science in the news was not the lack of curiosity among the audience but rather the lack of interest of colleagues in the media. Traditionally, people working in media have a non-scientific education and it is therefore possible to see this as a confrontation between the two cultures, first described by C. P. Snow. As a journalist dealing with science you have to work on two fronts, the first being to tell the public how crucial development in science is for their daily life and the second to convince colleagues within the media that science is an essential part of our society today. Europe, for several reasons, needs to cultivate professional science journalism and build a network among people working in the field. This work is essential as the research of today will be on the front page tomorrow

The relationship between science and civil society is essential to our understanding of cultural change during the Victorian era. Science was frequently packaged as an appropriate form of civic culture, inculcating virtues necessary for civic progress. In turn, civic culture was presented as an appropriate context for enabling and supporting scientific progress. Finnegan's study looks at the shifting nature of this process during the nineteenth century, using Scotland as the focus for his argument. Considerations of class, religion and gender are explored, illuminating changing social identities as public interest in science was allowed - even encouraged - beyond the environs of universities and elite metropolitan societies.

BackgroundThe rollout of COVID-19 vaccines has brought vaccine hesitancy to the forefront in managing this pandemic. COVID-19 vaccine hesitancy is fundamentally different from that of other vaccines due to the new technologies being used, rapid development, and widespread global distribution. Attitudes on vaccines are largely driven by online information, particularly information on social media. The first step toward influencing attitudes about immunization is understanding the current patterns of communication that characterize the immunization debate on social media platforms.ObjectiveWe aimed to evaluate societal attitudes, communication trends, and barriers to COVID-19 vaccine uptake through social media content analysis to inform communication strategies promoting vaccine acceptance.MethodsSocial network analysis (SNA) and unsupervised machine learning were used to characterize COVID-19 vaccine content on Twitter globally. Tweets published in English and French were collected through the Twitter application programming interface between November 19 and 26, 2020, just following the announcement of initial COVID-19 vaccine trials. SNA was used to identify social media clusters expressing mistrustful opinions on COVID-19 vaccination. Based on the SNA results, an unsupervised machine learning approach to natural language processing using a sentence-level algorithm transfer function to detect semantic textual similarity was performed in order to identify the main themes of vaccine hesitancy.ResultsThe tweets (n=636,516) identified that the main themes driving the vaccine hesitancy conversation were concerns of safety, efficacy, and freedom, and mistrust in institutions (either the government or multinational corporations). A main theme was the safety and efficacy of mRNA technology and side effects. The conversation around efficacy was that vaccines were unlikely to completely rid the population of COVID-19, polymerase chain reaction testing is flawed, and there is no indication of long-term T-cell immunity for COVID-19. Nearly one-third (45,628/146,191, 31.2%) of the conversations on COVID-19 vaccine hesitancy clusters expressed concerns for freedom or mistrust of institutions (either the government or multinational corporations) and nearly a quarter (34,756/146,191, 23.8%) expressed criticism toward the government’s handling of the pandemic.ConclusionsSocial media content analysis combined with social network analysis provides insights into the themes of the vaccination conversation on Twitter. The themes of safety, efficacy, and trust in institutions will need to be considered, as targeted outreach programs and intervention strategies are deployed on Twitter to improve the uptake of COVID-19 vaccination.

BACKGROUNDIn the Spring of 2020, residency programs across the country experienced rapid and drastic changes to their application process as a result of the coronavirus disease 2019 (COVID-19) pandemic. In response, residency programs shifted to virtual events and began harnessing social media to communicate with applicants.AIMTo analyze the changes in social media usage by orthopaedic surgery programs in response to the COVID-19 pandemic.METHODSBased on the 2019 residency and fellowship electronic database, accredited US orthopaedic surgery programs were reviewed for social media presence on Instagram and Twitter. Approximately 47000 tweets from 2011-2021 were extracted through the Twitter application programming interface. We extracted: Total number of followers, accounts following, tweets, likes, date of account creation, hashtags, and mentions. Natural language processing was utilized for tweet sentiment analysis and classified as positive, neutral, or negative. Instagram data was collected and deemed current as of August 11, 2021. The account foundation date analysis was based on the date recognized as the start of the COVID-19 outbreak in the United States, before or after March 1, 2020.RESULTSA total of 85 (42.3%) orthopaedic surgery residency program Twitter handles were identified. Thirty-five (41.2%) programs joined Twitter in the nine months after the 2020 covid outbreak. In 2020, there was a 126.6% increase in volume of tweets by orthopaedic surgery residency accounts as compared to 2019. The median number of followers was 474.5 (interquartile range 205.0-796.5). The account with the highest number of tweets was Hospital for Special Surgery (@HSpecialSurgery) with 13776 tweets followed by University of Virginia (@UVA_Ortho) with 5063 and Yale (@OrthoAtYale) with 899. Sentiment analysis before 2020 revealed 30.4% positive, 60.8% neutral, and 8.8% negative sentiments across tweets. Interestingly, the positive sentiment percentage increased in 2020 from 30.4% to 34.5%. Of the 201 ACGME-accredited orthopaedic residency programs on Fellowship and Residency Electronic Interactive Database, 115 (57.2%) participate on Instagram, with 101 (87.8%) identified as “resident”-managed vs 14 (12.2%) identified as “department”-managed. Over three quarters (77.4%) of Instagram accounts were created after March 1, 2020. The average number of followers per account was 1089.5 with an average of 58.9 total posts. CONCLUSIONOur study demonstrates a substantial growth of Instagram and Twitter presence by orthopaedic surgery residency programs during the COVID-19 pandemic. These data suggest that orthopaedic residency programs have utilized social media as a new way to communicate with applicants and showcase their programs in light of the challenges presented by the pandemic.

Artificial intelligence (AI) is creating a revolution in business and society at large, as well as challenges for organizations. AI‐powered social bots can sense, think and act on social media platforms in ways similar to humans. The challenge is that social bots can perform many harmful actions, such as providing wrong information to people, escalating arguments, perpetrating scams and exploiting the stock market. As such, an understanding of different kinds of social bots and their authors’ intentions is vital from the management perspective. Drawing from the actor‐network theory (ANT), this study investigates human and non‐human actors’ roles in social media, particularly Twitter. We use text mining and machine learning techniques, and after applying different pre‐processing techniques, we applied the bag of words model to a dataset of 30,000 English‐language tweets. The present research is among the few studies to use a theory‐based focus to look, through experimental research, at the role of social bots and the spread of disinformation in social media. Firms can use our tool for the early detection of harmful social bots before they can spread misinformation on social media about their organizations.

Network distribution and sentiment interaction: Information diffusion mechanisms between social bots and human users on social media

Rise of social bots: The impact of social bots on public opinion dynamics in public health emergencies from an information ecology perspective

Automated agents (“bots”) have emerged as an ubiquitous and influential presence on social media. Bots engage on social media platforms by posting content and replying to other users on the platform. In this work we conduct an empirical analysis of the activity of a single bot on Reddit. Our goal is to determine whether bot activity (in the form of posted comments on the website) has an effect on how humans engage on Reddit. We find that (1) the sentiment of a bot comment has a significant, positive effect on the subsequent human reply, and (2) human Reddit users modify their comment behaviors to overlap with the text of the bot, similar to how humans modify their text to mimic other humans in conversation. Understanding human-bot interactions on social media with relatively simple bots is important for preparing for more advanced bots in the future.

After the outbreak of the Russia-Ukraine war, social media become the major contested field for both sides. Social bots are widely involved in the Russia-Ukraine war discussion as communication actors. However, how social bots build the war agenda has not been well answered. This study explores the role of social bots through time series analysis and Structural Topic Model. The study finds that at the aggregate level there is a two-way agenda-setting between social bots and human accounts, and at the secondary level, social bots show different or even opposite agenda-setting effects in national/regional discussion. In addition, we find that social bots exhibit multiple positions in the conversation, reflecting the complexity of the manipulators behind them. This multiplicity of positions reveals that the role played by social bots is still based on the opposition of one side to the other, and the end result may exacerbate the conflict of online public opinion.